Indian Journal of Agricultural Research

  • Chief EditorV. Geethalakshmi

  • Print ISSN 0367-8245

  • Online ISSN 0976-058X

  • NAAS Rating 5.60

  • SJR 0.217, CiteScore: 0.595

Frequency :
Monthly (January, February, March, April, May, June, July, August, September, October, November, December)
Indexing Services :
BIOSIS Preview, ISI Citation Index, Biological Abstracts, Elsevier (Scopus and Embase), AGRICOLA, Google Scholar, CrossRef, CAB Abstracting Journals, Chemical Abstracts, Indian Science Abstracts, EBSCO Indexing Services, Index Copernicus
Submit

Full Research Article

Evaluation of Drought Tolerance and Adaptation of Large-seeded Soybean Genotypes under Various Drought Stress Levels

Kisman1,*, A. Farid Hemon1, Baiq Erna Listiana2, Suprayanti Martia Dewi2, Eries Dyah Mustikarini3
1Program Study of Magister of Dryland Agriculture, University of Mataram, Jl. Pendidikan 37 Mataram, Indonesia.
2Program Study of Agroecotechnology, University of Mataram, Jl. Majapahit 62 Mataram, Indonesia.
3Program Study of Magister of Agriculture Science, University of Bangka Belitung, Indonesia.

ABSTRACT

Background: Adapting large-seeded soybean to drought stress is essential, requiring development drought-tolerant cultivars and management practices to sustain yield under water-limited conditions. This study aimed to evaluate and identify drought-tolerant soybean genotypes using drought indices in order to recommend promising genotypes for cultivation in drought-affecting regions.

Methods: The experiment employed Split-Plot Design in Completely Randomized Design. The main plots were drought stress levels consisting of four levels, non-stress, 10% PEG6000, 20% PEG6000 and 65% field capacity. The sub-plots were 20 large-seeded soybean genotypes,  replicated four times. Based on yield performance under non-stress (Yp) and drought stress (Ys), drought indices (Stress tolerance index, Stress adaptation index, geometric mean productivity, mean productivity, harmonic mean, yield stability index, yield index, drought response index, tolerance index, stress susceptibility Index) were calculated, Pearson correlation and PCA biplot analyses were computed. All statistical analyses were done using the SmartStatXL add-in.

Result: Seed yield of large-seeded soybean genotypes varied significantly under different drought stress levels. Drought tolerance indices, STI, SAI, GMP, MP, HM, DRI and YSI, were strong positive correlated with yield, confirming their effectiveness in identifying drought-tolerant and stable genotypes. PCA biplot analysis effectively separated drought-tolerant from susceptible genotypes and classified Grobogan, Dega-1, KH-1 and Biosay-2 as tolerant under 10% PEG6000 » -0.19 MPa, Grobogan, Dega-1, KH-1 and Burangrang under 20% PEG6000 » -0.67MPa and Grobogan and Dega-1 under 65% field capacity. Of all the drought stress, Grobogan and Dega-1 consistently exhibited superior yield and drought tolerance, making them valuable genetic resources for breeding drought-tolerance soybean.

INTRODUCTION

Water is among the most crucial factors in agriculture. Drought due to lack of water during plant growth will affect plant growth and productivity (Liliane et al., 2020). Therefore, plant tolerance and adaptation to drought stress are very necessary for all crops including soybeans. Drought tolerance soybean enables it to thrive in challenging lack of water environments. Understanding and enhancing this trait is essential for sustainable agriculture and ecosystem management in the face of drought stress and climate change. Soybean breeders and agronomists aim to develop economically viable varieties that maintain yield under drought. Selecting high-yielding and stable yield genotypes under limited-water stress is a key criterion for evaluating (Mahantesh et al., 2018; Yan et al., 2020; Zafer et al., 2023).
       
In Indonesia, more than 110 varieties of soybean have been officially released by government, range from large- to small-seeded, with large-seeded types preferred by farmers and industries for their higher productivity and better suitability for processed products like tempeh and tofu (Prasetiaswati et al., 2022; Xu et al., 2022). The large-seeded genotypes often have tolerance to sub-marginal environmental conditions including drought stress due to their ability to access moisture in deeper soil layers (Riduan et al., 2022). However, many prior studies reported large-seeded genotypes might require more water since morphologically wider leaves more transpiration rate than small-seeded one, making drought tolerance a critical trait for these genotypes in water-limited regions (Kisman  et al., 2021, 2023; Kisman et al., 2022; Kisman et al., 2022). Developing drought-tolerant soybean varieties with favorable agronomic traits is essential. This process relies on access to tolerant genetic resources, effective screening, identification of key tolerance traits and targeted genetic improvement (Bagheri et al., 2023; Emmanuel et al., 2020; Madhu et al., 2023; Malinowska et al., 2020).
       
In identifying drought-tolerant genotypes, numerous effective screening methods have been established and documented. Among these methods, drought indices are commonly utilized, focusing on genotypes that consistently produce a high yield in both stressful and favorable conditions (Shahrokhi et al., 2020), namely stress tolerance index (STI) (Fernandez, 1992) and stress adaptation Index (SAI) (Howeler, 1991a), mean productivity (MP) (Rosielle and Hamblin, 1981), tolerance index (TOL) (Askari et al., 2017), geometric mean productivity (GMP) (Fernandez, 1992), stress susceptability index (SSI) (Fischer and Maurer, 1978), drought resistance index (DI) (Lan, 1998), yield stability index (YSI) (Bouslama and Schapaugh, 1984) and yield index (YI) (Gavuzzi et al., 1997). Those indices have been employed to assess the drought tolerance and adaptation on various crop genotypes by focusing on yield performance, including soybean (Kisman et al., 2021; Riduan et al., 2022; Wang et al., 2022; Zafer et al., 2023), wheat (Eid and Sabry, 2019; Khosravizad, 2023; Sedghiyeh et al., 2025), haricot beans (Wasae, 2021), sweet potato (Gitore et al., 2021), rice (Heinemann et al., 2019; Kumar et al., 2018), barley (Fekadu et al., 2022) and common bean bush (Sánchez-reinoso  et al., 2020). Those drought stress indices can be evaluated on planting media under simulated low water potential conditions induced by PEG 6000, a high-molecular-weight osmotic agent (Jincya et al., 2019; Shobanadevi et al., 2021).
       
This study aimed to evaluate and identify drought-tolerant soybean  genotypes using drought tolerance indices in order to recommend promising genotypes for cultivation in drought-affecting regions.

MATERIALS AND METHODS

Experimental location and materials
 
The experiment took place from May to November 2023 in a greenhouse at “Farm KU”, Tanjung Karang village (8o36' 39.505"S, 116o4' 34.714"E; 9 m a.s.l.), approximately 2 km from the University of Mataram, West Nusa Tenggara, Indonesia. The 2023 average monthly rainfall was 137 mm, with February recording the highest (454 mm over 23 rainy days) (BPS Kota Mataram, 2024). Twenty large-seeded soybean genotypes sourced from various institutions (Table 1) were used. Supporting materials included PEG6000, NPK Phonska (16-16-16), organic fertilizers, goat manure, pesticides (Cruiser 350FS, Furadan 3G, Antracol 70WP, Corona 325SC, Decis 25EC), polybags, burnt rice husks and topsoil collected from rice fields in Pegilen, Kuranji village.

Table 1: Genetic materials consisting of 18 large-seeded and 2 medium-seeded soybean genotypes obtained from various sources.


 
Experimental design
 
The study utilized a completely randomized design (CRD) arranged in a split-plot design within a greenhouse. The main plots comprised for drought levels: S0 (non-stress), S1 (10% PEG6000 ≈ -0.19 MPa), S2 (20% PEG6000 ≈ -0.67 MPa) and S3 (65% field capacity). Subplots consisted of 20 genotypes, with four replications each genotype.
 
Experimental procedures
 
Each 30 cm polybag was filled with 7 kg of a 2:1:1 mixture of dry topsoil, burnt husks and goat manure. Two pre-treated seeds (Cruiser 350FS) were sown per polybag, followed by Furadan 3G application to nitigate soil pests. After three weeks, one healthy plant was retained per polybag. Fertilizer (NPK Phonska) was applied at 50 kg ha-1 both pre-sowing and at 21 DAS. Manual weeding and pest control using Decis 25 EC were conducted twice at 3 and 5 weeks after sowing. Drought stress treatments began at the trifoliate stage, with PEG6000 applied weekly (40 ml) until the reproduktive phase (~30 DAS). The 65% field capacity treatment was managed by watering 1.5 L upon visible wilting symptoms (Kisman et al., 2023). The primary trait measured was seed weight (g plant-1).
 
Drought tolerance and adaptation indices
 
Ten indices (STI, SAI, SSI, DRI, YSI, YI, MP, GMP, HM and TOL) were used to assess genotype performance under stress and non-stress conditions, calculated using standard formulas (Table 2).

Table 2: The formulas used for indexing plant drought tolerance and adaptation under drought stresses.


 
Statistical analyses
 
Analysis of variance (ANOVA) at a 5% significance level was conducted to assess genotype performance across stress levels, followed by Tukey’s HSD test. Drought indices were computed as per Table 2 and Pearson correlation analysis (Fekadu et al., 2022) was used to identify significant associations between yield and indices. Genotypes were categorized based on correlation strength into tolerant/adapted and susceptible groups. Principal Component Analysis (PCA) and biplot visualizations were employed to identify high-yielding genotypes under both stress and non-stress conditions. All analyses were conducted using the SmartStatXL add-in (https://www.smartstat.info/download/category/22-excel-add-in.html#google_vignette).

RESULTS AND DISCUSSION

Variance analysis of seed yield
 
The analysis of variance of seed yield (g plant-1) of soybean genotypes evaluated (Table 3) revealed that a highly significant difference in soybean seed yield due to the single factor (drought stress levels (S), soybean genotypes (G) and the interaction of drought stress levels and soybean genotype (S x G). 

Table 3: Analysis of variance (ANOVA) of seed yield per plant under various drought stress levels.


       
Tukey’s HSD (Table 4) showed that mean seed yield under stress (S1, 11.09±0.57 g plant-1; S2, 9.41±0.51 g plant-1; S3, 9.65±0.54 g plant-1) was consistently lower than under non-stress (S0, 17.75±0.69 g plant-1). Genotype G12 (Grobogan, 21.40±1.69 g plant-1) and G15 (Dega-1, 18.26± 1.62 g plant-1) exhibited the highest yields, while G1 (Detam-2, 4.70±0.39 g plant-1) and G5 (Detam-1, 6.39±0.46 g plant-1) produced the lowest. Genotypes with consistent high yield (G12, G15, G16, G18, G20) or low (G1, G5, G10, G11) under non-stress conditions showed similar patterns under stress.

​

Table 4: Mean seed yield per plant of 20 soybean genotypes under various drought stress levels drought stress levels (S).


       
Yield reductions varied among genotyps across stress levels (Fig 1), consistent with Fekadu et al., (2022) in barley. The smallest reductions occurred in G4 (S1: -1.77%), G1 (S2: -12.58%) and G5/G1 (S3: -28.15%/-28.39%), while G8, G11 and G4 experienced the greatest reductions (-70.95%, -66.94% and -60.17%, respectively). G1 (Detam-2) exhibited the least and G8 (Anjasmoro) the most, yield loss across all stress levels. 

Fig 1: Percentage mean reduction of seed yield per plant (%) of 20 large-seeded soybean genotypes under varying drought stress levels, S0 (normal, 0% PEG6000), S1 (10% PEG6000), S2 (20% PEG6000), S3 (65% field capacity).


       
However, yield reduction alone is not a definitive indicator of drought tolerance. Akbar et al., (2018) dan Purbowahyuani et al., (2019) emphasized that high yields under optimal conditions reflect genetic potential, essential in evaluating stress tolerance. Pertiwi et al., (2022) further noted that tolerance indices prioritize the ability to express genetic potential under non-stress conditions. Thus, yield decline under stress may result from environmental influences rather than poor adaptability. Supporting this, Shahrokhi et al., (2020) indicated that genotypes maintaining high seed yield under both stress and non-stress conditions, reflected in indeces like STI, tends to exhibit superior drought resilience.
 
Drought tolerance and adaptation indices
 
Drought tolerance refers to a plant’s ability to sustain productivity under water-limited conditions (Shoaib et al., 2022), while adaptation involves physiological mechanisms like stomatal closure and osmoprotectant accumulation (Haghpanah et al., 2024; Seleiman et al., 2021). The Stress Adaptation Index (SAI) is a key tool for identifying drought-resilient soybean genotypes, emphasizing high yield potential, as initially propsed by Slamet and Suyamto (2001). Common indices used to assess drought response include STi, SAI, SSI, DRI, YSI, YI, MP, GMP, HM and TOL (Kisman et al., 2021; Riduan et al., 2022; Suhartina et al., 2021; Wasae, 2021).    
       
Table 5 shows considerable variation in drought tolerance indices across genotypes and stress levels (PEG6000 10%, 20% and 65% FC). STI values ranged from 0.1-1.8 with 10-20% of genotypes scoring >1.0 depending on stress level. SAI ranged from 0.1-3.2 with 40% of values >1.0 under all stress conditions. GMP, MP and HM each identified 10-20% exceeding 1.0, while YSI showed higher proportions (40-60%) of genotypes with values >1.0. YI values mostly fell below 1.0 with only 5% exceeding that threshold under S1. TOL and SSI values varied widely but did not indicate consistent tolerance trends. These results are consistent with previous findings in wheat by Eid and Sabry (2019), Khosravizad (2023) and Sedghiyeh et al., (2025). 

Table 5: Drought stress tolerance and adaptation indices of 20 large-seeded soybean genotypes under various drought stress levels (PEG6000 10%, PEG6000 20%, 65% field capacity).


         
Correlation analysis among all drought indices
 
Pearson correlation analysis is essential for identifying effective drought indices to determine genotypes with high yield potential and drought tolerance (Kumar et al., 2018). According to Anwar et al., (2011), indices that strongly correlate with seed yield under both stress and non-stress conditions are considered the most reliable indicators.
       
As shown in Table 6, significant positive correlations were observed among several drought indices, STI, SAI, GMP, MP, HM, DRI and YSI, with seed yields under normal (Yp) and drought stress conditions (Ys1, Ys2, Ys3). These correlations varied with drought severity, as indicated by yield differences between Yp and Ys. These results suggest that these indices are effective in identifying drought-tolerant genotypes capable of maintaining higher yields under stress. These findings align with previous research in wheat (Eid and Sabry, 2019; Khosravizad, 2023; Sedghiyeh et al., 2025).  

Table 6: Pearson correlation matrix of drought indices based on seed yield under PEG6000 10% (S1), PEG6000 20% (S2) and 65% field capacity (S3) drought stress conditions.

 
 
Tolerant/adapted/stable large-seeded soybean genotypes under drought stress
 
Biplot analysis enables effective identification of superior genotypes by simultaneously evaluating yield performance and drought-related indices under varying stress levels. In this current study, biplots constructed using two principal components (PC1 and PC2) illustrated genotype performance under stress levels of 10% PEG6000 (S1), 20% PEG6000 (S2) and 65% field capacity (S3) (Fig 2). PC1 represented overall yield stability and drought tolerance (Yp, Ys, STI, SAI, MP, GMP, HM, DRI, YSI), while PC2 captured drought susceptibility, distinguishing genotypes with high yield only in non-stress conditions. Genotypes with high PC1 and low PC2 were considered optimal (Golabadi and Arzani, 2006).   

Fig 2: Biplot diagram of 20 soybean genotypes based on seed yield under stress and non-stress and drought indices under different drought stress levels: S1 (10% PEG6000), S2 (20% PEG6000), S3 (65% field capacity).

   
       
Using Fernandez (1992) classification, genotypes were grouped based on yield performance: Group A (tolerant), Group B ( non-stress specific), Group C (stress specific) and Group D (susceptible). Under S1, G12 (Grobogan), G15 (Dega-1), G18 (KH-1) and G16 (Biosoy-2) were tolerant. Under S2, G12 (Grobogan), G15 (Dega-1), G13 (Burangrang) and G18 (KH-1) remained in Group A, while under S3, only G12 (Grobogan) and G15 (Dega-1) maintained their tolerat classification. These genotypes, especially KH-1, showed enhanced drought adaptation (Kisman et al., 2022). 
       
Group B include G7 (Argomulyo) under S1 and also G16 (Biosoy-2), G8 (Anjasmoro) under S2 and S3. Group D, comprising drought-susceptible genotypes with low yield under all conditions, included G8, G11 (Kemuning-1), G2 (Denasa-2) and G17 (Detap) at S1; G11, G4, G8, G3 (Denasa-1) at S2; and G4, G3, G9 (Local A) at S3. Genotypes G1, G5 (Detam-1), G10 (edamame Ryoko 75) and G19 (Kaba) were consistently identified in Group C across all stress levels. Prior research also recognized Grobogan and Dega-1 for their drought resilience (Saputra et al., 2015; Sukmasari, 2018; Wahono et al., 2018), with Grobogan noted performance in both drought and waterlogged conditions (Sukmasari, 2018).

CONCLUSION

Seed yield of large-seeded soybean genotypes varied significantly under different drought stress levels (10% PEG6000, 20% and 65% field capacity). Drought tolerance indices (STI, SAI, GMP, MP, HM, DRI and YSI) were significantly positive correlations with yields suggesting their reliability for identifying drought-tolerant and stable large-seeded soybean genotypes. Biplot analysis effectively separated drought-tolerant from susceptable genotypes and classified Grobogan, Dega-1 and Biosoy-2 as tolerant under 10% PEG6000 ≈ -0.19 MPa stress, Grobogan, Dega-1, KH-1 and Burangrang under 20% PEG6000 » -0.67MPa and Grobogan and Dega-1 under 65% field capacity. Of all the drought stress, Grobogan and Dega-1 were consistently superior high-yielding under both stress and non-stress conditions, showing the most tolerant and high dought stability genotypes. These genotypes serve as valuable genetic resources for enhancing drought tolerance in soybean breeding programs. 

ACKNOWLEDGEMENT

A great thanks to the Directorate General of Higher Education of the Education Ministry of Republic of Indonesia for providing competitive research funding through the Regular Fundamental scheme, under contract number: 134/E5/PG.02.00.PL/2023, so that this research can run well. Thank you very much conveyed to the Rector of the University of Mataram, Chairman of LPPM, Dean of the Faculty of Agriculture and all research teams and all parties involved in this research as well.

CONFLICT OF INTEREST

We, all authors declare no conflict of interest.

REFERENCES


  1. Akbar, M.R., Purwoko, B.S., Dewi, I.S. and Suwarno, W.B. (2018). Penentuan indeks seleksi toleransi kekeringan galur dihaploid padi sawah tadah hujan pada fase perkecam- bahan [determination of drought tolerance selection index of rainfed lowland rice doubled haploid lines at germination strage; English Translation]. Jurnal Agronomi Indonesia (Indonesian Journal of Agronomy). 46(2): Article 2. Available at: https://doi.org/10.24831/jai.v46i2.19086.

  2. Anwar, J., Subhani, G.M., Hussain, M., Ahmad, J., Hussain, M. and Munir, M. (2011). Drought tolerance indices and their correlation with yield in exotic wheat genotypes. Pakistan Journal of Botany. 43(3): 1527-1530.

  3. Askari, H., Kazemitabar, S.K., Zarrini, H.N. and Saberi, M.H. (2017). Different statistical procedures for selection of salt tolerant barley genotypes at germination stage. Indian Journal of Agricultural Research. doi: 10.18805/IJARe.A-278.

  4. Bagheri, M., Santos, C.S., Rubiales, D. and Vasconcelos, M.W. (2023). Challenges in pea breeding for tolerance to drought: Status and prospects. Annals of Applied Biology. 183(2): 108-120. https://doi.org/10.1111/aab.12840.

  5. Bouslama, M. and Schapaugh Jr., W.T. (1984). Stress tolerance in soybeans. I. Evaluation of three screening techniques for heat and drought tolerance. Crop Science. 24(5): cropsci1984.0011183X002400050026x. https://doi.org/ 10.2135/cropsci1984.0011183X002400050026x

  6. BPS Kota Mataram. (2024). Kota Mataram Dalam Angka 2024 [Mataram City In Figures 2024; English Translation]. Available at: https://mataramkota.bps.go.id/id/publication/ 2024/02/28/a4fc62ff945a5389e0204278/kota-mataram- dalam-angka-2024.html.

  7. Eid, M.H. and Sabry, S. (2019). Assessment of variability for drought tolerance indices in some wheat (Triticum aestivum L.) genotypes. Egyptian Journal of Agronomy. 41(2): 79-91. https://doi.org/10.21608/agro.2019.10401.1153.

  8. Emmanuel, I., Victor, O., Caroline, U., Rizvi, A.H., Kumar, T. and Alam,  A. (2020). Screening of some selected Indian maize cultivars to simulated drought condition. Indian Journal of Agricultural Research.  54(4): 465-470. doi: 10. 18805/IJARe.A-5247.

  9. Fekadu, W., Mekbib, F., Lakew, B. and Haussmann, B.I.G. (2022). Assessment of genetic variability and acid soil tolerance in ethiopian barley landraces. Ethiopian Journal of Agricultural Sciences. 32(4): Article 4.

  10. Fernandez, G.C.J. (1992). Effective selection criteria for assessing plant stress tolerance. adaptation of food crops to temperature and water stress. International Symposium on Adaptation of Food Crops to Temperature and Water Stress. https:// doi.org/10.22001/wvc.72511.

  11. Fischer, R. A. and Maurer, R. (1978). Drought resistance in spring wheat cultivars. I. Grain yield responses. Australian Journal of Agricultural Research. 29(5): 897-912. https://doi.org/ 10.1071/ar9780897.

  12. Gavuzzi, P., Rizza, F., Palumbo, M., Campanile, R.G., Ricciardi, G L. and Borghi, B. (1997). Evaluation of field and laboratory predictors of drought and heat tolerance in winter cereals. Canadian Journal of Plant Science. 77(4): 523-531. https:// doi.org/10.4141/P96-130.

  13. Gitore, S. A., Danga, B., Henga, S., Gurmu, F., Gitore, S.A., Danga, B., Henga, S. and Gurmu, F. (2021). Evaluating drought tolerance indices for selection of drought tolerant orange fleshed Sweet Potato (OFSP) genotypes in Ethiopia. International Journal of Agricultural Science and Food Technology. 7(2): 249-254.

  14. Golabadi, M. and Arzani, A. (2006). Assessment of drought tolerance in segregating populations in durum wheat. African Journal of Agricultural Research. 1(5): 162-171.

  15. Haghpanah, M., Hashemipetroudi, S., Arzani, A. and Araniti, F. (2024). Drought tolerance in plants: Physiological and molecular responses. plants (Basel, Switzerland). 13(21): 2962. https://doi.org/10.3390/plants13212962.

  16. Heinemann, A.B., Ramirez-Villegas, J., Rebolledo, M.C., Costa Neto, G.M.F. and Castro, A.P. (2019). Upland rice breeding led to increased drought sensitivity in Brazil. Field Crops Research. 231: 57-67. https://doi.org/10.1016/j.fcr.2018.11.009.

  17. Howeler, R.H. (1991a). Identifying Plants Adaptable to Low pH Conditions. In R.J. Wright, V.C. Baligar and R. P. Murrmann (Eds.), Plant-Soil Interactions at Low pH: Proceedings of the Second International Symposium on Plant-Soil Interactions at Low pH, 24-29 June 1990, Beckley West Virginia, USA (pp. 885–904). Springer Netherlands. https:// doi.org/10.1007/978-94-011-3438-5_100.

  18. Howeler, R.H. (1991b). Long-term effect of cassava cultivation on soil productivity. Field Crops Research. 26(1): 1-18. https:// doi.org/10.1016/0378-4290(91)90053-X.

  19. Jafari, A., Paknejad, F. and Jami AL-Ahmadi, M. (2012). Evaluation of selection indices for drought tolerance of corn (Zea mays L.) hybrids. International Journal of Plant Production. 3(4): 33-38. https://doi.org/10.22069/ijpp.2012.661.

  20. Jincya, M., Prasad, V.B.R., Jeyakumara, P., Senthila, A. and Manivannan, N. (2019). Evaluation of green gram genotypes for drought tolerance by PEG (polyethylene glycol) induced drought stress at seedling stage. Legume Research. 44(6): 684-691.  doi: 10.18805/LR-4149.

  21. Khosravizad, B.V.V. (2023). Evaluation of grain yield and drought tolerance indices in Armenian and Iranian wheat varieties under irrigated and non-irrigated conditions. AgriScience and Technology. 2(82). https://journal.anau.am/index.php/ anau/article/view/414.

  22. Kisman, Hemon, A.F., Listiana, B.E., Ismayanti, F.D. and Asrul, L. (2021). Drought Susceptibility Index and Correlation of Soybean Based on Yield and Yield Component. IOP Conference Series: Earth and Environmental Science. 681(1): 012020. https:// doi.org/10.1088/1755-1315/681/1/012020.

  23. Kisman, K., Hemon, A.F., Sumarjan, S. and Dewi, S M. (2023). Physiological response of three large-seeded soybean genotypes under drought and waterlogged stress conditions. AIP Conference Proceedings. 2583(1). https://doi.org/10.1063/5.0116156.

  24. Kisman, K., Yakop, U.M., Dewi, S.M. and Idrus, F.A. (2022). Vegetative Growth Response of Three Large-Seeded Soybean [Glycine max (L.) Merrill] Genotypes under Drought Stress Conditions; Prosiding SAINTEK. 4: 254-266.

  25. Kisman, Sumarjan, Hemon, A.F., Dewi, S.M., Susilowati, L.E. and Gunawan, B.W. (2022). Changes in the anatomical characters of root and stem of three large-seeded soybean [Glycine max (L.) Merrill] under drought stress. IOP Conference Series: Earth and Environmental Science.1107(1): 012031. https://doi.org/10.1088/1755-1315/1107/1/012031.

  26. Kumar, M., Kumar, A. and Mandal, N.P. (2018). Evaluation of recombinant Inbreed Lines (RIL) population of upland rice under stress and non stress conditions for grain yield and drought tolerance. Indian Journal of Agricultural Research. 52(2): 119-125. doi: 10.18805/IJARe.A-4729.

  27. Lan, J. (1998). Comparison of evaluating methods for agronomic drought resistance in crops. Acta Agric Boreali-Occidentalis Sinica. 7: 85-87.

  28. Liliane, T.N., Charles, M.S., Liliane, T.N. and Charles, M.S. (2020). Factors affecting yield of crops. In agronomy-climate change and food security. Intech Open. https://doi.org/ 10.5772/intechopen.90672.

  29. Madhu, B., Sukrutha, B., Singh, N.U., Venkateswarao, G., Madhu, B., Sukrutha, B., Singh, N.U. and Venkateswarao, G. (2023). Breeding strategies for improvement of drought tolerance in rice: Recent approaches and future outlooks. In sustainable rice production-challenges. Strategies and Opportunities. Intech Open. https://doi.org/10.5772/intechopen.107313.

  30. Mahantesh, S., Babu, H.N.R., Ghanti, K. and Raddy, P.C. (2018). Identification of drought tolerant genotypes based on physiological, biomass and yield response in groundnut (Arachis hypogaea L.). Indian Journal of Agricultural Research. 52(3): 221-227. doi: 10.18805/IJARe.A-4984.

  31. Malinowska, M., Donnison, I. and Robson, P. (2020). Morphological and physiological traits that explain yield response to drought stress in miscanthus. Agronomy. 10(8): Article 8. https://doi.org/10.3390/agronomy10081194.

  32. Pertiwi, M.D., Sulistyaningsih, E., Murti, R.H. and Purwanto, B.H. (2022). Identification of high-temperature tolerance of some potato varieties based on stress tolerance indice and cluster analysis. Agric. 34(1): Article 1. https://doi.org/ 10.24246/agric.2022.v34.i1.p79-88.

  33. Prasetiaswati, N., Elisabeth, D.A.A. and Susanto, G.W.A. (2022). The feasibility of large-seeded soybean cultivation. E3S Web of Conferences. 361: 02006. https://doi.org/10. 1051/e3sconf/202236102006.

  34. Purbowahyuani, R., Kastono, D. and Indradewa, D. (2019). Relationship between root traits and drought tolerance of five soybean (Glycine max L.) cultivars. Vegetalika. 8(4): 4. https://doi.org/10.22146/veg.42712.

  35. Riduan, A., Rainiyati, R., Alia, Y. and Nusifera, S. (2022). Tolerance some soybean cultivars to stress drought at vegetative to generative phase. Jurnal Penelitian Pendidikan IPA, 8 (Special Issue), Article SpecialIssue. https://doi.org/10. 29303/jppipa.v8iSpecialIssue.2487.

  36. Rosielle, A.A. and Hamblin, J. (1981). Theoretical aspects of selection for yield in stress and non-stress environment. Crop Science. 21(6): cropsci1981.0011183 X002100 060033x. https://doi.org/10.2135/cropsci1981.00111 83X002100060033x.

  37. Sánchez-reinoso, A.D., Ligarreto-moreno, G.A. and Restrepo-díaz, H. (2020). Evaluation of drought indices to identify tolerant genotypes in common bean bush (Phaseolus vulgaris L.). Journal of Integrative Agriculture. 19(1): 99-107. https:/ /doi.org/10.1016/S2095-3119(19)62620-1.

  38. Saputra, D.S., Timotiwu, P.B. and Ermawati, E. (2015). The effect of drought stress on growth and seed production of five soybean varieties. Jurnal Agrotek Tropika. 3(1): 1. https://doi.org/10.23960/jat.v3i1.1881.

  39. Sedghiyeh, V., Shekari, F., Abbasi, A., Sabaghnia, N. and Roustaii, M. (2025). Evaluation of drought tolerance ability in wheat genotypes through comprehensive stress indices. HAYATI Journal of Biosciences. 32(1). Article 1. https://doi.org/ 10.4308/hjb.32.1.117-131.

  40. Seleiman, M.F., Al-Suhaibani, N., Ali, N., Akmal, M., Alotaibi, M., Refay, Y., Dindaroglu, T., Abdul-Wajid, H.H. and Battaglia, M.L. (2021). Drought stress impacts on plants and different approaches to Alleviate Its Adverse Effects. Plants. 10(2). https://doi.org/10.3390/plants10020259.

  41. Shahrokhi, M., Khorasani, S.K. and Ebrahimi, A. (2020). Evaluation of drought tolerance indices for screening some of super sweet maize [Zea mays (L.) var. Saccharata] inbred lines. AGRIVITA Journal of Agricultural Science. 42(3): 435- 448. https://doi.org/10.17503/agrivita.v42i3.2574.

  42. Shoaib, M., Banerjee, B.P., Hayden, M. and Kant, S. (2022). Roots’ drought adaptive traits in crop improvement. Plants. 11(17): 17. https://doi.org/10.3390/plants11172256.

  43. Shobanadevi, C., Elangaimannan, R. and Vadivel, K. (2021). Screening of blackgram genotypes for drought tolerance using PEG (Polyethylene Glycol) induced drought stress at seedling stage. Legume Research. 45(8): 933-941. doi: 10.18805/ LR-4695.

  44. Slamet, S. and Suyamto, S. (2001). Improvement of soybean genotype tolerance to drought stress. Buletin Palawija. 1: 40-49. https://doi.org/10.21082/bul.

  45. Suhartina, Purwantoro, Nugrahaeni, N. and Mejaya, M.J. (2021). Response of soybean lines to drought stress during reproductive Phase. 324-329. https://doi.org/10.2991/absr.k. 210621.055.

  46. Sukmasari, M.D. (2018). Response of nine soybean [Glycine max (L.) Merrill] varieties grown under water-saturated conditions. Repository Bukudan Jurnal, 0. Available at: https://jurnal.unma.ac.id/index.php/RBJ/article/view/ 771.

  47. Wahono, E., Izzati, M. and Parman, S. (2018). Interaction Between Water Availability levels and varieties on proline content and growth of soybean [Glycine max (L.) Merr]; Buletin  Anatomi dan Fisiologi. 3(1): 11-19. https://doi.org/10.14710/baf.3. 1.2018.11-19.

  48. Wang, X., Li, X. and Dong, S. (2022). Screening and identification of drought tolerance of spring soybean at seedling stage under climate change. Frontiers in Sustainable Food Systems. 6. https://doi.org/10.3389/fsufs.2022.988319.

  49. Wasae, A. (2021). Evaluation of drought stress tolerance based on selection indices in haricot bean varieties exposed to stress at different growth stages. International Journal of Agronomy. 2021(1): 6617874. https://doi.org/10.1155/ 2021/6617874.

  50. Xu, C., Wu, T., Yuan, S., Sun, S., Han, T., Song, W. and Wu, C. (2022). Can soybean cultivars with larger seed size produce more protein, lipids and seed yield? A Meta-Analysis. Foods. 11(24): Article 24. https://doi.org/10.3390/foods 11244059.

  51. Yan, C., Song, S., Wang, W., Wang, C., Li, H., Wang, F., Li, S. and Sun, X. (2020). Screening diverse soybean genotypes for drought tolerance by membership function value based on multiple traits and drought-tolerant coefficient of yield. BMC Plant Biology. 20(1): 321. https://doi.org/10.1186/s12870-020- 02519-9.

  52. Zafer, M., Tahir, M.H., Bakhtavar, M.A., Darwish, E., Khan, M., Khan, Z., Fatima, C., Aftab, A., Rahman, S.U. and Rehman, S.U. (2023). Drought susceptibility Index; a preferred criterion in screening for tolerance in soybean. Journal of Bioresource Manag- ement. 10(1). https://corescholar.libraries.wright.edu/jbm/ vol10/iss1/8.
Reviewed By

Download Article
In this Article
    Contact us
    Follow us

    Editorial Board

    View all (0)