Use of Phenomics for Differentiation of Mungbean (Vigna radiata L. Wilczek) Genotypes Varying in Growth Rates Per Unit of Water - Rane, Jagadish; Raina, Susheel Kumar; Govindasamy, Venkadasamy; Bindumadhava, Hanumantharao; Hanjagi, Prashantkumar; Giri, Rajkumar; Jangid, Krishna Kumar; Kumar, Mahesh; Nair, Ramakrishnan M. (Frontiers in Plant Science, 2021)
Mungbean (Vigna radiata L. Wilczek) is an inexpensive and environmentally friendly protein source in the human diet, particularly many of the vegetarian population. As a short duration crop, mungbean fits well into different cropping systems dominated by staple food crops such as rice and wheat. Hence, knowing the growth and production pattern of this important legume under varied soil moisture conditions gains a paramount significance. Towards that end, twenty-four elite mungbean genotypes were grown with and without water stress for 25 days in a controlled environment. Top and side(two) view images of all genotypes captured by high resolution camera installed in the high throughput phenomics were analysed to extract pertinent parameters associated with plants features. We tested eight different multivariate models employing machine learning algorithms, to predict fresh biomass from a dozen features extracted from images of diverse genotypes in the presence and absence of soil moisture stress. Based on the MAE, RMSE, and R squared values, which are used to assess the precision of a model, PLS method among the eight models was selected for predicting the biomass. Predicted biomass was used to compute plant growth rates and water use indices which were found to be highly promising surrogate traits as they could differentiate response of genotypes to soil moisture stress, more effectively. To the best of our knowledge, this is perhaps the first report stating the use of phenomics method as a promising tool for assessing growth rates and also the productive use of water in mungbean crop.