research paper on mung bean

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• Published: 15 July 2021

Mechanism for enhancing the growth of mung bean seedlings under simulated microgravity

• Shusaku Nakajima   ORCID: orcid.org/0000-0002-8704-6532 1 , 2 ,
• Masayasu Nagata 2 &
• Akifumi Ikehata 2  

npj Microgravity volume  7 , Article number:  26 ( 2021 ) Cite this article

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• Agriculture
• Plant sciences

To elucidate a mechanism for enhancing mung bean seedlings’ growth under microgravity conditions, we measured growth, gene expression, and enzyme activity under clinorotation (20 rpm), and compared data obtained to those grown under normal gravity conditions (control). An increase in fresh weight, water content, and lengths were observed in the clinostat seedlings, compared to those of the control seedlings. Real-time PCR showed that aquaporin expression and the amylase gene were upregulated under clinorotation. Additionally, seedlings under clinorotation exhibited a significantly higher amylase activity. Near-infrared image showed that there was no restriction of water evaporation from the seedlings under clinorotation. Therefore, these results indicate that simulated microgravity could induce water uptake, resulting in enhanced amylase activity and seedling growth. Upregulated aquaporin expression could be the first trigger for enhanced growth under clinorotation. We speculated that the seedlings under clinorotation do not use energy against gravitational force and consumed surplus energy for enhanced growth.

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Introduction.

Space, which is the final frontier for humans, can be a new source of water, minerals, and human habitation 1 , 2 . However, an abnormal space environment, notably microgravity, causes severe unfavorable effects, such as bone loss, cardiovascular disease, lung deformation, and DNA damage 3 , 4 , 5 , 6 , 7 . Since the phytochemical components of fresh vegetables contribute to reducing these risks, similar cultivation systems here on the Earth are essential for future long-duration space missions. Microgravity is a unique environment that induces physical and physiological changes in plants, and a comprehensive understanding of plant growth and development under microgravity is required for space agriculture.

Because of limited access to spaceflight, rotation devices, such as a clinostat (CL) and Radom Positioning Machine (RPM), have been used to generate microgravity here on the Earth. Although simulated microgravity is not the same as real microgravity in space 8 , 9 , these devices can cultivate plants repeatedly at a low cost. Recent studies have demonstrated that a fast rotating system with a small radius around a rotating axis can provide better microgravity than slow rotating system and RPM 10 , 11 , 12 . Therefore, most researchers cultivating plants under clinorotation employed fast rotation speed 20–60 rpm, depending on sample size 13 , 14 .

Previous experiments performed in space and by ground-based simulations have revealed that microgravity can enhance growth and phytochemical properties at the early developmental stage of specific plants. For instance, Arabidopsis grown in space developed longer seedlings and larger leaves, compared to the ground control 15 , 16 . Root elongation was reported in sweet potato grown in space, Brassica napus L. (1 rpm) and mung bean (2 rpm) grown under clinorotation 17 , 18 , 19 . Additionally, a higher accumulation of phytochemical components was found in Brassica rapa L. and soybean seedlings during spaceflight 20 , 21 . There are reports on the enhanced antioxidant activity of mung bean seedlings grown under clinorotation (2 rpm) and antidiabetic properties of wheatgrass grown under RPM 19 , 22 . The rapid growth will contribute to shorter cultivation and enhanced phytochemical properties, as a countermeasure against the dangerous space environment. However, little is known about the mechanism of microgravity and its positive effects on the early developmental stage of seedlings.

Seed germination is triggered by water uptake, after a lag phase, followed by radicle elongation 23 . Subsequently, reserve energy accumulated in seeds is hydrolyzed by specific enzymes for seedling growth. Aquaporin is an intrinsic protein that governs water transport in various processes, including germination 24 , 25 . Furthermore, in the case of legumes, the degradation of accumulated starch in seeds begins with the synthesis of α-amylase activated by absorbed water, and the conversion of starch to oligosaccharides, which is further hydrolyzed to maltose by β-amylase 26 . Maltose is then hydrolyzed by α-glucosidase with the release of glucose, which plays a significant role in fueling plant growth and development before the leaves can begin to photosynthesis. Thus, we hypothesized that microgravity affects water uptake and energy hydrolysis involved in germination and early growth.

This study aims to elucidate the cause of enhanced growth under microgravity conditions. Therefore, we cultivated mung bean under clinorotation, and measured aquaporin and amylase activity involved in water uptake and energy hydrolysis during germination. Data for enhanced growth due to aquaporin and amylase activity of seedlings grown under clinorotation are shown in the Results and Discussion section in this article.

Growth of seedlings

The growth of mung bean seedlings under the control and clinorotation is shown in Table 1 . The fresh weight and water content of seedlings under grown clinorotation were significantly higher than those grown under the control conditions. Additionally, the seedlings grown under clinorotation developed a significantly longer shoot and root than those grown under the control conditions. Similar results on the positive influence of microgravity in spaceflight and ground-based simulations were reported, as described in the Introduction.

Water distribution

To further examine the water state in seedlings grown under clinorotation, we monitored water distribution using a near-infrared (NIR) imaging system. Fig. 1 indicated both visible and NIR images of the control and CL seedlings. Although water content significantly increased under clinorotation (Table 1 ), there was no specific change in water distribution among seedlings grown under control and clinorotation. Water loss was suppressed in harvested mung bean seedlings under 3D-CL (2–4 rpm) compared to normal gravity conditions 27 , but no such feature was observed in the growth stage of the seedlings in this study. Stem elongation resulted in a higher water content under clinorotation than roots as seen in the NIR images.

a , b Visible images of seedlings. The cotyledon, stem, and root sections were marked by red. ( c , d ) The NIR images of same seedlings. The color bar indicates second derivative intensity at 1418 nm. The upper seedlings were grown under clinorotation and bottom seedlings were grown under the control conditions.

Aquaporin gene expression

We measured the gene expression of plasma membrane intrinsic proteins ( PIP ) and tonoplast intrinsic proteins ( TIP ) in the roots (Table 2 ). In mung bean roots, PIP1-2 and PIP2-1 expressions were higher than other aquaporins. While no changes in PIP2-1 and PIP2-2 expression, the PIP1-2 , PIP1-4 , TIP1-1 , and TIP1-3 were significantly activated in the seedlings grown under clinorotation. The increase in water content under clinorotation was either due to enhanced water uptake or reduced evaporation. If the latter is the case, water should be accumulated in the seedlings, resulting in water distribution changes under clinorotation. However, that was not the case based on the NIR image (Fig. 1b ). Thus, upregulated aquaporin expressions indicate that higher water content in seedlings under clinorotation could be due to enhanced water uptake ability.

Amylase gene expression and activity

The amylase gene expression and amylase activity in cotyledons are shown in Table 3 and Fig. 2 , respectively. The expression of four amylase genes encoding α-amylase and β-amylase were significantly higher in the cotyledons grown under clinorotation. Additionally, the cotyledons of seedlings under clinorotation exhibited 27% higher amylase activity. These results showed that starch hydrolyzed enzymes in cotyledons were activated under clinorotation.

Asterisks indicate significant difference between control and clinorotation.

In this study, we showed that simulated microgravity generated by clinorotation promotes gene expression and hydrolysis enzyme activity involved in the germination process, as hypothesized. Notably, the upregulated aquaporin expression could be the trigger for enhanced growth under microgravity because water uptake is the first step in germination and subsequent growth. Terrestrial plants have adapted to the constant gravitational condition here on the Earth after evolution from the sea and must consume energy to maintain homeostasis against gravitational force 28 . In contrast, plants grown under microgravity do not need such energy, as shown in previous reports. Protoplasts isolated from tobacco used less metabolic energy for regeneration during spaceflight 29 . Soleimani et al. 14 also observed an increase in growth and metabolism of tobacco cells grown under clinorotation (20 rpm), which suggests that an energy-saving process occurs under simulated microgravity. Apart from other organisms, the use of less energy was observed in human lung cells cultivated in space 30 . Therefore, we speculated that the mung bean seedlings grown under clinorotation exhibited a similar energy-saving process and used its surplus energy for upregulating aquaporin expression.

Aquaporin expression and water flow under microgravity are significant subjects of discussion in space experiments. Jing et al. 31 observed a similar upregulation of aquaporins in rice calli. Wang et al. 32 also observed an enhanced guttation in rice seedlings, therefore suggesting that water uptake and transport are easier under microgravity. These data from previous studies agree with data obtained in this study on the upregulation of aquaporin and higher water content under clinorotation. Although the detailed roles of aquaporins are still underdetermined, previous plant studies have revealed that PIP1 and TIP1 , which are upregulated under clinorotation (Table 2 ), are involved in cell division and tissue elongation after germination. For example, in the positive control using an aquaporin activator, increased water content and elongation were observed in various germinating seedlings 33 , 34 . Alternatively, in the negative control using an aquaporin inhibitor, a lower expression of aquaporin resulted in delayed or abnormal growth 25 . These results support the fact that upregulated aquaporin enhances growth under clinorotation.

Since there are a few reports on amylase activity in germinating seedlings grown under microgravity, it is difficult to compare our data with that of previous studies directly. However, α-amylase activity is significantly suppressed in wheat seedlings exposed to hypergravity 35 , 36 . Generally, the influence of microgravity and hypergravity is opposite, and there is the possibility that amylase activity is promoted in wheat seedlings germinating under microgravity conditions. Since starch is accumulated in wheat seeds as reserve energy like in mung bean, these results suggest that microgravity induces amylase activity in these types of seeds.

A potential mechanism for enhanced growth and phytochemical properties in mung bean seedlings under clinorotation observed in this, and previous studies 19 is shown in Fig. 3 . Clinorotation first activates aquaporin activity in roots (Table 2 ) and could promote water uptake ability. The enriched water condition in the seedlings under clinorotation further induces amylase gene expression encoding α- and β-amylase (Table 3 ), resulting in higher amylase activity in cotyledons (Fig. 2 ). Our previous study showed that starch accumulated in seeds is rapidly degraded under clinorotation, and the seedlings could have more sugars converted from starch 19 . We believe that these sugars may be involved in the enhanced growth and phytochemical properties under clinorotation. Indeed, upregulated aquaporin expression could be the first step for enhanced growth under clinorotation.

The green area was observed in roots, whereas the blue area was observed in cotyledons. Parentheses are discussions and not obtained data.

The positive effects of microgravity on the early developmental stage of plants have been reported, but the leading cause for this is still unknown. In contrast, we discovered that simulated microgravity generated by clinorotation activated aquaporin and hydrolyzed enzymes in mung bean seedlings, thereby resulting in enhanced growth. These results strongly recommended that similar plants with enhanced aquaporin and hydrolyzed enzymes under microgravity are suitable for space agriculture. Since the effects of microgravity vary on plant species 37 , further investigation on gene expression in other plants is needed. Additionally, there is a need for further experiments to be conducted in real microgravity in space for a more comprehensive understanding of microgravity effect.

Plant materials and growth conditions

Seedlings were rotated under a similar experimental system used in our previous study 19 . The CL consisted of an AC servo motor (SGMAH-A5BAA21, Yasukawa Electric, Japan) and a cylindrical acrylic housing (9.4 cm diameter × 9.0 cm height), which were filled with 0.8% (w/w) agar medium (3.0 cm depth). Eight seeds were germinated and cultivated in the center of the rotation axis within a circle of 2 cm radius. In the CL experiment (Fig. 4 ), the rotor and seedlings axes were horizontal (i.e., perpendicular to the g-vector) and rotated at 20 rpm. At this rotation speed, centrifugal acceleration was 8.9 × 10 −3  g. Seedlings grown in the control conditions were cultivated in the housing and placed on the bottom of the same incubator. Seedlings in both growth conditions were cultivated in darkness at 25.0 ± 1.0 °C for 3 d. To obtain fundamental data, fresh weight, length, and water content were measured after 3 d of cultivation. According to a previous study 19 , stem sections between the cotyledon/hypocotyl interface and the hypocotyl/root interface were determined. We also determined root sections between the hypocotyl/root interface and the root tip. In addition, the water content was calculated by gravimetric determination, after seedlings were oven-dried at 80 °C for 3 d.

a Side and b front views. Eight mung bean seeds were placed in an acrylic housing at a distance of 2 cm from the axis in a circle and rotated at 20 rpm for 3 d.

NIR imaging

Since water has high absorption bands in the NIR regions, NIR spectra and images can monitor water content in plants 38 , 39 . To measure water distribution under clinorotation, hyperspectral NIR image was captured by Imspector N17E (Specim, Finland) in the range of 950–1600 nm, according to the previous method 39 with some modifications. We first measured the intensity of polytetrafluoroethylene (PTFE) reference reflector (Spectralon®, Labsphere, Inc., North Sutton, NH, USA), and obtained reflectance spectra of seedlings. After transforming absorbance spectra, we employed second derivative treatments and the intensities at 1418 nm of each pixel were used for NIR imaging.

Gene expression analysis

Measurement of gene expression was performed according to the method 40 . Seedlings were immediately frozen in liquid nitrogen after cultivation and stored at −80 °C until use. RNA was extracted using the RNeasy plant Mini Kit (Qiagen, Netherlands). The quality of RNA was measured by a UV spectrophotometer (Nano-200, Medclub Scientific, Taiwan) and cDNA was synthesized according to the method of PrimeScript RT reagent Kit with gDNA Eraser (Takara, Japan). Quantitative PCR was conducted in triplicate using the Thermal Cycler Dice Real Time System TP800 (Takara, Japan), with TB Green Premix Ex Taq II (Tli RNaseH Plus, Takara, Japan) and specific primers (Table 4 ). We analyzed the expression of four amylase genes in cotyledons, namely α-amylase , α-amylase 2 , β-amylase , and β-amylase 1 , and six aquaporin genes in roots, namely PIP1-2 , PIP1-4 , PIP2-1 , PIP2-2 , TIP1-1 , and TIP1-3 . The expression value of actin normalized relative expression values.

Amylase assay

Amylase activity was measured according to the method used in our previous study 19 with a few modifications. Fresh cotyledons were homogenized in 50 mM K-phosphate buffer (pH 6.8) immediately after cultivation and the supernatant was used for amylase assay after being centrifuged. A mixture, containing 0.5 mL 2.5% starch solution, 0.3 mL 0.1 M sodium acetate buffer (pH 5.5), and 0.1 mL Milli Q water reacted with 0.2 mL of plant extracts at 55 °C for 5 min. The reaction was stopped by the addition of 0.5 mL 1 M HCl, and 0.2 mL aliquot of this mixture was diluted with distilled water to 10 mL, including 0.1 mL 1 M HCl and 0.1 mL 0.2% iodine solution. A blank was prepared by adding the plant extracts after the addition of HCl stopped the reaction. The absorbance of the solution was measured at 610 nm using a spectrometer (U3900, Hitachi, Japan).

Statistical analysis

Thirty seedlings collected from at least four entirely independent experiments were used for growth measurements. Ten samples collected from at least three times entirely independent experiments were used for gene expression and α-amylase assay. We used the t -test to examine the difference between the control and clinorotation, and significant difference was accepted at p  < 0.05. All data were represented as means ± standard error.

Reporting summary

Further information on research design is available in the Nature Research Reporting Summary linked to this article.

Data availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

We thank Mr. Sakae Ohbayashi (National Agriculture and Food Research Organization) for designing the CL; Dr. Yoshikiyo Sakakibara (National Agriculture and Food Research Organization) for using his incubator; Dr. Takuma Genkawa (National Agriculture and Food Research Organization) for providing useful suggestions for NIR image analysis. Open access fee was supported by JSPS KAKENHI grant number 21K14948.

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S.N. and M.N. designed and conducted experiments. S.N. wrote the first draft of the paper and all authors contributed to the writing.

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Nakajima, S., Nagata, M. & Ikehata, A. Mechanism for enhancing the growth of mung bean seedlings under simulated microgravity. npj Microgravity 7 , 26 (2021). https://doi.org/10.1038/s41526-021-00156-6

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DOI : https://doi.org/10.1038/s41526-021-00156-6

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• Published: 09 October 2021

Nutritional, phytochemical and antioxidant properties of 24 mung bean ( Vigna radiate L.) genotypes

• Fuhao Wang 1 , 2   na1 ,
• Lu Huang 1   na1 ,
• Xingxing Yuan 1 ,
• Xiaoyan Zhang 1 ,
• Luping Guo 3 ,
• Chenchen Xue 1 &
• Xin Chen   ORCID: orcid.org/0000-0002-8292-7699 1 , 2 , 3  

Food Production, Processing and Nutrition volume  3 , Article number:  28 ( 2021 ) Cite this article

5687 Accesses

7 Citations

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This study aimed to investigate the proximate and phytochemicals present in seeds of 24 mung bean ( Vigna radiate L.) genotypes from four provinces of China for estimating their nutritional and antioxidant properties. Proximate analysis of mung bean genotypes revealed that starch, protein, fat, ash and water-soluble polysaccharide ranged from 39.54–60.66, 17.36–24.89, 4.24–12.18, 2.78–3.53 and 1.99–2.96 g/100 g respectively. The five principal fatty acids detected in mung beans were stearic acid, palmitic acid, linoleic acid, oleic acid, and linolenic acid. The contents of insoluble-bound phenolic compounds, soluble phenolic compounds, and flavonoids ranged from 0.78 to 1.5 mg GAE g − 1 , 1.78 to 4.10 mg GAE g − 1 , and 1.25 to 3.52 mg RE g − 1 , respectively. The black seed coat mung bean genotype M13 (Suheilv 1) exhibited highest flavonoid and phenolic contents which showed strong antioxidant activity. Two flavonoids (vitexin and isovitexin) and four phenolic acids (caffeic, syringic acid, p -coumaric, and ferulic acids) were identified by HPLC. Vitexin and isovitexin were the major phenolic compounds in all mung bean genotypes. The content of soluble phenolic compounds had positive correlation with DPPH ( r 2  = 0.713) and ABTS ( r 2  = 0.665) radical scavenging activities. Principal component analysis indicated that the first two principal components could reflect most details on mung bean with a cumulative contribution rate of 66.1%. Twenty-four mung bean genotypes were classified into four groups based on their phenolic compounds contents and antioxidant activities. The present study highlights the importance of these mung bean genotypes as a source of nature antioxidant ingredient for the development of functional foods or a source of health promoting food.

Graphical Abstract

Introduction

Mung bean ( Vigna radiate L.) is a species of Fabaceae plant which is well-known as green gram (Ganesan & Xu 2018 ). It has been widely grown in the Southeast Asia and is very common in consumer products around the world. Mung beans are rich in protein, starch, cellulose, minerals, and vitamins (Khaket et al. 2015 ). Studies have shown that mung bean has physiological functions such as anti-obesity, anti-oxidation, and anti-bacterial (Yao et al., 2013 ). Mung bean provides a high-quality natural plant protein source which has been used as a substitute for meat and milk protein in many underdeveloped countries (Connolly et al. 2015 ; Du et al. 2018 ). Studies have shown that mung bean polysaccharide has antioxidant and immunomodulatory activities (Lai et al. 2010 ). Moreover, the essential fatty acids (FAs) contained in mung beans can promote the growth and development of the body. In addition to its nutritional importance, mung beans are a rich source of phytochemicals including phenols and flavonoids that show health promoting effects such as antioxidants, anti-tumor and anti-radiation (Randhir & Shetty 2007 ; Soucek et al. 2005 ). Phenolic phytochemicals are the largest category of phytochemicals and the most widely distributed in plant (King & Young 1999 ). They mainly exist in free, soluble bound and insoluble bound forms (Alshikh et al. 2015 ; Jung et al. 2002 ).

Mung beans are commonly consumed food legume in Asian countries. Seeds of mung beans have been used to prepare a variety of fresh, fermented and dried foods. They are very popular foods in China and are known as “green pearls.” Mung beans are often used in food processing, such as mung bean porridge, mung bean soup, bean paste, mung bean cake, and raw bean sprouts. They can also be used as jelly, noodles, and vermicelli due to their high starch content. In addition, they are good raw materials for famous wines. Mung bean protein has excellent functional properties such as solubility, water retention, emulsification, gelation, foaming, and foam stability. It has application prospects in flour products, meat products, dairy products, and beverages in the food processing industry. Protein beverages (protein milk, coffee bean milk) made from protein isolates have high nutritional value and high-quality.

Following a country-wide collection during the 1980′s, more than 5000 accessions of mung bean germplasm have been deposited in the National Crop Genebank of China (Liu et al. 2006 ; Wang et al. 2018 ). In despite of the abundant germplasm resources of mung bean, the diversity of nutritional composition is still unknown. Due to importance of mung bean and its products, it is necessary to investigate nutritional and phytochemical compounds across various genotypes. In this study, 24 mung beans genotypes from four provinces in China were collected for the following purposes: (1) compare their nutritional compositions, (2) analyze their phytochemicals contents, and (3) evaluate correlations between phytochemical compounds and antioxidant activities. Results of this study will provide a good basis for the assessment and application of different mung bean genotypes.

Materials and methods

Twenty-four mung bean genotypes (Fig.  1 ) were collected from four provinces: Shanxi (north of China), Shaanxi (northwest of China), Jiangsu (east of China), and Hebei (north of China). We selected six mung bean genotypes per province. Among them, M12-M18 genotypes come from our lab. Name and geographical origin of these genotypes are presented in Table  1 . Seeds of these genotypes were grown in the Liuhe Base of Jiangsu Academy of Agricultural Sciences.

Photos of 24 mung bean genotypes (M1–24)

2, 2-diphenyl-1-picrylhydrazyl (DPPH), 2, 2-azinobis (3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt (ABTS), ascorbic acid (vitamin C, Vc), Folin–Ciocalteu’s phenol reagent were purchased from Sigma-Aldrich Chemical Co. (St. Louis, MO, USA). All other reagents used were of analytical grade and purchased from Sodebio Reagent Co., Ltd. (Nanjing, Jiangsu, China).

Analysis of nutrient components

Protein content was determined by using Kjeldahl method with Kjeltec TM2300 Auto Sampler System (Foss Analytical, Hillerød, Denmark) (Thiex et al. 2002 ). Soxhlet extraction (Extraction System B-811, Buchi, Flawil, Sankt Gallen, Switzerland) with petroleum ether was used to determine crude fat content (AOAC 1990 ). Ash content was determined by using the combustion method with an electric muffle furnace (SX2–4-13, Leiyun Instruments, Shanghai, China) (AOAC 1990 ). Starch content was determined using a starch kit (BC0700, Solarbio Science & Technology Co., Ltd., Beijing, China).

Fatty acid composition

Fatty acid (FA) composition was determined according to the method of Zhang et al. ( 2013 ) with slight modifications. Briefly, 0.5 g mung bean powder was added in a 2 mL centrifuge tube with 1.5 mL n-hexane. The mixture was left overnight and then centrifuged at 8200  g for 5 min (Eppendorf Centrifuge 5804R, Hamburg, Germany). Then, 350 μL of sodium methoxide solution was added and vortexed for 1 h. After centrifugation, the supernatant was as used for high-performance gas chromatography analysis (Agilent 7890B, Agilent Technologies Inc., Wilmington, DE, USA).

Determination of water-soluble polysaccharide (WSP)

The WSP was determined according to Yao et al. ( 2016 ) with several modifications. The mung bean powder was extracted with 80% ethanol for 1 h and then centrifuged at 2000  g for 5 min. The supernatant was removed and extracted twice with distilled water at 90 °C for 3 h. After centrifugation, the supernatant was collected with Sevag reagent (chloroform:n-butanol = 4:1,v/v) and shaken for 10 min. The mixture was centrifuged at 2000  g for 5 min. The lower organic solvent and protein at the interface were then removed. The gelatin was denatured, and the upper polysaccharide solution was retained.

Preparation of standard curve: 10 mg of glucose standard solution was accurately weighed and dissolved in 10 mL to obtain 1 mg/mL glucose standard solution. The solution was diluted to 10, 20, 40, 60, 80, and 100 μg/mL. Then, 1.0 mL of the diluted solution was drawn, and 1 mL of distilled water was added. Immediately thereafter, 1.0 mL of a 6% phenol solution was added, and 5.0 mL of concentrated sulfuric acid was slowly added and shaken while adding. After mixing well, the solution was left to stand at room temperature for 20 min. The absorbance of the solution was measured at 490 nm by a spectrophotometer (Alpha-1101 m, Puyuan Instruments, Shanghai, China). Next, 1.0 mL of polysaccharide sample solution with certain concentration was drawn, and distilled water was added to make it 2.0 mL. The subsequent operation was the same as glucose labeling. The purity of the corresponding polysaccharide was calculated according to its absorbance value and standard curve.

Extract analysis

Preparation of ethanol extracts.

Mung bean powder (1 g) was mixed with 25 mL of 80% ethanol solution and extracted in a water bath for 4 h. The solution was cooled to room temperature and centrifuged at 15000  g for 15 min. The operation was repeated 2–3 times, and the obtained supernatant was mixed and concentrated. The volume was made to reach 20 mL with methanol and stored at − 20 °C for testing. The collected supernatants were examined for soluble phenolic compounds.

Determination of total flavonoid content

Total flavonoid content (TFC) was determined according to the method reported by Xie et al. ( 2015 ). The sample extract (250 μL) was mixed with 1.25 mL of distilled water, and 25 μL of 5% NaNO 2 was added to react for 6 min. Then, 150 μL of 10% AlCl 3 was added to react for 5 min. Finally, 0.5 mL of 1 M NaOH and 275 μL of distilled water were added to the mixture, and the absorbance was measured at 510 nm after 10 min. Rutin with different concentrations was plotted as the standard curve, and the results were expressed as rutin equivalents (RE).

The content of soluble phenolic compounds

The content of soluble phenolic compounds in the samples was determined by using the Folin-Ciocalteu method. The sample solution (400 μL) and 4.6 mL of deionized water were placed in a test tube, and 1 mL of Folin-Ciocalteu and 24 mL of 7.5% (w/v) of sodium carbonate solution were injected into the test tube. After reacting for 2 h at room temperature, the absorbance of the sample was measured at a wavelength of 760 nm. The standard curve was configured with different concentrations of gallic acid, and the results were expressed as gallic acid equivalents (GAE).

The content of insoluble-bound phenolic compounds

Extraction of insoluble-bound phenolic compounds was performed according to the method reported by Zhang et al. ( 2013 ). Briefly, 20 mL of NaOH (2 mol/L) was mixed with the residue left after extracting soluble phenolic compounds and incubated for 1 h at room temperature. The mixture was centrifuged at 4500  g for 5 min, and the supernatant was extracted and adjusted to pH 2 with HCl (6 mol/L). Then, an equal volume of ethyl acetate was added for extraction, and the extraction was repeated 3 times. The extract was mixed, evaporated to dryness by a rotary evaporator at 45 °C, reconstituted to 5 mL of methanol, and determined by using the Folin-Ciocalteu method.

High-performance liquid chromatography (HPLC) analysis of phenolic compounds

Agilent 1260 high performance liquid chromatography (Agilent Technologies Inc. Santa Clara, CA, USA) equipped with the Agilent Poroshell 120 EC-C18 Column was used to detect the main phenolic compounds in mung bean seeds. The mobile phase consisted of acetonitrile (A) and ultrapure water containing 0.1% trifluoroacetic acid (B). Gradient elution was performed as follows: 0–7 min, 5–30% A; 7–15 min, 30–40% A; 15–25 min, 40–50% A; 25–30 min, 50–95% A; 30–35 min, 95–5% A. The flow rate was set at 1.0 mL min − 1 and the injection volume was 10 μL. The column was operated at 30 °C. The wavelength of the detector was set at 280 nm. Quantification of phenolic compounds was carried out by an external standard method using calibration curves.

Evaluation of antioxidant capacity

Assay of dpph radical scavenging activity.

DPPH analysis was executed in line with the report of Chai et al. ( 2018 ). Briefly, DPPH was dissolved in methanol. Then, 0.5 mL of DPPH (0.4 mmol/L) and 0.5 mL of the extract were mixed to react in the dark at room temperature for 30 min. The absorbance was measured at 517 nm with a spectrophotometer. The results were expressed as μmol vitamin C per gram samples.

Assay of ABTS radical cation scavenging activity

ABTS radical cation scavenging assay was performed according to the method reported by Lee et al. ( 2011 ) with some modifications. ABTS radical ions were produced by mixing 7 mM ABTS aqueous solution with 2.45 mM K 2 S 2 O 8 aqueous solution, storing in the dark for 16 h, diluting 20 times with absolute ethanol before use, and storing at 30 °C. Next, 1.2 mL of ABTS ethanol solution was mixed with 300 μL of extract to react at 30 °C for 6 min. The absorbance was measured at 734 nm with a spectrophotometer. The results were expressed as μmol vitamin C per gram.

Hydroxyl radical scavenging ability

The hydroxyl radical scavenging ability was determined according to Xiao et al. ( 2015 ) with simple modifications. Briefly, 300 μL of FeSO 4 (9 mmol/L), 300 μL of H 2 O 2 and 300 μL of the extract were mixed. After shaking, the mixture was added with 300 μL of salicylic acid-ethanol (9 mmol/L) and incubated at 37 °C for 30 min. The absorbance was measured at 510 nm. The results were expressed as μmol vitamin C per gram samples.

Statistical analysis

All experiments were conducted in triplicate and results were expressed as mean ± standard deviation. The statistical significance of the results was obtained by one-way analysis of variance and PCA using SPSS version 21.0 software. The Pearson correlation coefficient was used to estimate the correlation between phytochemical compounds and antioxidant activities. PCA was used to assess the contribution of chemical components to mung beans.

Results and discussion

Nutritional compositions.

Protein and starch are the two most abundant nutritional components in mung bean seed. In this study, the protein and starch contents of 24 mung bean genotypes ranged from 17.36 to 24.89 g/100 g and 39.54 g/100 g to 60.66 g/100 g (Table  2 ), respectively. M6 (Jinlv 399) showed the highest contents of protein (24.89 g/100 g) and starch (60.66 g/100 g) which could be used for specific food processing, such as noodles and vermicelli. Compared with other legumes, mung beans have a higher carbohydrate content, predominantly starch (Tang et al. 2014 ). The contributions of ash were in the ranges of 2.78 to 3.53 g/100 g. The content of water-soluble polysaccharide (WSP) ranged from 1.99 to 2.96 g/100 g. M14 (Sulv 3) exhibited the highest content of WSP, while M2 showed the lowest value. The biological activity of polysaccharides has received attention, such as antioxidant and immunological activities.

Table 2 shows the crude fat content and FA composition of 24 kinds of mung beans. The content of crude fat ranged from 4.24 to 12.18 mg/g. High-performance gas chromatography was used for the analysis of FA in mung bean. Five principal FAs were observed and identified according to standards (Fig.  2 ). Peaks 1, 2, 3, 4 and 5 with the retention time of 2.402, 3.187, 3.318, 3.602 and 3.953 min were referred to as palmitic acid, stearic acid, oleic acid, linoleic acid and linolenic acid, respectively. Linoleic acid was the most abundant in mung bean and accounted for 38.95–44.74 percentage of the total fatty acids. A similar observation was reported by Anwar et al. ( 2007 ) who investigated fatty acid composition of different mung bean cultivars grown in Pakistan. Studies have shown that polyunsaturated fatty acids are important structural substances in the retina and neurons which can protect the vision. Polyunsaturated fatty acids have important physiological functions in human metabolism, such as esterification of cholesterol, lowering blood cholesterol and triglycerides (Yates et al. 2014 ).

High performance gas chromatogram of fatty acids in mung bean. Peaks 1, 2, 3, 4 and 5 were identified as palmitic acid, stearic acid, oleic acid, linoleic acid and linolenic acid

Contents of phytochemicals (total flavonoid content, insoluble-bound phenolic content and soluble phenolic content)

As shown in Table  3 , the total flavonoid content of 24 mung bean genotypes ranged from 1.25 to 3.52 mg RE g − 1 . M13 (Suheilv 1) presented the highest flavonoid content (3.52 mg RE g − 1 ) and M5 (Jinlv 995) presented the lowest flavonoid content. Flavonoids are general name of a group of chemicals including catechins, anthocyanidins, proanthocyanidins, flavonols, isoflavonoids and flavones (Luo et al. 2016 ). Flavonoids have important physiological functions such as anti-oxidation and anti-inflammatory (Zuk et al. 2019 ). Zhang et al. ( 2013 ) used acetone and water as extraction solvents, and the highest flavonoid content obtained was 6.0 mg g − 1 . This may be different from the extraction solvent. The nature of the raw materials itself also has a relationship, such as the difference in the color of the skin and the difference in maturity.

The contents of soluble and insoluble-bound phenolic compounds in 24 mung bean genotypes investigated are shown in Table 3 . The phenolic content of the soluble fraction ranged from 1.78 to 4.10 mg GAE g − 1 . Insoluble-bound phenolic content ranged from 0.78 to 1.5 mg GAE g − 1 . M13 genotype exhibited the highest content of both soluble and insoluble-bound phenolic compounds. Meanwhile, M22 had the lowest soluble phenolic content of 1.78 mg GAE g − 1 and M8 exhibited the lowest insoluble-bound phenolic content of 0.78 mg GAE g − 1 . The difference between soluble and insoluble-bound phenolic contents is significant, which is similar to Wang et al. ( 2016 ). A similar result was reported by de Camargo et al. ( 2015 ) who observed that the content of soluble phenolic compounds (free and esterified) was significantly higher than insoluble-bound fraction in peanut skin. The amount of phenolic compound is affected by genotype, agronomic habits (irrigation, fertilization, and pest management), harvest maturity, post-harvest storage, and climatic conditions (Mattila et al. 2005 ).

Identification of major phenolic compounds in mung bean seeds

Soluble and insoluble-bound phenolic compounds in mung bean seeds were identified by HPLC as shown in Fig.  3 and Table  4 . Peaks 1, 2, 3, 4, 5 and 6 with the retention time of 17.785, 18.534, 24.160, 29.017 and 29.731 min were referred to as caffeic acid, syringic acid, p -coumaric acid, ferulic acid, vitexin and isovitexin, respectively (Fig. 3 ). In the present study, six phenolic compounds were identified, including four phenolic acids (syringic, caffeic, p -coumaric, and ferulic acids) and two flavonoids (vitexin and isovitexin). Results showed that vitexin and isovitexin were the dominant phenolic compounds in all mung bean genotypes. This is consistent with a previous study (Yang et al. 2020 ). The vitexin content of soluble and insoluble-bound fractions ranged from 481.02 to 910.26 μg g − 1 and from 123.77 to 463.25 μg g − 1 , respectively. The isovitexin content of soluble and insoluble-bound fractions ranged from 568.57 to 1572.74 μg g − 1 and from 104.42 to 421.77 μg g − 1 , respectively. The isovitexin content in the soluble fractions of mung bean seeds were higher than their corresponding vitexin content. M13 showed the highest vitexin (910.26 μg g − 1 ) and isovitexin (1572.74 μg g − 1 ) contents in the soluble fractions of all studied mung beans. Large differences were found among all mung beans in the contents of both soluble and insoluble-bound flavonoids. The vitexin and isovitexin contents in the soluble fractions of mung beans are higher than that in the insoluble-bound fractions. The contents of individual phenolic acids in different bean varieties are also shown in Table 4 . Contrary to flavonoids, the contents of phenolic acids in the soluble fractions are lower than that in the insoluble-bound fractions. Shi et al. ( 2016 ) also reported that the average content of bound phenolic acids in the mung bean samples accounted for 89.8% of the total amount of phenolic acids. Insoluble-bound phenolic compounds can survive upper gastrointestinal digestion and are released from the colon by the effect of microorganism. Results suggested that caffeic acid was the major phenolic acid in mung bean cultivars, ranged from 2.45 to 15.12 μg g − 1 in the soluble fractions and from 2.38 to 16.46 μg g − 1 in the insoluble-bound fractions, respectively. Caffeic acid is an effective scavenger of the ABTS + and DPPH radicals, which has strong antioxidant activity (Gülin 2006 ). Syringic acid was not detected in all mung bean varieties except M18. Flavonoids and phenolic acids are regarded as the major compounds contributing to the total antioxidant activities of mung bean seeds (Shi et al. 2016 ).

High-performance liquid chromatogram of phenolic compounds in mung bean. Peaks 1, 2, 3, 4, 5 and 6 were identified as caffeic acid, syringic acid, p -coumaric acid, ferulic acid, vitexin and isovitexin

Antioxidant activity

The results of antioxidant activities are presented in Fig.  4 . Soluble phenolic compounds showed stronger antioxidant activity than insoluble-bound phenolic compounds. M23 (Jilv 9025) exhibited the strongest DPPH free radical scavenging ability (Fig. 4 a) for soluble phenolic compounds (4.44 μmol/g). At the same time, M13 had the strongest DPPH free radical scavenging ability for the insoluble-bound fraction (3.73 μmol/g). The antioxidant activity can be influenced by many factors and cannot be fully described with one single method. These commonly used methods have their advantages and disadvantages for measuring antioxidant activity. Therefore, in this study, the radical scavenging performance was also evaluated by using the ABTS radical cation and hydroxyl radical assays. Regardless of the soluble or insoluble-bound phenolic compounds, M13 (Suheilv 1) genotype showed the highest ABTS radical scavenging ability (Fig. 4 b). The result showed that the ability of soluble phenolic compounds to scavenge hydroxyl radicals ranged from 10.38 to 15.54 μmol/g (Fig. 4 c). However, the insoluble-bound phenolic compounds exhibited significantly lower hydroxyl radical scavenging activity. Free radicals will seize the electrons of biomolecules, causing the biomolecules to be altered and cause various diseases, such as inflammation, aging, and cardiovascular diseases. Phenolic compounds can act as hydrogen or electron donors when reacting with oxidative substances (Luo et al. 2016 ). Therefore, they present strong free radical scavenging activity and antioxidant activity. In general, results indicated that the black seed coat mung bean genotype M13 from our lab presented the strongest antioxidant activity.

Antioxidant activities of different mung bean genotypes (mean ± SD, n  = 3), a DPPH radical scavenging activity; b ABTS radical cation scavenging activity; c hydroxyl radical scavenging ability. Results were expressed as μmol VC/g

Correlation of antioxidant activity with the contents of soluble phenolic compounds and flavonoids

As shown in Table  5 , soluble phenolic content has significantly high correlation with DPPH ( r 2  = 0.713) and ABTS ( r 2  = 0.665) radical scavenging activities. Flavonoid content is significantly correlated with DPPH ( r 2  = 0.463) radical scavenging activity. No evident correlation is observed between hydroxyl radical scavenging ability and phytochemical contents. A high correlation between the content of phenolic compounds and antioxidant activity has also been previously demonstrated by Shi et al. ( 2016 ).

• Principal component analysis

Data of phenolic compounds content, flavonoid content and antioxidant activities of the 24 mung bean genotypes were subjected to principal component analysis (PCA). As shown in Fig.  5 , the first two principal components explained 66.1% of the total variation (R2X [1] =37.9% and R2X [2] =28.2%). The PCA scatter plot revealed the dispersion between the 24 mung bean genotypes. M13 genotype had the largest deviation from the other genotypes, presenting the highest antioxidant activity, phenolic compounds content and flavonoid contents. The longest distance between M13 and M8 showed significant differences in terms of phytochemical contents and antioxidant activities. Principal component analysis indicated that although different mung beans had similar growth environment, they could show significantly differences in phytochemical and antioxidant properties because of their different genotypes. The 24 mung beans were classified into four groups. Group 1 was characterized by high levels of TFC, phenolic contents, DPPH and ABTS free radical scavenging abilities, which contained only M13. Group 2 contained M4, M5, M15, M18 and M22. These genotypes mainly presented similar antioxidant activity. Results of PCA showed satisfactory separation of phenolic compounds and antioxidant activity of these genotypes, indicating that M13 is significantly different from other mung bean genotypes, and implying its potential nutritional and functional values in food processing. Results of this study could provide a good reference for the selection of mung bean genotypes in food production and processing.

Principal component analysis based on the phenolic compounds content, flavonoid content and antioxidant activities of 24 mung bean genotypes

Conclusions

In this study, the nutritional composition, phytochemicals contents and correlations between phytochemical compounds and antioxidant activities of 24 mung bean genotypes from four provinces in China were investigated. The nutritional composition and phytochemical properties of 24 mung bean genotypes are different from each other. Starch, protein, fat, ash and water-soluble polysaccharide ranged from 39.54 to 60.66, 17.36 to 24.89, 4.24 to 12.18, 2.78 to 3.53 and 1.99 to 2.96 g/100 g respectively. M13 (Suheilv 1) showed the highest content of phytochemicals contents, such as flavonoids (3.52 mg RE g − 1 ), soluble phenolic compounds (4.10 mg GAE g − 1 ), and insoluble-bound phenolic compounds (1.50 mg GAE g − 1 ). Vitexin and isovitexin were identified by HPLC as the major phenolic compounds in all mung bean genotypes. M13 showed the highest vitexin (910.26 μg g − 1 ) and isovitexin (1572.74 μg g − 1 ) contents in the soluble fractions of all studied mung beans. Different assays were performed to judge the antioxidant activity of mung bean genotypes, and M13 exhibited strong DPPH and ABTS radical scavenging activities. According to principal component analysis, 24 mung bean samples were classified into four groups based on their phenolic compounds contents and antioxidant activity. The black seed coat mung bean genotype M13 could be used as a superior variety with high antioxidant capacity for functional food production and processing. Overall, this work provides useful information for the potential future application of different mung bean genotypes as source of functional and healthy food. More intensive studies are needed to identify the most effective chemical components in these investigated genotypes.

Availability of data and materials

The data presented in this study are available on request from the corresponding author.

Abbreviations

Gallic acid equivalents

Rutin equivalents

High-performance liquid chromatography

2, 2-diphenyl-1-picrylhydrazyl

2, 2-azinobis (3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt

Water-soluble polysaccharide

Total flavonoid content

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Acknowledgements

We wish to thank Dr. Wang Jialei from Central Laboratory in Jiangsu Academy of Agricultural Sciences for her help in the HPLC analysis.

This work was financed by earmarked fund for China Agriculture Research System (CARS-08-G15) and Jiangsu Agricultural Science and Technology Innovation Fund (CX (20) 2015).

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Fuhao Wang and Lu Huang contributed equally to this work.

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Institute of Industrial Crops, Jiangsu Academy of Agricultural Sciences, Nanjing, Jiangsu, China

Fuhao Wang, Lu Huang, Xingxing Yuan, Xiaoyan Zhang, Chenchen Xue & Xin Chen

College of Food Science and Engineering, Nanjing University of Finance and Economics, Nanjing, Jiangsu, China

Fuhao Wang & Xin Chen

School of Food and Biological Engineering, Jiangsu University, Zhenjiang, Jiangsu, China

Luping Guo & Xin Chen

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Wang F. and Huang L. conducted the experiments, analyzed the data and drafted the manuscript. Yuan X. and Zhang X. helped to process the data. Guo L. took care of the production of the samples. Chen X. and Xue C. supervised the project, conceived the project idea and reviewed the manuscript. All authors have read and approved the final manuscript.

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Wang, F., Huang, L., Yuan, X. et al. Nutritional, phytochemical and antioxidant properties of 24 mung bean ( Vigna radiate L.) genotypes. Food Prod Process and Nutr 3 , 28 (2021). https://doi.org/10.1186/s43014-021-00073-x

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DOI : https://doi.org/10.1186/s43014-021-00073-x

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REVIEW article

Biotic and abiotic constraints in mungbean production—progress in genetic improvement.

• 1 World Vegetable Center, South Asia, Hyderabad, India
• 2 Myanmar Department of Agricultural Research, Nay Pyi Taw, Myanmar
• 3 Pulses Research Centre, Bangladesh Agricultural Research Institute (BARI), Gazipur, Bangladesh
• 4 Crop Improvement Division, ICAR-Indian Institute of Pulses Research (IIPR), Kanpur, India
• 5 Pakistan Agricultural Research Council, Islamabad, Pakistan
• 6 Kenya Agricultural and Livestock Research Organization (KALRO), Katumani, Kenya
• 7 National Agricultural Research Organization-National Semi-Arid Resources Research Institute (NARO-NaSARRI), Soroti, Uganda
• 8 Agri-Science Queensland, Department of Agriculture and Fisheries, Hermitage Research Facility, Warwick, QLD, Australia
• 9 National Institute of Abiotic Stress Management, Baramati, India
• 10 World Vegetable Center, Tainan, Taiwan

Mungbean [ Vigna radiata (L.) R. Wilczek var. radiata ] is an important food and cash legume crop in Asia. Development of short duration varieties has paved the way for the expansion of mungbean into other regions such as Sub-Saharan Africa and South America. Mungbean productivity is constrained by biotic and abiotic factors. Bruchids, whitefly, thrips, stem fly, aphids, and pod borers are the major insect-pests. The major diseases of mungbean are yellow mosaic, anthracnose, powdery mildew, Cercospora leaf spot, halo blight, bacterial leaf spot, and tan spot. Key abiotic stresses affecting mungbean production are drought, waterlogging, salinity, and heat stress. Mungbean breeding has been critical in developing varieties with resistance to biotic and abiotic factors, but there are many constraints still to address that include the precise and accurate identification of resistance source(s) for some of the traits and the traits conferred by multi genes. Latest technologies in phenotyping, genomics, proteomics, and metabolomics could be of great help to understand insect/pathogen-plant, plant-environment interactions and the key components responsible for resistance to biotic and abiotic stresses. This review discusses current biotic and abiotic constraints in mungbean production and the challenges in genetic improvement.

Introduction

Mungbean [ Vigna radiata (L.) R. Wilczek var. radiata ] is a short-duration grain legume cultivated over 7 million hectares, predominantly across Asia and rapidly spreading to other parts of the world. Mungbean seeds are rich in proteins (∼24% easily digestible protein), fiber, antioxidants, and phytonutrients ( Itoh et al., 2006 ). Mungbean is consumed as whole seed or split cooking, flour, or as sprouts, thus, forms an important source of dietary protein. Mungbean sprouts contain high amounts of thiamine, niacin, and ascorbic acid. Yield potential of mungbean is in the range of 2.5–3.0 t/ha, however, the average productivity of mungbean is staggering low at 0.5 t/ha. The low productivity is due to abiotic and biotic constraints, poor crop management practices and non-availability of quality seeds of improved varieties to farmers ( Chauhan et al., 2010 ; Pratap et al., 2019a ). The major biotic factors include diseases such as yellow mosaic, anthracnose, powdery mildew, Cercospora leaf spot (CLS), dry root rot, halo blight, and tan spot, and insect-pests especially bruchids, whitefly, thrips, aphids, and pod borers ( Lal, 1987 ; Singh et al., 2000 ; War et al., 2017 ; Pandey et al., 2018 ). Abiotic stresses affecting mungbean production include waterlogging, salinity, heat, and drought stress ( HanumanthaRao et al., 2016 ; Singh and Singh, 2011 ). Genetic diversity in cultivated mungbean is limited due to breeding efforts that were restricted to relatively few parental lines and hence the need to broaden the narrow genetic base of cultivated mungbeans. Development of short-duration varieties has paved the way for expansion of mungbean into different cropping systems (rice–rice, rice–wheat and rice-maize intercropping) and for cultivation in other regions of the world including Sub-Saharan Africa and South America ( Shanmugasundaram, 2007 ; Moghadam et al., 2011 ). In order to improve productivity and stabilize crop production, there is a need to develop varieties resistant to biotic and abiotic stress factors. Breeding information on the biotic and abiotic stresses in mungbean and on the influence of environmental stresses at different plant development stages is essential to identify the sources for tolerance traits expressed at the right stage. With advanced technologies viz ., phenotyping, genomics, proteomics and metabolomics, the genetic basis of plant interactions with pest, pathogen, and environment can be dissected to design effective crop improvement strategies. In this context, we discuss the biotic and abiotic constraints in mungbean, and the breeding efforts to improve this short duration crop.

Biotic Stress in Mungbean

Major diseases and economic impacts.

Viral, bacterial, and fungal diseases are of economic importance in South Asia, South East Asia, and Sub-Saharan Africa ( Taylor et al., 1996 ; Singh et al., 2000 ; Raguchander et al., 2005 ; Mbeyagala et al., 2017 ; Pandey et al., 2018 ). Mungbean yellow mosaic disease (MYMD) is an important viral disease of mungbean ( Singh et al., 2000 ; Noble et al., 2019 ). MYMD is caused by several begomoviruses, which are transmitted by whitefly Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae) ( Nair et al., 2017 ). The major fungal diseases are Cercospora leaf spot (CLS) [ Cercospora canescens Ellis & G. Martin], powdery mildew ( Podosphaera fusca (Fr.) U. Braun & Shishkoff, Erysiphe polygoni (Vaňha) Weltzien) and anthracnose ( Colletotrichum acutatum (J.H. Simmonds), C. truncatum (Schwein.) Andrus & Moore, C. gloeosporioides (Penz.) Penz. & Sacc). Dry root rot [ Macrophomina phaseolina (Tassi) Goid] is an emerging disease of mungbean. The less important ones are web blight ( Rhizoctonia solani Kuhn), Fusarium wilt ( Fusarium solani (Mart.) Sacc) and Alternaria leaf spot ( Alternaria alternata (Fr.) Keissl) ( Ryley and Tatnell, 2011 ; Pandey et al., 2018 ). Halo blight ( Pseudomonas syringae pv. phaseolicola ), bacterial leaf spot ( Xanthomonas campestris pv. phaseoli ), and tan spot ( Curtobacterium flaccumfaciens pv. flaccumfaciens ) are the important bacterial diseases. The economic losses due to MYMD account for up to 85% yield reduction in India ( Karthikeyan et al., 2014 ). Dry root rot caused 10–44% yield losses in mungbean production in India and Pakistan ( Kaushik and Chand, 1987 ; Bashir and Malik, 1988 ). Reports of yield losses of 33–44% due to Rhizoctonia root rot ( Singh et al., 2013a ) and 30–70% due to anthracnose ( Kulkarni, 2009 ; Shukla et al., 2014 ) from India were estimated. Yield losses due to CLS were 97% in Pakistan and different states of India ( Iqbal et al., 1995 ; Chand et al., 2012 ; Bhat et al., 2014 ), and 40% due to powdery mildew ( Khajudparn et al., 2007 ). Among the minor fungal diseases, 20% yield loss was reported due to Fusarium wilt ( Anderson, 1985 ) and 10% due to Alternaria leaf spot ( Maheshwari and Krishna, 2013 ). A survey of mungbean fields throughout China between 2009–2014 reported average yield reductions of 30–50% and total crop failure in severely infected fields due to halo blight ( Sun et al., 2017 ). Halo blight is an emerging disease in China ( Sun et al., 2017 ) and Australia ( Noble et al., 2019 ). In Iran, 70% incidence ( Osdaghi, 2014 ) and in India 30% incidence ( Kumar and Doshi, 2016 ) of bacterial leaf spot ( X. phaseoli ) has been reported. Studies were carried out to investigate the efficacy of bactericides, fungicides, bio-fungicides and botanicals in seed treatment and foliar spray and impact of cultural practices to reduce mungbean diseases ( Pandey et al., 2018 ). Deployment of varieties with genetic resistance is the most effective and durable method for integrated disease management.

Breeding for Resistance to Viral Diseases

Research into resistance to MYMD has been underway since 1980, with mutant genotypes developed from local germplasm by mutation breeding (gamma irradiation) at the National Institute for Agriculture and Biology, Pakistan, which later led to the development of the popular NM series varieties including NM 92 and NM 94 ( Ali et al., 1997 ). Researchers reported that in mungbean, the genetic resistance against MYMD is governed by a single recessive gene ( Reddy, 2009a ), a dominant gene ( Sandhu et al., 1985 ), two recessive genes and complementary recessive genes ( Pal et al., 1991 ; Ammavasai et al., 2004 ). The mungbean variety NM 92 showed a resistant reaction against MYMD due to a single recessive gene ( Khattak et al., 2000 ). Dhole and Reddy (2012) reported that two recessive genes governed the segregation ratio in the F 2 population in six crosses between resistant and susceptible genotypes. However, F 2 and F 3 populations developed through an inter-specific [TNAU RED × VRM (Gg) 1] and intra-specific [KMG 189 × VBN (Gg)] crosses showed role of a single recessive gene in MYMD resistance ( Sudha et al., 2013 ). Saleem et al. (1998) in their study with F 2 populations derived from crosses between two local lines (NM-92 and NM-93-resistant to MYMD) and four exotic lines (VC-1973A, VC-2254A, VC-2771A and VC-3726A-susceptible to MYMD), found that susceptibility and resistance were controlled by a single genetic factor and that susceptibility was dominant over resistance. Similar results were recorded by Jain et al. (2013) in F 2 and F 3 populations of crosses between five susceptible (LGG 478, KM6 202, PUSA 9871, K 851, and KM6 204) and 4 resistant (KM6201, Sonamung, Samrat, and KM6 220) lines, and it was reported that the inheritance was governed by single dominant gene. However, two recessive genes were found to be responsible for MYMD resistance in the populations developed from crosses between two resistant (Satya and ML 818) and two susceptible (Kopergoan and SML 32) cultivars ( Singh et al., 2013b ). However, in the study of Mahalingam et al. (2018) two dominant genes governed MYMD resistance in the crosses between resistant (SML 1815, MH 421) and susceptible [VBN (Gg) 3, VBN (Gg) 2, LGG 460, RMG 10-28, and TM 96-2] genotypes. The major genes controlling MYMD resistance in the two crosses (KPSI × BM 6 and BM1 × BM 6) using six (P 1 , P 2 , F 1 , F 2 , BC 1 , and BC 2 ) generations were estimated within 1.63–1.75 loci ( Alam et al., 2014 )

It is important to identify the strain/species of the virus causing the disease to make comparison between the different studies done. In repeated samplings over consecutive years in India, Nair et al. (2017) reported genetic similarity of MYMV strains from mungbean to a strain from Urdbean [ Vigna mungo (L.) Hepper] (MYMV-Urdbean) dominant in North India, strains most similar to MYMV- Vigna predominant in South India, and Mungbean yellow mosaic India virus (MYMIV) strains predominant in Eastern India. The resistance sources of mungbean genotypes to MYMD ( Table 1 ) can be used as potential donors and to develop mapping populations for the development of potential markers for MYMD. For the development of resistant lines, researchers have deployed plant-breeding methods with traditional methods of disease screening. In this regard, marker-assisted selection (MAS) is the most promising technique for disease resistant cultivar development. The study of genotypic diversity and the discovery of linked markers for R gene and quantitative trait loci (QTL) maps construction through molecular markers has improved the adeptness in the breeding programs conferring resistance for MYMD ( Sudha et al., 2013 ). Basak et al. (2004) developed a yellow mosaic virus resistance linked marker named ‘VMYR1’ in mungbean. Among the parents, one pair, resistance gene analog (RGA) 1F-CG/RGA 1R (445bp DNA) of gene was found to be polymorphic out of 24 pairs of RGA primers screened. In F 2 and F 3 families, the polymorphisms were found to be linked with YMV-reaction. Binyamin et al. (2015) used sequence characterized amplified region-based markers linked with the MYMD-resistance gene for the screening of mungbean genotypes against the disease. In the resistant and tolerant genotypes, marker amplified desired bands were reported, while no amplification was observed in susceptible genotypes. Maiti et al. (2011) identified two MYMD-resistance marker loci, CYR1 and YR4 completely linked with MYMD-resistant germplasms and co-segregating with MYMD-resistant F 2 and F 3 progenies. Holeyachi and Savithramma (2013) identified random amplified polymorphic DNA (RAPD) markers linked with MYMD recombinant breeding lines. They reported that out of 20 random decamers, only 10 primers showed polymorphism between parents China mung (S) and BL 849 (R) and among them, only one primer (UBC 499) amplified a single 700 bp band in the resistant parent (BL 849) that was absent in susceptible genotype (China mung). Kalaria et al. (2014) studied the polymorphism by using 200 RAPD and 17 inter simple sequence repeat (ISSR) markers. Among RAPD markers, OPJ-18, OPG-5, and OPM-20 and in ISSR DE-16 were found to be potential ones, as they produced 28, 35, 28, and 61 amplicons, respectively. The resistant genotypes NAUMR1, NAUMR2, NAUMR3, and Meha were clearly separated from the susceptible cultivar, GM4. In another study, 5 QTLs based on simple sequence repeats (SSR) markers were investigated against MYMD, of them, three were from India ( qYMIV1, qYMIV2 , and qYMIV3 ) and 2 were from Pakistan ( qYMIV4 and qYMIV5 ) ( Kitsanachandee et al., 2013 ). The QTL, qYMIV1 explained 9.33% variation in disease response. Similarly, qYMIV2 explained 10.61%, qYMIV3 explained 12.55%, qYMIV4 explained 21.55% and qYMIV5 explained 6.24% variations in the disease response. Two major QTLs controlling genes on linkage group 2 ( qMYMIV2 ) and 7 ( qMYMIV7 ) resistant to MYMD were reported. These QTLs were conferring resistance in both F 2 and BC 1 F 1 populations with a coefficient of determination (R 2 ) of 31.42–37.60 and 29.07–47.36%, respectively ( Alam et al., 2014 ). Markers linked to QTLs in this study will be useful in marker-assisted breeding for the development of MYMD resistant mungbean varieties. During the growing season plant breeders can conduct repeated genotyping in the absence of disease incidence by applying linked marker-assisted genotyping. This technique will save labor and time during the introgression of MYMD-resistance through molecular breeding, as phenotyping against begomoviruses is complex, labor and time consuming. New donors of MYMD resistance have also been identified from interspecific sources ( Chen et al., 2012 ; Nair et al., 2017 ).

Table 1 Resistant sources of mungbean against mungbean yellow mosaic disease.

Breeding for Resistance to Fungal Diseases

Researchers screened mungbean genotypes against fungal diseases from different countries in controlled and field conditions in order to identify sources of resistance. Resistant genotypes reported by investigators against various fungal diseases are presented in Table 2 . It may be noted that screening of mungbean genotypes against powdery mildew and Cercospora leaf spot diseases has been much explored. However, little work has been done on the identification of sources of resistance against anthracnose and dry root rot and needs to be addressed as future priorities. Screening of mungbean genotypes against fungal diseases provided in Table 2 were carried out under natural conditions, except for dry root rot, Khan and Shuaib (2007) screened in laboratory conditions.

Table 2 Resistant genotypes of mungbean against fungal diseases.

Efficient breeding for fungal stresses requires readily available resistant germplasm and markers linked with QTL regions or major genes that can be employed in marker-assisted selection (MAS). In mungbean, for Cercospora leaf spot and powdery mildew molecular markers have been identified for application in breeding programs. However, QTLs or molecular markers for dry root rot and anthracnose have not been investigated. Both qualitative and quantitative modes of inheritance have been reported for resistance to powdery mildew Kasettranan et al. (2009) . Single dominant gene control of resistance to powdery mildew was reported ( AVRDC, 1979 ; Khajudparn et al., 2007 ; Reddy, 2009b ), while Reddy et al. (1994) reported that two major dominant genes control the resistance. Chaitieng et al. (2002) and Humphry et al. (2003) found that one QTL conferred the resistance to powdery mildew, while Young et al. (1993) reported three QTLs linked with powdery mildew resistance. Young et al. (1993) made the conclusion from studying the mapping population developed from mungbean line VC3890 as a resistance parent. The population developed from a cross between KPS 2 (moderately resistant) and VC 6468-11-1A (resistant) mungbean genotypes was investigated by Sorajjapinun et al. (2005) and they reported additive gene action control of resistance. Kasettranan et al. (2010) identified SSR markers based QTLs such as qPMR-1 and qPMR-2 associated with resistance to powdery mildew. One major QTL on the linkage group 9 and two minor QTLs on linkage group 4 were identified in mungbean line V4718 ( Chankaew et al., 2013 ). The mapping population against powdery mildew developed from mungbean line RUM5 resulted in two major QTLs on LG6 and LG9 and one minor QTL on LG4 ( Chankaew et al., 2013 ). Fine mapping with populations developed from crosses between highly susceptible and highly resistant parents would be reliable for the identification of reliable markers.

Lee (1980) reported that a single dominant gene governs the resistance to CLS. Reports on quantitative genetic control of resistance to CLS ( Chankaew et al., 2011 ) and a single recessive gene control ( Mishra et al., 1988 ) have been reported. One major QTL ( qCLS ) for CLS located on linkage group 3, which explained 66-81% phenotypic variation was reported ( Chankaew et al., 2011 ) using F 2 (CLS susceptible cultivar Kamphaeng Saen1, KPS1 × CLS-resistance mungbean line, V4718) and BC 1 F 1 [(KPS1 × V4718) × KPS1] populations.

Breeding for Resistance to Bacterial Diseases

Bacterial pathogens are seed-borne and can persist in crop residue. Varietal resistance is recognized as the cornerstone of integrated disease management ( Noble et al., 2019 ). Little work has been done on the screening of mungbean genotypes against bacterial diseases and identifying genetic markers associated with bacterial diseases in mungbean. From India, Patel and Jindal (1972) evaluated 2160 genotypes of mungbean for resistance to bacterial leaf spot ( X. phaseoli ) and reported that Jalgaon 781, P 646, P 475, and PLM 501 mungbean genotypes were resistant. From Pakistan, 8 out of 100 mungbean genotypes, were reported as resistant against bacterial leaf spot disease under field conditions ( Iqbal et al., 1991 ; Iqbal et al., 2003 ). Munawar et al. (2011) screened 51 genotypes against bacterial leaf spot disease in Pakistan, and found NCM11-8, NCM 15-11, AZRI-1, and 14063 mungbean genotypes as resistant in natural incidence of the disease. In their field evaluation, few genotypes such as NCM 258-10, NCM-21, NCM 11-6, AZRI-06, and NCM 11-3 showed moderate resistance reaction.

The inheritance of bacterial leaf blight is governed by a single dominant gene ( Thakur et al., 1977 ). Patel and Jindal (1972) reported that in mungbean genotypes Jalgaon 781, P 646, P 475, and PLM 501, the inheritance of resistance to bacterial leaf blight (BLB) was monogenic dominant. While QTLs were identified for bacterial leaf blight disease in other crops like chickpea ( Dinesh et al., 2016 ), no records are available on QTLs of mungbean against bacterial disease. Screening for halo blight and tan spot has been carried out by the Australian breeding program in both controlled (glasshouse) and field conditions to identify useful donors as well as resistant progenies ( Noble et al., 2019 ). Identification of genetic markers/QTLs associated with halo blight, tan spot, and bacterial leaf spot disease resistance in mungbean will accelerate the development of resistant commercial cultivars. These markers can be established through genome-wide association studies using large, diverse mungbean mapping populations’ representative of worldwide germplasm ( Schafleitner et al., 2015 ; Noble et al., 2019 ).

Major Insect-Pests and Economic Impacts

Insect-pests attack mungbean at all crop stages from sowing to storage and take a heavy toll on crop yield. Some insect-pests directly damage the crop, while others act as vectors of diseases. The economically important insect-pests in mungbean include stem fly, thrips, aphids, whitefly, pod borer complex, pod bugs, and bruchids ( Swaminathan et al., 2012 ). Stem fly (bean fly), Ophiomyia phaseoli (Tryon), is one of the major pests of mungbean. Other species of stem fly that infest mungbean include Melanagromyzasojae (Zehntner) and Ophiomyia centrosematis (de Meijere) ( Talekar, 1990 ). This pest infests the crop within a week after germination and under epidemic conditions, it can cause total crop loss ( Chiang and Talekar, 1980 ). Whitefly, B. tabaci is a serious pest in mungbean and damages the crop either directly by feeding on phloem sap and excreting honeydew on the plant that forms black sooty mould or indirectly by transmitting MYMD. Whitefly’s latent period is less than four hours and a single viruliferous adult can transmit the MYMV within 24 h of acquisition and inoculation. The male and female whiteflies can retain the infectivity of the virus for 10 and 3 days, respectively. Further, B. tabaci complex consists of 34 cryptic species ( Boykin and De Barro, 2014 ). Whitefly causes yield losses between 17 and 71% in mungbean ( Marimuthu et al., 1981 ; Chhabra and Kooner, 1998 ; Mansoor-Ul-Hassan et al., 1998 ). Thrips infest mungbean both in the seedling and in flowering stages. The seedling thrips are Thrips palmi Karny and Thrips tabaci Lindeman and the flowering thrips are Caliothrips indicus Bagnall or Megalurothrips spp. During the seedling stage, thrips infest the seedling’s growing point when it emerges from the ground, and under severe infestation, the seedlings fail to grow. Flowering thrips cause heavy damage and attack during flowering and pod formation. They feed on the pedicles and stigma of flowers. Under severe infestation, flowers drop and no pod formation takes place. Spotted pod borer, Maruca vitrata (Fab.) is a major insect-pest of mungbean in the tropics and subtropics. With an extensive host range and distribution, it is widely distributed in Asia, Africa, the Americas and Australia ( Zahid et al., 2008 ). The pest causes a yield loss of 2–84% in mungbean amounting the US $30 million ( Zahid et al., 2008 ). The larvae damage all the stages of the crop including flowers, stems, peduncles, and pods; however, heavy damage occurs at the flowering stage where the larvae form webs combining flowers and leaves ( Sharma et al., 1999 ). Cowpea aphid, Aphis craccivora Koch., sucks plant sap that causes loss of plant vigour and may lead to yellowing, stunting or distortion of plant parts. Further, aphids secrete honeydew (unused sap) that leads to the development of sooty mould on plant parts. Cowpea aphid also acts as a vector of bean common mosaic virus. Bruchids are the most important stored pests of legume seeds worldwide. They infest seeds both in field and in the storage, however, major damage is caused in storage. Bruchid damage can cause up to 100% losses within 3–6 months, if not controlled ( Tomooka et al., 1992 ; Somta et al., 2007 ). Twenty species of bruchids have been reported infesting different pulse crops ( Southgate, 1979 ). Of these, the Azuki bean weevil ( Callosobruchus chinensis L.) and cowpea weevil ( Callosobruchus maculatus Fab.) are the most serious pests of mungbean. The cryptic behaviour of bruchids where the grubs feed inside the legume seeds makes it easy to spread them through international trade.

Breeding for Insect Resistance

Identification of sources of resistance is important for the introgression of resistance into cultivars through breeding. The primary gene pool forms the first choice for the breeder for source of resistance. The secondary and tertiary gene pools provide further choices of variation to be incorporated into the crop. Although a number of screening methods have been developed, lack of uniform insect infestation across seasons and locations in some key pests, whose rearing and multiplication is difficult on artificial diets, is highly challenging for screening plants against insect-pests. For pod borers, screening in field, and greenhouse conditions is generally done by releasing ten first-instar larvae on the plant placed in net wire framed cage (40 cm in diameter, 45 cm long) under no-choice and free choice conditions ( Sharma et al., 2005 ). Under laboratory conditions, the easiest and the most reliable technique used for screening plants for pod borer and foliage feeding insects is detached leaf bioassay techniques ( Sharma et al., 2005 ). This technique is very useful to screen the germplasm where antibiosis and non-preference are important components of plant resistance. Under field conditions, screening is also done by augmenting insect populations, planting date adjustment, tagging the inflorescences and plant grouping according to maturity and height ( Sharma et al., 2005 ). For screening against Maruca , plant phenology is an important criterion to be taken into consideration ( Dabrowski et al., 1983 ; Sharma et al., 1999 ). Plants are screened for resistance on the basis of the number of shoots prior to flowering and the number of eggs per plant during the early stages of the crop ( Oghiakhe et al., 1992 ). Whitefly, thrips, and cowpea aphid resistance screening in mungbean is done on the basis of the number of insects and scoring the plants for insect damage on a visual rating scale ( Taggar and Gill, 2012 ). Screening for bruchid resistance is done by using small plastic cups with 10–50 seeds in a no-choice or free-choice conditions and releasing up to five pairs of newly emerging adults ( Somta et al., 2007 , Somta et al., 2008 ).

To breed for resistance to insect-pests, understanding plant-insect interactions is very important. Some of the important parameters for successful breeding for insect resistance is to understand the biology of the insect pest, infesting stage and the biochemical and molecular aspect of insect-plant interactions. The role of various agro-ecological and environmental conditions along with uniform insect infestation is very important as the evaluation techniques, insect population and plant ecology depend on these factors. Further, it is important to have an optimum population build-up of the insect-pests during the most vulnerable stage of the crop. Uniform infestation at appropriate stages of plant development plays an important role in identifying insect-resistant genotypes and to reduce or eliminate the escapes ( Maxwell and Jennings, 1980 ). Basic strategies in breeding for insect resistance are to identify the resistance coding genes from wild/cultivated species and introgress them into improved lines through recombination, hybridization, and selection. Though conventional plant breeding has some limitations it has contributed to significant improvement in yield and disease and insect resistance in mungbean ( Fernandez and Shanmugasundaram, 1988 ). Induced mutation by using physical and chemical mutagens have been implicated in the development of insect and disease resistant varieties along with the other target traits in mungbean ( Lamseejan et al., 1987 ; Wongpiyasatid et al., 2000 ; Watanasit et al., 2001 ). Some of the techniques in conventional breeding to develop insect resistant cultivars include mass selection, pure line selection and recurrent selection ( Dhillon and Wehner, 1991 ; Burton and Widstorm, 2001 ). Techniques such as backcross breeding, pedigree breeding and bulk selection are being used for developing insect resistance in mungbean along with improved agronomic traits.

Sources of Resistance Against Insect-Pests

Host plant resistance plays an important role in crop protection against insect pests. The identification of new insect resistance sources provides breeders with avenues to breed for resistance to insect pests. The variability primary gene-pool available with the breeders could serve an important source for various traits including insect resistance. Generally, many valuable genes that confer resistance to insect pests can be found in the wild species and/or non-domesticated crop relatives ( Sharma et al., 2005 ). Extensive screening studies have been carried out under controlled and natural conditions to identify insect resistance sources in mungbean ( Table 3 ). For stem fly, very few studies have been carried out for the identification of resistant sources in mungbean. World Vegetable Center and The International Center for Tropical Agriculture (CIAT) identified some stem fly resistant genotypes, which have been used as potential sources in breeding for resistance against stem fly ( Talekar, 1990 ; Abate et al., 1995 ). CIAT identified G 05253, G 05776, G 02005, and G 02472 as highly resistant to stem fly. Co 3 has been reported as resistant to Ophiomyia centrosematis (De Meijere) ( Devasthali and Joshi, 1994 ). Some of the whitefly resistant sources have been identified globally and used to breed for resistance to this pest. Abdullah-Al-Rahad et al. (2018) reported Bari Mung -6 as resistant to whitefly and cowpea aphid under natural infestation. Sources of resistance to both seedling and flower thrips have been identified in mungbean under natural and artificial infestation in mungbean ( Table 3 ). Breeding for resistance to spotted pod borer has lead to the identification of some of the sources of resistance in mungbean ( Chhabra et al., 1988 ; Sahoo et al., 1989 ; Gangwar and Ahmed, 1991 ; Sahoo and Hota, 1991 ; Bhople et al., 2017 ). In mungbean, not much work has been done to identify the sources of resistance against cowpea aphid. Just a couple of resistant sources are available ( Bhople et al., 2017 ; Abdullah-Al-Rahad et al., 2018 ).

Table 3 Resistant sources of mungbean against insect pests.

Despite screening a large number of lines against bruchids, only a few resistant sources have been identified till date. These include V2709, V2802, V1128, and V2817 ( Somta et al., 2008 ). The first bruchid resistant source was TC1966, a wild mungbean ( V. radiata var. sublobata (Roxb.) Verdc.), collected in Madagascar and was used as a source of resistance ( Tomooka et al., 1992 ; Watanasit and Pichitporn, 1996 ). TC1966 showed complete resistance to C. maculatus and C. chinensis and the resistant reaction was observed to be controlled by a single dominant gene, Br ( Fujii and Miyazaki, 1987 ; Kitamura et al., 1988 ; Fujii et al., 1989 ). However, they found linkage drag that resulted in pod shattering in the cultivars developed using TC 1966 ( Watanasit and Pichitporn, 1996 ). Two mungbean lines, V2709 and V2802 were identified by the World Vegetable Center with complete resistance to bruchids and have been extensively used in breeding programs to develop bruchid resistant mungbean ( Talekar and Lin, 1981 ; AVRDC, 1991 ; Talekar and Lin, 1992 ). V2709 has been used as a source of resistance to develop three bruchid-resistant lines (Zhonglv 3, Zhonglv 4, and Zhonglv 6) in China ( Yao et al., 2015 ) and, one bruchid-resistant variety (Jangan) in Korea ( Hong et al., 2015 ). Somta et al. (2008) identified two mungbean cultivated lines, V1128 and V2817 as resistant to C. maculatus . At the World Vegetable Center, bruchid resistance from two black gram accessions, VM2011 and VM2164 was introgressed into mungbean successfully ( AVRDC, 1987 ). Out of 101 breeding lines screened against bruchids, five lines (VC1535-11-1-B-1-3-B, VC2764-B-7-2-B, VC2764-B-7-1-B, VC1209-3-B-1-2-B, and VC1482-C-12-2-B) were reported as tolerant to bruchids ( AVRDC, 1988 ). Recently, World Vegetable Center has developed promising lines that are resistant to bruchids, thrips and cowpea aphid ( ACIAR, 2018 ; ACIAR, 2019 ).

Among insect-pests, bruchid resistance in mungbean has been extensively studied using the molecular techniques. However, QTL mapping for resistance to field insect-pests that are common in legumes has been studied common bean and cowpea. In common bean, Empoasca spp. ( Murray et al., 2004 ), T. palmi ( Frei et al., 2005 ), Apion godmani Wagner ( Blair et al., 2006 ) and bruchids ( Blair et al., 2010 ), while in cowpea, Megalurothrips sjostedti (Trybon) ( Omo-Ikerodah et al., 2008 ) and A. craccivora ( Huynh et al., 2015 ) have been studied in detail. The stem fly resistance in mungbean has been found to be governed by additive, dominance and epistasis mechanisms ( Distabanjong and Srinives, 1985 ). The wild species of mungbean TC 1966, which is resistant to C. maculatus, C. chinensis, C. analis and C. phaseoli has been widely used by breeders to develop bruchid resistant lines by crossing with agronomically superior cultivars ( Fujii et al., 1989 ; Talekar and Lin, 1992 ; Tomooka et al., 1992 ; Somta et al., 2007 ). Molecular techniques have been utilized to identify bruchid resistant mungbean, locate genes that code for bruchid resistance, clone them genes and develop molecular markers for mapping bruchid resistance ( Tomooka et al., 1992 ; Tomooka et al., 2000 ; Somta et al., 2008 ; Schafleitner et al., 2016 ). The selection efficiency and reduction in tests for screening of breeding material against insect pests including bruchids has been increased by the molecular markers developed ( Schafleitner et al., 2016 ).

Various molecular markers such as restriction fragment length polymorphism (RFLP), RAPD, single nucleotide polymorphism (SNP) and SSR have been used to map bruchid resistance in mungbean ( Young et al., 1992 ; Villareal et al., 1998 ; Chen et al., 2007 ; Chotechung et al., 2011 ), most of them are qualitative and the results are based on phenotypic data. In TC1966, bruchid resistance has been mapped using RFLP ( Young et al., 1992 ). They mapped 14 linkage groups containing 153 RFLP markers of 1,295 centiMorgans (cM) with an average distance of 9.3 cM between the markers. The analysis of 58 F 2 progenies from a cross between TC1966 and a susceptible mungbean cultivar showed that an individual F 2 population possess a bruchid resistance gene within a tightly linked double crossover and was used for the development of bruchid resistant mungbean. A population derived from a cross between the cultivar Berken and ACC41 (a wild mungbean genotype, V. radiata subsp. sublobata ) using RFLP probes were used to develop a linkage map ( Humphry et al., 2002 ). The mungbean bacterial artificial chromosome libraries have been developed by STSbr1 and STSbr2 [polymerase chain reaction-based markers] ( Miyagi et al., 2004 ). The authors reported close linkage in a recombinant inbred line (RIL) population between ACC41 and ‘Berken’. Further, Sarkar et al. (2011) showed that STSbr1 amplified a 225bp fragment in V. sublobata accession (sub2) and 12 other cultivars that were resistant to bruchids. Though RAPD markers are fast and simple, the distance between them is high from the bruchids resistant gene. RAPD markers for bruchid resistance have also been used with a mapping population from RIL and near-isogenic line (NIL; B4P 5-3-10, B4P3-3-23, DHK 2-18, and B4Gr3-1 with bruchid resistant genes from Pagasa 5, Pagasa 3, VC 1973A and Taiwan Green, respectively by using TC 1966 as a resistance source ( Villareal et al., 1998 ). NILs were differentiated by using 31 RAPD markers from which 25 showed co-segregation in the RIL population. A RIL population obtained from crossing ‘Berken’ (bruchid-susceptible line) with ACC41 (bruchid-resistant line) was used to map the Br1 locus ( Wang et al., 2016 ). Ten RAPD markers were identified by Chen et al. (2007) for bruchid resistance in 200 RILs from a cross between TC1966 and NM 92. These included UBC66, UBC168, UBC223, UBC313, UBC353, OPM04, OPU11, OPV02, OPW02, and OPW13. Out of these, four markers (OPW02, UBC223, OPU11, and OPV02) were closely linked. For bruchid resistance in mungbean, a few SSR markers have been reported. These include SSRbr1, DMB-SSR158, and GBssr-MB87 ( Miyagi et al., 2004 ; Chotechung et al., 2011 ; Chen et al., 2013 ; Hong et al., 2015 ). In V2802 and TC 1966, chromosome 5 possess the DMB-SSR 158 marker associated with Vradi05g03940-VrPGIP1 and Vradi05g03950-VrPGIP2 genes, which code for polygalacturonase inhibitor involved in bruchid resistance ( Chen et al., 2013 ; Chotechung et al., 2016 ). The major QTL in TC1966 and DMB-SSr 158 marker are <0.1cM away from the bruchid resistant gene ( Chen et al., 2013 ). Also, QTL qBr has been reported between markers VrBr-SSR013 and DMB-SSR158 at the same position.

The sequence-changed protein genes (SCPs) and differentially expressed genes (DEGs) retain the transcript diversity and specificity of the Br genes ( Liu et al., 2016 ) and the variations in DEGs promoter and of SCPs can be potential markers in breeding for resistance against bruchids. Two QTLs, MB87 and SOPU11 have been reported to be associated with bruchid resistant genes in the study from a population developed from crossing Sunhwa (susceptible) and Jangan (resistant variety developed from back crossing with V2709) ( Hong et al., 2015 ). Mei et al. (2009) reported a QTL in wild mungbean ACC41 that accounts for about 98.5% of bruchid resistance.

Recently, SNP markers have gained high momentum for use in breeding for pest and disease resistant plants. Their abundant, ubiquitous nature in the genome and readily availability for genotyping makes them very useful ( Brumfield et al., 2003 ). Further, being co-dominant, single-locus, and biallelic markers, the SNPs are unique for use in breeding programs. Owing to the small genome size of mungbean (515 Mb/1C), the full genome sequencing or a reduced representation library sequencing are possible that would lead to the generation of many SNP markers ( Moe et al., 2011 ). Further, SNPs have been extensively studied in breeding for resistance in mungbean against stink bug, Riptortus clavatus and adzuki bean weevil, C. chinensis ( Moe et al., 2011 ; Schafleitner et al., 2016 ). Schafleitner et al. (2016) identified dCAPS2, dCAPS3, CAPS1, and CAPS12 SNP markers for bruchid resistance in mungbean. Despite being physically mapped to different chromosomes, these markers showed genetic linkage by co-segregation at the proportions of 96.5% in the F 3 families of the crosses TC 1966 X NM 92 and V2802 X NM 94. They reported that in both crosses, the QTL for the bruchid resistance was mapped to chromosome 5 and the markers showed the prediction of 100%. Kaewwongwal et al. (2017) reported that VrPGIP1 and VrPGIP2 , which are tightly linked genes confer bruchid resistance in V2709. They identified two alleles for VrPGIP1 and VrPGIP2 in V2709 as VrPGIP1-1 and VrPGIP2-2 , respectively.

The next generation sequencing (NGS) technologies are being utilized to develop SNPs used for genotyping several traits and increase the amounts of transcripts much higher than the cloning and Sanger sequencing approaches in plants and animals. The genetic complexities of various traits including resistance to biotic and abiotic stresses are being studied using genotyping by sequencing (GBS) methods. Some of the areas in which GBS has been utilized include purity testing, genetic mapping, MAS, marker-trait associations, and genomic selection ( Schafleitner et al., 2016 ). Schafleitner et al. (2016) used GBS technology on populations derived from TC1966 (wild mungbean accession-bruchid resistant) and V2802 (a cultivated mungbean accession) with bruchid susceptible lines, NM 92 and NM 94. A total of 32,856 SNPs were obtained, out of which 9,282 SNPs were scored in RIL populations. Finally, 7,460 SNP sequences were aligned to 11 chromosomes and 1,822 were aligned to scaffold sequences. It has been reported that SuperSAGE in combination with the NGS has been applied to study the biotic and abiotic stress resistance/tolerance in some legumes ( Rodrigues et al., 2012 ; Almeida et al., 2014 ), however, such combinations have not been studied in detail for insect resistance. RNAseq technique is very important to study the pest and disease resistance in plants in a given situation. In RNAseq, sequencing of all the transcripts that are expressed in response to pest pressure is developed and is highly powerful as the transcriptomes are synthesised de novo and can also be used to compare the expression of genes in different insect pressures. Additionally, RNAseq can be used to study the simultaneous expression of genes both in plant and in the pest in a given situation ( Liu et al., 2012 ). Genome-wide transcriptome profiling techniques provide the expression of a huge number of genes in response to insect damage, however, it is challenging to identify which of them are involved in resistant plant phenotypes. The studies on the co-localization of these genes with QTLs and functional genomics has been quite helpful, however, it will be critical to study the generation and application of high-throughput reverse genetic platforms. Though functional genomics is applied to understand the genetic basis of resistance and is implicated in breeding for resistance against insect-pests, further in-depth investigations are needed to stabilize the insect resistance in mungbean. Furthermore, identification of molecular markers linked to genes/QTLs controlling insect-pest resistance has been studied in many legumes, only in a few cases, these markers have been used in MAS breeding, the main constraint being the large distance between the markers and the gene/QTL controlling resistance ( Shi et al., 2009 ; Schafleitner et al., 2016 ).

Abiotic Stresses in Mungbean

Abiotic stresses negatively influence plant growth and productivity and are the primary cause of extensive agricultural losses worldwide ( Arun and Venkateswarlu, 2011 ; Ye et al., 2017 ). Reduction in crop yield due to environment variations has increased steadily over the decades ( Boyer et al., 2013 ). Abiotic stresses include extreme events and factors related to atmosphere (heat, cold, and frost); water (drought and flooding); radiation (UV and ionizing radiation); soil (salinity, mineral or nutrient deficiency, heavy metal pollutants, pesticide residue, etc.) and mechanical factors (wind, soil compaction) ( HanumanthaRao et al., 2016 ). Crops utilize resources (light, water, carbon and mineral nutrients) from their immediate environment for their growth. The microenvironment and the management practice of cultivation influence crop growth and development directly ( Figure 1 ). Climate change further adds to the complexity of plant-environment interactions ( Goyary, 2009 ). The eco-physiological models that integrate the understanding of crop physiology and crop responses to environmental cues from detailed phenotyping are therefore used to understand the impact of environmental factors on crop growth and development, predict yield/plant response and also assist in developing management strategies ( Figure 2 ) (APSIM: Chauhan et al., 2010 ; MungGro: Biswas et al., 2018 ). The plant response to abiotic stress at the cellular level is often interconnected ( Beck et al., 2007 ) leading to molecular, biochemical, physiological and morphological changes that affect plant growth, development and productivity ( Ahmad and Prasad, 2012 ). Several crop production models project a reduction in the crop yields of major agricultural crops mostly due to climate change ( Rosenzweig et al., 2014 ), which tend to make crop growth environment unfavorable due to abiotic stresses. Such efforts in crops like mungbean is rare and requires a special attention. In the current era, environmental stresses are a menace to global agriculture and there is a need to emphasize trait based breeding to ensure yield stability across the locations as well as crop seasons. Efforts are underway to develop new tools for understanding possible mechanisms related to stress tolerance and identification of stress tolerance traits for promoting sustainable agriculture ( Cramer et al., 2011 ; Fiorani and Schurr, 2013 ). Basic tolerance mechanisms involve the activation of different stress-regulated genes through integrated cellular as well as molecular responses ( Latif et al., 2016 ). Plants respond to their immediate surroundings in diverse ways, which assist the cells to adapt and achieve cellular homeostasis manifested in phenotypes of plants under particular environment ( James et al., 2011 ). While breeding lines are regularly phenotyped for easily visible traits including growth and yield components, many traits that contribute to stress tolerance are ignored. This can be largely due to feasibility of measuring these traits precisely and rapidly. Hence, recent phenotyping tools deploy image capture and automation in advanced plant phenotyping platforms. These recent efforts are expected to boost efforts to translate basic physiology of crop plants into products with practical values to support breeding program in harsh environments (viz., stresses like salinity, soil moisture, extreme temperatures etc) explained in the following section.

Figure 1 Schematic representations of crop growth and development dynamics (Generic template; Connections between the two schematics are shown by the shaded boxes); [ Hammer et al., 2010 : https://doi.org/10.1093/jxb/erq095 ].

Figure 2 Process chart of mungbean growth model (MungGro) [ Biswas et al., 2018 ]

In agriculture, soil salinity has been a threat in some parts of the world for over 3000 years ( Flowers, 2006 ) and it has been aggravated by irrigation water sourced through surface irrigation in arid and semi-arid environments ( HanumanthaRao et al., 2016 ). Salt stress mainly in most of the crops reduces seed germination, fresh and dry biomass, shoot and root length, and yield attributes of mungbean ( Promila and Kumar, 2000 ; Rabie, 2005 ; Ahmed, 2009 ). It affects root growth and elongation, thereby, hampering nutrient uptake and distribution. Root growth was significantly reduced with higher Sodium Chloride (NaCl) (NaCl) concentrations. Nevertheless, BARI Mung4 showed better performances at higher NaCl concentration considering a yield-contributing character. Nodules/plant decreased with the increase of salinity although the nodule size increased ( Naher and Alam, 2010 ). Being polygenic in nature, salinity tolerance is genotype-dependent and growth stage-specific phenomenon, therefore, tolerance at an initial (seedling) stage may not be corroborated with tolerance at later growth (maturity) stages ( Sehrawat et al., 2013 ). It also involves multidimensional responses at several organ levels in plants (e.g., tissue, molecular, physiological and plant canopy levels) ( HanumanthaRao et al., 2016 ). Because of this complexity and lack of appropriate techniques for introgression, little progress has been achieved in developing salt-tolerant mungbean varieties over years ( Ambede et al., 2012 ; HanumanthaRao et al., 2016 ). Appreciable improvement in salt tolerance of important crops (barley, rice, pearl millet, maize, sorghum, alfalfa, and many grass species) have been attained in the past, but not in legumes in general and mungbean in particular ( Ambede et al., 2012 ). Rapid screening methods are required to identify putative donor parents in a breeding program ( Saha et al., 2010 ). In a comprehensive study, Manasa et al. (2017) screened 40 mungbean lines sourced from World Vegetable Center for salinity tolerance using Salinity Induction Response (SIR) technique at the seedling as well as at whole plant levels by canopy phenotyping assay under 150 and 300 mM NaCl stress scenario. The results showed a marked reduction in growth and yield performances of both tolerant and susceptible lines, but a few lines displayed a relatively better biomass and pod yield on par with non-stressed control plants. The intrinsic ability of salt portioning to vacuole (more influx of Na + ions) by tolerant lines during high salt concentration in the cytocol could be one of the reasons for their tolerance. Based on the extent of salt tolerance both at seedling and whole plant stages, a few salt tolerant (EC 693357, 58, 66, 71, and ML1299) lines were identified ( Manasa et al., 2017 ) for further validation under field conditions.

Soil Moisture Stress

The response of legumes to the onset of drought vary and the final harvestable yield will significantly be reduced ( Nadeem et al., 2019 ). Global climate change attributes erratic prediction in drought episodes and its control of crop yields. Being grown on marginal lands, mungbean is largely considered as a drought tolerant (grow with a limited soil moisture). However, like any other plants, it responds to a decrease in available soil moisture by reducing its growth and hence productivity. It is evident from the experiment that 30% decrease in water supply relative to water optimum for crop growth results in nearly 20% decrease in seed weight per plant if the soil moisture stress imposed around a vegetative stage. The plants subjected to stress during flowering showed 50 to 60% decrease in seed yield ( Fathy et al., 2018 ). Soil moisture stress did not affect the number of pods per plant as severely as it did for seed weight or biomass per plant in this experiment, clearly indicating that seed formation or filling is the most sensitive to soil moisture stress. It is also suggested that the dry matter partitioning is one of the potential screening trait for drought tolerance in mungbean ( Hossain et al., 2010 ; Nadeem et al., 2019 ). When the drought stress was severe enough to reduce plant biomass per m 2 from 359 to 138 g, the resultant reduction in pod number was nearly 50% and the same for seed yield was nearly 60% relative to well-watered plants ( Kumar and Sharma, 2009 ).

The decrease in total plant dry weight and harvest index were the main reasons for reduced seed yield due to drought stress in mungbean ( Sadasivan et al., 1988 ; Thomas et al., 2004 ). Significant reduction in pod initiation and pod growth rates were the major responses to soil moisture stress during flowering and pod-filling stages ( Begg, 1980 ). Water stress during flowering results in reduced yield mainly due to flower abscission ( Moradi et al., 2009 ). The relative water content in leaves and partitioning of biomass have been sighted as the traits contributing to tolerance to drought in summer mungbean ( Kumar and Sharma, 2009 ). Yield loss of 31-57% at flowering and 26% at post flowering/podding stages in mungbean due to drought stress was reported by Nadeem et al. (2019) . The drought-induced imbalance in electrons produced and consumed during the photosynthetic process gives rise to harmful superoxide molecules, which have been cited as a major reason for damages at the cellular level. Hence, key factors that can alleviate oxidative stress are the focus of research for alleviating drought stress. Recent studies infer that alleviation of drought-caused oxidative stress depends largely on the status of Ascorbic acid and Glutathione pools in reduced and oxidative stages ( Anjum et al., 2015 ). There is a need to explore genetic variation for these traits and possibility of introgressing the relevant genes for improving drought tolerance in mungbean. Decreased leaf water potential was associated with reduced activity of nitrogenase, glutamine synthetase, asparagine synthetase, aspartate aminotransferase, xanthine dehydrogenase and uricase that are associated with nitrogen fixation (Kaur et al., 1985). New insights into these metabolites and enzymes can be obtained to understand their roles through recently evolved metabolomics.

Water stress-induced inhibition of hypocotyl elongation is more conspicuous in separated cotyledons than the intact ones. It is necessary to check if the larger cotyledons can be the solution for better plant establishment under soil moisture stress. When two mungbean genotypes exhibiting more than two-fold variation in leaf water loss were explored for the genetic variation in their physiological and molecular responses to drought, efficient stomatal regulation was observed in water saving low leaf water loss (LWL) genotype ( Raina et al., 2016 ). The stomatal closure under drought was accompanied with a concomitant down-regulation of farnesyl transferase gene in this genotype. However, other genotypes had a cooler canopy temperature facilitated by a branched root system that allowed better extraction of soil moisture ( Raina et al., 2016 ). These mechanisms and traits of mungbean are suitable for harsh environments but needs a prioritization based on the type of drought and agro-ecological features. The other important key physiological traits viz., water use efficiency, root growth/biomass, carbon isotope discrimination (∆ 13 C) and leaf temperature (Canopy temperature difference), may be beneficial for screening mungbean for drought tolerance.

High Temperature or Heat Stress and Increasing Atmospheric Carbon Dioxide (CO 2 )

Of the various environmental stresses that a plant can experience, temperature has the widest and far-reaching effects on legumes. Temperature extremes, both high (heat stress) and low (cold stress), are injurious to plants at all stages of development, resulting in severe loss of productivity. Legumes, such as chickpea, lentil, mungbean, soybean, and peas, show varying degrees of sensitivity to high and low-temperature stresses, which reduces their potential performance at different developmental stages such as germination, seedling emergence, vegetative phase, flowering, and pod/seed filling phase ( HanumanthaRao et al., 2016 ; Sharma et al., 2016 ). The optimum temperature for growth and development of mungbean is 28–30°C and the range under which plant continues to develop seed is 33–35°C. Each degree rise in temperatures above optimum reduces the seed yield by 35–40% relative to the plants grown under optimum temperature ( Sharma et al., 2016 ).

Temperatures >45°C that often coincides at flowering stage can lead to flower abortion and yield losses. Sharma et al. (2016) evaluated the effect of high temperature on different mungbean lines for vegetative and reproductive performances using Temperature Induction Response (TIR) and physiological screening, techniques at seedling and whole plant levels. The promising tolerant lines were shortlisted for further investigation at the whole plant level. These lines were grown in containers under full irrigation in outdoors; screened for growth and yield traits at two sowings: normal sowing (NS), where day/night temperatures during reproductive stage were <40/28°C, and late sowing (LS), where temperatures were higher (> 40/28°C). The leaves of LS plants showed symptoms of leaf rolling and chlorosis and accelerated phenology lead to sizable marked reduction in leaf area, biomass, flowers and pods. Interestingly, shortening of flowering and podding duration was also observed.

To address ever-fluctuating temperature extremes that various legumes get exposed to, efforts are being made to develop heat-tolerant varieties through conventional breeding methods (exposing breeding lines to open air growing seasons having high temperature episodes either throughout the growth stages or specific to flowering or reproductive phase) in order to select promising tolerant lines. Subsequently subject these shortlisted entries to varied growing environments that coincide with drier/heat periods for confirmatory validation to identify true-genotypes to engage them in heat stress breeding programs. With the advancement of `omics’ era, phenomics platform (phenotyping) can conveniently be applied to screen field shortlisted or promising sub-set of candidates with more precisely conditioned high-temperature regimes (at customized growth periods) to identify true types along with expressed plant architectures. Tolerance to suboptimal temperatures has not been studied extensively in crops like mungbean. However, for the improvement in grain yield of this crop in hilly areas or in higher latitudes it is necessary to introgress traits associated with cold or low-temperature tolerance.

Increasing atmospheric CO 2 concentration along with temperature also pose a constraint to plant growth and development, which would be more pronounced in C 3 plant species (like mungbean) than C 4 . Some of the physiological functions (activation of carboxylating enzymes, photosynthetic rates, cell expansion, carbohydrate synthesis etc) will be enhanced which have an impact on leaf area and biomass associated improvements. An improved biomass by virtue of increased leaf expansion may not always result in higher yield levels. However, in mungbean, higher pod and seed yields were documented when a few high temperature tolerant genotypes exposed to elevated CO 2 of 550 ppm compared to ambient CO 2 of 400 ppm ( Bindumadhava et al., 2018 ). However, molecular mechanism governing aggravated metabolic functions at different growth stages is still unclear and possibility of employing CO 2 fertigation as a breedable trait needs more research attention in days to come from the context of changing global climate.

Waterlogging

Anthropogenic studies reveal that the frequency and severity of flooding events increase with climate change ( Arnell and Liu, 2001 ). Waterlogging adversely affects germination, seedling emergence and growth, crop establishment and root and shoot growth ( Bailey-Serres and Voesenek, 2008 ; Toker and Mutlu, 2011 ). Heavy rains during pod ripening stage results in premature sprouting, leading to inferior seeds. Mungbean is predominantly cultivated in rice-fallow systems and is sensitive to waterlogging ( Singh and Singh, 2011 ). Excess rainfall in such cultivation systems can result in waterlogging wherein roots are completely immersed in water and shoots (sometimes) are partially or fully submerged. Ahmed et al. (2013) highlighted the biochemical mechanisms viz ., increased availability of soluble sugar, enhanced enzymatic activity of glycolytic pathway antioxidant defense mechanism, and altered aerenchyma formation help plants withstand waterlogging. In addition to the deficiency of oxygen, waterlogging can alter the mineral nutrient composition accessible for plants and needs to be considered during genetic crop improvement ( Setter et al., 2009 ). Spring grown crops are more prone to water stress as the rainfall is scanty and farmers mostly prefer to grow this crop on residual moisture. Therefore, cultivating short duration cultivars may help in escaping terminal moisture stress ( Pratap et al., 2013 ).

Breeding for Abiotic Traits

At the plant level, there were several satisfying attempts in mungbean to screen and identify tolerant types for high temperature (heat stress), salinity, waterlogging, and water stress from physiological, biochemical, and molecular perspectives ( Kaur et al., 2015 ; HanumanthaRao et al., 2016 ; Bhandari et al., 2017 ; Manasa et al., 2017 ; Sehgal et al., 2018 ). The breeding lines selected and identified for these aforementioned stresses would form a panel of donor resources for future trait-navigated crop improvement ( Table 4 ).

Table 4 Tolerant/resistant sources of mungbean against abiotic stresses.

The initial phase of breeding in mungbean resulted in selecting a few locally adapted germplasm, mainly for biotic stresses resistance and high yield. While selecting for abiotic stress resistance was not practiced directly, selection for yield, plant type, and adaptation related traits indirectly lead to selection for abiotic stress resistance as well. The selection has been a useful strategy to identify superior cultivars with significant drought tolerance. Warm season food legumes generally encounter two types of drought stresses: (i) terminal drought, which is more prominent in summer/spring crops, usually coincides with late reproductive stage and increases towards generative stage, and (ii) intermittent drought, which may occur anytime during vegetative growth and results due to a break in rainfall or insufficient rains at the vegetative stage. The ranking of warm season food legumes in increasing order of drought resistance was soybean, followed by blackgram, mungbean, groundnut, bambara nut, lablab bean and cowpea ( Singh et al., 1999 ). Fernandez and Kuo (1993) used a stress tolerance index (STI) to select genotypes with high yield and tolerance to temperature and water stresses in mungbean. Singh (1997) described the plant type of mungbean suitable for Kharif (rainy) as well as dry (spring/summer) seasons. Pratap et al. (2013) also suggested the development of short duration cultivars for Spring/Summer cultivation so that these escape terminal heat and drought stress. Cultivars with 60–65 days’ crop cycle, determinate growth habit, high harvest index, reduced photoperiod sensitivity, fast initial growth, longer pods with more than 10 seeds/pod and large seeds are more suitable to the summer season. Keeping this backdrop, a number of early maturing mungbean lines have been selected and released as commercial cultivars.

RNAi Technology: Biotic and Abiotic Stress Resistance

Though conventional breeding strategies have helped breeders to produce disease and insect resistant, and high yielding varieties, the challenges in the conventional breeding make it time-consuming and often leads to the transfer of undesired traits along with desired traits. Further, the functional analysis of candidate genes that code for physiological and biochemical pathways in plants responsible for resistance against diseases and insect-pests have been studied in detail in legumes. However, these studied are limited in mungbean. To further advance the functional genomic analysis of plants, gene silencing technologies using RNA interference (RNAi) or virus-induced gene silencing have been developed to study the expression or inhibition of the candidate genes ( Wesley et al., 2001 ). RNAi technology offers a new and innovative potential tool for plant breeding for resistance/tolerance to biotic and abiotic stresses through the introduction of small non-coding RNA sequences that are able to regulate gene expression in a sequence-specific manner ( Figure 3 ; Dubrovina and Kiselev, 2019 ). The suppression of expression of a specific gene provides an opportunity to remove or accumulate a specific trait in plants that would lead to biochemical or phenotypic changes, which in turn, provide resistance/tolerance to plants against biotic and abiotic stresses. Furthermore, RNAi-mediated gene silencing techniques can be used by plant breeders to suppress genes in full or partially using specific promoters and construct design ( Senthil-Kumar and Mysore, 2010 ). In RNAi technology, the candidate gene activity is disrupted and or silenced in a sequence-specific manner by introducing constructs that generate double-stranded RNAs ( Dennis et al., 1999 ). Though this technology is generally used as a pest and disease control strategy on the pest aspect, the plant-mediated or host-induced RNAi (HI-RNAi) can be used to develop the engineered crop plant material with hair-pin RNAi vector to produce dsRNA that would target the insect and pathogen genes. When the insect feeds on the plant parts, the entry of dsRNA into the insect gut will induce the RNAi activity and silence the target gene in the insect pest ( Zha et al., 2011 ). Further, RNAi can be used to alter the gene expression in plants involved in resistance against diseases ( Senthil-Kumar and Mysore, 2010 ) and abiotic stresses ( Abhary and Rezk, 2015 ). Haq et al. (2010) studied the silencing of complementary-sense virus genes involved in MYMV replication in soybean by targeting a complementary-sense gene (ACI) encoding Replication Initiation Protein (Rep) against Mungbean yellow mosaic India virus. Similarly, Kumar et al. (2017) generated cowpea plants with resistance to MYMV using RNAi technology, which contained three different intron hairpin RNAi constructs. RNAi technology has been used against a number of insect-pests such as H. armigera by targeting the CYP6AE14 gene 9 ( Mao et al., 2007 ). When transcriptional factor genes of H. armigera were targeted by HI-RNAi, a significant reduction in mRNA and protein levels was observed that resulted in deformed larvae and larval mortality ( Xiong et al., 2013 ). Additionally, this technology has been implicated in increasing the production of unique secondary metabolites, increasing the shelf life of the fruits, improving crop yield and improving insect and disease resistance ( Abhary and Rezk, 2015 ). Sunkar and Zhu (2004) reported that in Arabidopsis plants, miRNAs are involved in tolerance against abiotic stress including cold, drought, and salinity. They further showed that exposure to higher salinity levels, dehydration, cold, and abscisic acid upregulated the expression of miR393. While RNAi technology can be used to improve biotic and abiotic stress resistance/tolerance in mungbean, large-scale field studies are needed to study any potential risks of this technology.

Figure 3 Exogenous RNA applications for RNA interference (RNAi) in plants against biotic stresses. (A) Exogenous artificial RNA application on the plant. (B) The exogenous RNAs transported into the cytoplasm. (C) The dsRNA or hpRNA molecules are recognized by a ribonuclease, DICER-like (DICER), which cleaves the dsRNA into siRNAs. (D) The siRNAs are then incorporated in the RNA-induced silencing complex (RISC) that guides sequence-specific degradation or translational repression of homologous mRNAs. (E) The components of the siRNA/mRNA complex can be amplified into secondary siRNAs by the action of RNA-dependent RNA-polymerase (RdRP). (F) Movement of the RNA silencing signal between plant cells and through the vasculature. Dashed arrows depict different steps of the RNAi induction process and dsRNA/siRNA movement between plant cells and plant pathogens. The solid arrow depicts the RdRP-mediated amplification of siRNA. Red arrows depict the local and systemic movement of the RNA silencing signal in the plant (From Dubrovina and Kiselev, 2019 ).

Breeding Constraints for Developing Biotic/Abiotic Stress Resistant/Tolerant Mungbean

In breeding for resistance to biotic and abiotic stresses in legumes, the important factors that are taken into consideration include the genetic distance between the resistant source and the cultivars to be improved, screening methodology, inheritance pattern and the resistance traits to be improved. The genetic diversity and the genetic distances between cultivars and the resistance sources can be integrated in breeding approach such as gene pyramiding ( Kelly et al., 1998 ; Kim et al., 2015 ). The important breeding approaches such as the pedigree and single seed descent methods are used to transfer the major resistant alleles and QTLs between cultivars and elite breeding lines. However, the increased genetic distances between the source and the cultivars lead to segregation of characters, which can be reduced by repeated backcrossing such as inbred-backcrossing, recurrent backcrossing, or congruity backcrossing (i.e., backcrossing alternately with either parent). During early stages of the breeding program for breeding to diseases and insect resistance, introgressing resistance alleles and QTL from wild populations, recurrent or congruity backcrossing or modifications are highly important. Although gamete selection using multiple-parent crosses ( Asensio-S.-Manzanera et al., 2005 , Asensio-S.-Manzanera et al., 2006 ) and recurrent selection ( Kelly and Adams, 1987 ; Singh et al., 1999 ; Terán and Singh, 2010 ), respectively, could be effective, their use in the legumes where a large number of pollinations are required may not be feasible.

Linkage drag is one of the important challenges while developing the disease or insect resistant cultivars, especially when wild sources are used as donors. To reduce linkage drag, repeated backcrossings are needed ( Keneni et al., 2011 ). Deployment of wild germplasm in resistance breeding, which is an important source of resistance introgression to commercial cultivars, is often impeded by the undesirable genetic linkages, which may result in the co-inheritance of the undesired and desired traits that may affect seed quality, germination and other traits ( Edwards and Singh, 2006 ; Acosta-Gallegos et al., 2008 ; Keneni et al., 2011 ). Breeding for resistant to diseases and insect-pests where resistance is controlled by a single gene is easier as compared to multigenic resistance ( Miyagi et al., 2004 ; Somta et al., 2008 ; War et al., 2017 ). The multigenic disease and insect-resistance with low dominance may result in the transfer of the undesirable traits such as leaf size, seed texture, and color along with the desired traits ( Edwards and Singh, 2006 ). Crossing over between homologous chromosomes during meiosis is important to transfer the genes controlling desired traits and to overcome the linkage drag. For this, a large number of F 2 populations is required to be grown to increase the recovery of new recombinants due to crossing-over.

Another very important factor impeding breeding for resistance to diseases is the development of various strains by a pathogen and to insect-pests is the biotypic variation in insect-pests. Plant genotypes that are resistant to one pathogen strain or insect biotype may be susceptible to the other strain of the same pathogen or insect biotype. Insect biotypes show genetic variability within a pest population. Biotype species are morphologically similar, however, their biological traits vary. The emergence and spread of whitefly-transmitted viruses are attributed to the evolution of virus strains, development of aggressive biotypes and increase in the whitefly population ( Chiel et al., 2007 ). While studying the MYMV begomoviruses infecting mungbean and their interaction with B. tabaci in India, Nair et al. (2017) identified that a MYMV resistant NM 94 variety was susceptible to the disease in different locations. The MYMV strains identified were MYMV-Urdbean, MYMV- Vigna and MYMIV. They further identified that three cryptic species of B. tabaci are responsible for spreading MYMD. The cryptic species of whitefly included Asia II 1 (dominant in Northern India), Asia II 8 (dominant in most of Southern, India) and Asia 1 (present in Hyderabad, Telangana, and Coimbatore, Tamil Nadu locations of Southern India). Gene pyramiding the incorporation of multiple resistant genes in a cultivar is seen as an alternative to breeding for diseases/insect resistance with several strains/biotypes.

Though there have been several continued attempts to evolve crop varieties/genotypes for a specific biotic and abiotic stress, on a larger scale, the success achieved was less owing to the combined impact of several stresses and unexpected sudden episodes of pests and diseases all along growth stages of the plants; hence, only a few countable successes have been reported in legumes, more so in cereals. Stemming the critical stage of crop growth for breeding itself need a thorough assessment, be seed germination, early vigour or field establishment, vegetative phase, flowering and early podding to podding stage, reproductive to final maturity stages etc. In this array of developmental stages, pinning down a specific stage and the very influencing trait for breeding seems very challenging though several strategies have hovered around flowering and reproductive phase (being termed `sensitive’) with an objective to develop breeding lines that withstand stress load and produce relatively better pod and seed yield.

Future Outlook

Though a number of disease resistant lines have been developed for yellow mosaic, powdery mildew, and CLS, very few resistant sources are available for anthracnose, dry root rot and bacterial diseases. Further, molecular markers developed for powdery mildew and CLS need to be used in the breeding program to develop further disease resistant lines. Development of markers for dry root rot and anthracnose is needed to fast track development of disease resistant lines. Insect resistant sources of few insects such as bruchids and whiteflies are available, which are being used in breeding programs to develop insect resistant mungbean. However, there is every possibility of the introgression of undesired traits from these resistant sources to the cultivars. In order to have stable disease and insect resistant mungbean for a specific disease or pest, a synergy between the conventional breeding techniques and molecular technologies is very important ( Kim et al., 2015 ; Schafleitner et al., 2016 ). Identification of molecular markers will help in the evaluation of the diseases and pest resistance and reduce our dependency on the phenotypic data, which might be laborious in big trials ( Kitamura et al., 1988 ; Chen et al., 2007 ). Further, using molecular markers can help to transfer insect resistance from the related legumes such as black gram into mungbean. However, it is very important to identify and combine multiple resistant genes into the same cultivar. Thus gene pyramiding should be the target for breeders to develop mungbean with resistance to diseases and insect-pests and avoid strain/biotype development. The mechanism of diseases and insect resistance needs to be studied to identify herbivore- and pathogen-specific signal molecules and their mode of action. Furthermore, the RNAi technology can be used to improve biotic stress resistance in mungbean. However, in order to establish RNAi technology as a potential pest management strategy in plant breeding, large-scale field studies are essential. Further, the potential risks of this technology needs attention.

Breeding mungbean lines for stressful environments is very important. While in particular, stress dominates a population of environments, many of the agroecologies are featured by multiple stresses. This often makes a particular agro-ecology unique for which systemized solutions are essential. For making the best combination of abiotic stress and the traits to incorporate, it is essential to have insight on the fundamental mechanism for stress tolerance from intrinsic physiological and biochemical perspectives. We aim to develop root systems that help plants to withstand moisture deficits by drawing water from the deeper soils. Screening for various abiotic stresses needs to be more precise and stringent to identify robust donor/s for these traits. The identified donors need to put in use by the breeders at a faster pace. Plant type/s having a deep root system, early maturity span, erect stature with sympodial pod-bearing, multiple pods per cluster and longer pods with many nodes and shorter internodes will help in withstanding heat and drought-related stresses. Of late, converging various modern technologies like, infra-red thermography, automated robotics, camera images, and computational algorithms, which all make components of high throughput phenotyping facilities (phenomics and phenospex) can facilitate high throughput phenotyping for stress tolerance ( Pratap et al., 2019b ). However, non-destructive methods being utilized for targeted regions or environments needs optimization for establishing a relation between the known difficult to measure traits and the surrogate parameters derived from images, which represent plant responses to abiotic stresses. These phenomics methods can help precisely quantifying plant shoot architectural responses to stresses caused by soil moisture deficit, salinity, high temperature etc. More than a dozen image parameters have been explained to illustrate the responses of plants to stress that can guide in identifying the relevant traits and the protocol for screening large number of breeding lines or mapping population that are aiming at identification of stress tolerant genes. As evident from published literature, some of the traits such as high photosynthesis or quantum yields have been associated with tolerance to drought, salinity or high temperature. Generally, it is attributed to the capacity of plants to maintain water balance in the tissue reflected by relative water content and stress avoidance mechanism. However, it is essential to look into the traits such as capacity to retain physiological function, for example, even at 50% of optimum relative water content. Such traits are not feasible for application in plant breeding program with conventional approach. However, plant phenomics platform allow no destructive measurement of physiological function such as chlorphyll fluorescence based PS-II system. They are also equipped with NIR-based tools to assess non-destructively tissue water status in plants subjected to stress. These tools can allow measurement of tolerance of PS-II system health at given levels of tissue water content and hence true tolerance to stresses such as soil moisture deficit, salinity and high temperatures. Further, mechanisms to escape from abiotic stresses like drought and high temperatures are extensively been explored in many crops to get optimum yield in stress prone agroecologies. However, there is scope for exploring diurnal escape from stress in a way that plant can exhibit water saving mechanisms during peak stress hours in the diurnal cycle and keep their stomata open for sufficiently capture ambient CO 2 . It is possible to quantify such traits by strategically employing phenomics tools such as infrared imaging system. High temperatures during nights, is likely to enhance respiratory loss of assimilates, however, there are no mechanisms to measure these traits. It is essential to device tools/protocols for these measurements either in high or semi-throughput modes. Since mungbean is grown largely in marginal environments or in a short time between harvest and sowing of preceding and subsequent crops, it is essential to assess recovery from stress and performance in terms of seed yield. Continuous monitoring image based system can allow precise quantification of these traits by separating developmental changes from actual impact of stress. Recently evolved CT scan based tools and protocols will allow understand root-soil-water interaction and can quantify roots system architecture more precisely. This will open up new avenues for designing phenomics and genomics approaches for supporting improvement of stress tolerance in crops.

Molecular approaches are becoming handy in revealing resistance/tolerance mechanisms, which will help in modifying mungbean plants to suit the biotic and abiotic stresses. Genome Wide Association Studies [ Noble et al., 2018 ; Breria et al., 2019 )] would help in better understanding of the genetic basis of the phenotypes. Association mapping for biotic and abiotic resistant/tolerant traits is highly important to identify the desired haplotypes in performing association mapping on a panel of adapted elite breeding lines. This will provide the ample justification to utilize these lines directly in breeding programs. The selection of favorable haplotypes through MAS will be reduce the phenotyping material in the advanced breeding generations and increase the breeding efficiency. The development of NGS technologies, the discovery of SNP/alleles has become easy. This mungbean diversity panel constitutes a valuable resource for genetic dissection of important agronomic traits to accelerate mungbean breeding. Genetic variability with mungbean and between closely related species can be studied from the sequence-based information, which forms a pre-requisite criterion for breeding for resistant/tolerance to biotic and abiotic stress. This is also important for the species conservation and provides breeders with new and/or beneficial alleles for developing advanced breeding materials. Further, advanced phenotyping technologies such as NGS help to increase the discovery of trait-allele and genotype-phenotype interactions. There must be systematic efforts towards exploring physiological and biochemical regulations of biotic and abiotic stresses and studying the whole profile of genes, proteins and metabolites imparting resistance/tolerance so that the same can be manipulated to develop improved cultivars of mungbean.

Author Contributions

RN—conceived the idea and contributed to the review in general. AKP and AW—contributed mainly to the biotic stress section. HB and JR—contributed mainly to the abiotic stress section. TS, AA, AP, SM, RK, EKM, CD, and RS contributed to the review in general.

The financial assistances for this review was provided by Australian Center for International Agricultural Research (ACIAR) through the projects on International Mungbean Improvement Network (CIM-2014-079) and UKaid project on “Unleashing the economic power of vegetables in Africa through quality seed of improved varieties,” the strategic long-term donors to the World Vegetable Center: Republic of China (Taiwan), UK aid from the UK government, United States Agency for International Development (USAID), Germany, Thailand, Philippines, Korea, and Japan. Authors also thank ICAR-NICRA for supporting research on stress tolerance in mungbean.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Keywords: mungbean, breeding, stresses, insect-pests, diseases, marker-assisted selection

Citation: Nair RM, Pandey AK, War AR, Hanumantharao B, Shwe T, Alam AKMM, Pratap A, Malik SR, Karimi R, Mbeyagala EK, Douglas CA, Rane J and Schafleitner R (2019) Biotic and Abiotic Constraints in Mungbean Production—Progress in Genetic Improvement. Front. Plant Sci. 10:1340. doi: 10.3389/fpls.2019.01340

Received: 27 March 2019; Accepted: 25 September 2019; Published: 25 October 2019.

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Copyright © 2019 Nair, Pandey, War, Hanumantharao, Shwe, Alam, Pratap, Malik, Karimi, Mbeyagala, Douglas, Rane and Schafleitner. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Ramakrishnan M. Nair, [email protected]

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