This study aims to explain the effects of silicon (Si) foliar application on gas exchange characteristics, photosynthetic pigments, membrane stability and leaf relative water content of different wheat cultivars in the field under drought stress conditions. The experiment was arranged as a split-split plot based on randomized complete block design with three replications. Irrigation regime (100%, 60%, and 40% F.C.), silicon (control and Si application) and wheat cultivars (Shiraz, Marvdasht, Chamran, and Sirvan) were considered as main, sub and sub-sub plots, respectively. This study was carried out at the Research Farm of the Collage of Agriculture, Shiraz University, Iran, during 2012–2013 growing season. The results showed that foliar application of silicon increased the leaf relative water content, photosynthesis pigments (chlorophyll a, b and total chl and carotenoids), chlorophyll stability index (CSI) and membrane stability index (MSI) in all wheat cultivars, especially in Sirvan and Chamran (drought tolerant cultivars), under both stress and non-stress conditions. However, more improvement was observed under drought stress as compared to the non-stress condition. In contrast, these parameters decreased under drought stress. Si significantly decreased electrolyte leakage in all four cultivars under drought stress conditions. Furthermore, the intercellular carbon dioxide (CO₂) concentration (C_i) increased under drought stress. Si application decreased C_i especially under drought stress conditions. Net photosynthesis rate (A), transpiration rate (E) and stomatal conductance (g_s) were significantly decreased under drought conditions. Under drought, Si applied plants showed significantly higher leaf photosynthesis rate, transpiration rate, and stomatal conductance. Intrinsic water use efficiency (WUEi) and carboxylation efficiency (C_E) decreased in all cultivars under drought stress. However, the silicon-applied plants had greater WUEi and C_E under drought stress. The stomatal limitation was found to be higher in stressed plants compared to the control. Exogenously applied silicon also decreased stomatal limitation. Overall, application of Si was found beneficial for improving drought tolerance of wheat plants.

The effects of silicon (Si) and salicylic acid (SA) applications on proline content and expression of Δ¹-pyrrolin-5-carboxylate synthetase (P5CS) were examined under different drought levels and different drought exposure times. Two wheat cultivars, a drought tolerant and a drought sensitive were used. The experiment was a factorial based on completely randomized design with three replicates. Expression analysis by the quantitative real time PCR showed that the tolerant cultivar had significantly higher P5CS expressions compared to the sensitive one under drought stress. In sampling time points, the maximum level of mRNA was observed at 48 h after stress was applied. At 48 h after stress induction, the expression of P5CS was almost 3.1 fold higher in the tolerant cultivar compared to the sensitive one. In both cultivars, gene expression decreased from 48 to 72 h. The stressed plants treated with Si + SA showed a higher expression. Proline content started to increase by Si and SA treatments and the maximum proline content was obtained at simultaneous application of Si + SA. Drought stress significantly reduced chlorophyll content, relative water content and leaf water potential of both cultivars, while increased electrolyte leakage (EL) of the leaves. In contrast, foliar-applied Si and SA significantly increased these parameters and reduced EL, and the effect of simultaneous application of Si and SA was greater. The results suggest that the P5CS is a stress inducible gene. This gene has the potential to be used for improvement of drought stress tolerance in wheat. Network analysis highlighted positive interaction of osmotic stress, drought and cold stress on P5CS1 and the regulatory role of MYB2, ERF-1, and EIN3 transcription factors. In conclusion, alleviation of drought stress by application of Si and SA was associated partially with enhanced expression of P5CS gene and following proline accumulation.

The role of exogenous individual or combined application of silicon (Si) and salicylic acid (SA) (control, 6 mm Si, 1 mm SA, and 6 mm Si + 1 mm SA) on grain yield and some key physiological characteristics of wheat (Triticum aestivum L.) cvv. Shiraz (drought-sensitive) and Sirvan (drought-tolerant) was investigated under field water-stress conditions (100% and 40% field capacity). Drought stress caused a considerable reduction in biological yield, yield and yield components, relative water content and leaf water potential of both cultivars. Application of Si and SA effectively improved these parameters in water-deficit treatments. Moreover, water-limited conditions markedly promoted the activities of key antioxidant enzymes including peroxidase, ascorbate peroxidase, catalase and superoxide dismutase as well as the levels of malondialdehyde (MDA) and hydrogen peroxide (H2O2), while enhancing the accumulation of soluble sugars, potassium, magnesium and calcium in leaf tissues. Application of Si and SA further enhanced the activities of the key antioxidant enzymes and accumulation of osmolytes, and decreased the levels of H2O2 and MDA in drought-stressed plants; the positive effects of Si were greatest when it was applied with SA. Synergistic effects of Si + SA application on yield and physiological parameters were apparent compared with Si or SA applied separately. Water-stress alleviation and yield improvement in the wheat cultivars by Si and SA application was attributable to partly improved osmotic adjustment and antioxidant activity as well as to more favourable water status under stress conditions. Overall, Si and SA application proved to have great potential in promoting grain yield of wheat in drought-prone areas.

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.