Spatio-temporal evaluation of drought adaptation in wheat revealed NDVI and MTSI as powerful tools for selecting tolerant genotypes
Authors: Srinatha Reddy S. , Singh G. Mahendra , Kumar Uttam , Bhati Pradeep , Vishwakarma Manish , Navathe Sudhir , Yashavanthakumar K. J. , Chand Ramesh , Sharma Sandeep , Mishra Vinod K. , Joshi Arun K. 
Published: January 2023

Context

Water stress is fast becoming a major limiting factor for wheat production. Hence, identifying drought tolerant genotypes is critical for sustaining the food supply chain. However, there are no phenotypic markers or statistical models available that may be employed for the efficient selection of field grown drought tolerant wheat genotypes.

Objectives

We evaluated wheat genotypes to (1) identify novel sources of drought tolerance (2) understand underlying adaptation mechanisms of drought tolerance (3) identify phenotypic markers and a stable model for the selection of drought tolerant genotypes

Methods

One hundred ninety-six diverse wheat genotypes were evaluated at three different locations in India: Banaras Hindu University (BHU), Varanasi (E1 and E3: control; E2 and E4: drought); Agharkar Research Institute (ARI), Pune (E5 and E7: control; E6 and E8: drought) and Borlaug Institute for South Asia (BISA), Jabalpur (E9 and E11: control; E10 and E12: drought) for various agronomic, physiological and yield traits for two consecutive years. Drought was imposed at the heading stage (Z59) by withholding irrigation for four weeks until the moisture reading reached <45% than the control (100%).

Results

The performance of all genotypes significantly declined under drought at all the locations. Normalized difference vegetation index (NDVI) significantly correlated (r = 0.41** and 0.36**) with the grain yield under drought during maturity. At the same time, there was no association under control conditions (r = 0.07 and 0.10) at the BHU center during 2020-21 and 2021-22, respectively. Stress indices, such as geometric mean productivity (GMP) and stress tolerance index (STI), showed a high correlation (r= 0.89** and r = 0.88**, respectively) with the grain yield under drought and were effective in differentiating drought tolerant genotypes. GGE bi-plots discriminated the environments (observed obtuse angle between E3 with E6 and E9, E4 with E6 and E9) having negative relation and cross-over interaction for grain yield. Further, the multi-trait stability index (MTSI) identified 29 stable genotypes across all environments and was predicted as the most accurate model due to its fewer Root Mean Square Prediction Difference (RMSPD) values.

Conclusion

NDVI is a useful high throughput screening tool under drought and MTSI is an effective method for selecting stable wheat genotypes across different water stressed locations.

Implications

The identified tools (NDVI), method (MTSI), and tolerant genotypes appear to be valuable resources that together will be useful in the ongoing breeding programs to enhance the drought tolerance of wheat.

Highlights

Drought stress significantly reduces wheat production globally.

NDVI serves as a useful tool for high throughput screening under drought for field-based experiments.

AMMI, GGE, WAASBY and MTSI plots are effective in detecting GEI effects.

MTSI is a reliable tool for selecting stable and high mean performers.