Environmental stresses present major challenges in our quest to achieve sustainable food production. The reactions of plants to environmental stresses are complex and involve many kinds of physiological and biochemical responses. Stress causes multifarious adverse effects in plants. Production of a family of reactive oxygen species (ROS) is a common phenomenon. When plants are subjected to environmental stress, the balance between the production of ROS and the quenching activity of antioxidants is upset, often resulting in an oxidative damage. Plants with high levels of antioxidant enzyme activity are reported to have greater resistance to this oxidative damage. The activities of component enzymes or the antioxidant levels are usually only double in response to many stress situations. This rather moderate response might be understood if we consider that the system is geared to self-destruction when it comes under threat. Understanding the mechanisms by which plants perceive environmental signals and transmit the signals to cellular machinery to activate adaptive responses is of fundamental importance to biology. The present review is focusing on ROS generation and plant defenses to them.

Prediction is an attempt to accurately forecast the outcome of a specific situation while using input information obtained from a set of variables that potentially describe the situation. They can be used to project physiological and agronomic processes; regarding this fact, agronomic traits such as yield can be affected by a large number of variables. In this study, we analyzed a large number of physiological and agronomic traits by screening, clustering, and decision tree models to select the most relevant factors for the prospect of accurately increasing maize grain yield. Decision tree models (with nearly the same performance evaluation) were the most useful tools in understanding the underlying relationships in physiological and agronomic features for selecting the most important and relevant traits (sowing date-location, kernel number per ear, maximum water content, kernel weight, and season duration) corresponding to the maize grain yield. In particular, decision tree generated by C&RT algorithm was the best model for yield prediction based on physiological and agronomical traits which can be extensively employed in future breeding programs. No significant differences in the decision tree models were found when feature selection filtering on data were used, but positive feature selection effect observed in clustering models. Finally, the results showed that the proposed model techniques are useful tools for crop physiologists to search through large datasets seeking patterns for the physiological and agronomic factors, and may assist the selection of the most important traits for the individual site and field. In particular, decision tree models are method of choice with the capability of illustrating different pathways of yield increase in breeding programs, governed by their hierarchy structure of feature ranking as well as pattern discovery via various combinations of features.

In plants, aquaporins (AQP) occur in multiple isoforms in both plasmalemma and tonoplast membranes resulting in regulation of water flow in and out of cells, and ultimately, water transfer through a series of cells in leaves and roots. Consequently, it is not surprising that physiological and molecular studies have identified AQPs as playing key roles in regulating hydraulic conductance in roots and leaves. As a result, the activity of AQPs influences a range of physiological processes including phloem loading, xylem water exit, stomatal aperture and gas exchange. The influence of AQPs on hydraulic conductance in plants is particularly important in regulating plant transpiration rate, particularly under conditions of developing soil water-deficit stress and elevated atmospheric vapor pressure deficit (VPD). In this review, we examine the impact of AQP activity and hydraulic conductance on crop water use and the identification of genotypes that express soil water conservation as a result of these traits. An important outcome of this research has been the identification and commercialization of cultivars of peanut (Arachis hypogaea L.), maize (Zea mays L.), and soybean (Glycine max (Merr) L.) for dry land production systems.