Abstract
The presented study was aimed at investigating the variability for drought tolerance among potato cultivars. To achieve this, the stability of drought tolerance of potato cultivars under different water regime conditions was inspected during 11 years of consecutive experiments. The data on 50 potato cultivars’ responses to drought stress, based on the morphological features of plants, i.e., leaf and stem mass and size of the assimilation area, have been collected. The tuber yield, as well as calculated plant tolerance indexes and Climatic Water Balance for each growing season, were analyzed. The studied cultivars were later assigned into one of three tolerance groups for soil drought. The highest linear relationship was found between the mass of leaves and stems and the tuber yield but was found too weak to raise any conclusions. Thus, the ensemble learning models have been evaluated and returned better performance results, and the final classifier is the implementation of extreme gradient boosting. The final classifier of the 96.7% accuracy, which used several measured potato parameters (Relative yield decrease, Stem mass, Maturity, Assimilation area, Leaves mass, Yield per plant, calculated Climatic water balance, and indices: MSTI and DSI) that could distinguish the different tolerance groups were evaluated in the study.
Highlights
Global climate change in the form of extreme heat and drought poses a major challenge to sustainable crop production by negatively affecting plant performance and crop yield [1,2]
Hijmans [6] anticipates that the world potato production will decline by 18–32% in the projected period of 2040–2069 as a consequence of biotic and abiotic stresses associated with climate change
The detailed objectives of this study are to understand (1) the variability for drought tolerance among potato cultivars, (2) the stability of drought tolerance of potato cultivars under different water regime conditions, and (3) the relation between physiological traits and tuber production under drought stress and the machine learning approach to both prepare and evaluate the model able to describe the tolerance of potato cultivars to drought stress using several agronomic and morphological features of plants
Summary
Global climate change in the form of extreme heat and drought poses a major challenge to sustainable crop production by negatively affecting plant performance and crop yield [1,2]. Potatoes are cultivated in over 100 countries feeding over a billion people worldwide. They are a rich source of carbohydrates and provide other essential nutrients, such as dietary fiber, vitamins, minerals, protein, and antioxidants [3]. It has been predicted that the potato yield will decline substantially by 2055 due to global warming and drought [5]. Hijmans [6] anticipates that the world potato production will decline by 18–32% in the projected period of 2040–2069 as a consequence of biotic and abiotic stresses associated with climate change. To improve the potato yield, we need to identify the best production practices and develop new potato cultivars that best fit the predicted climate change
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