The world’s five Mediterranean-climate regions (MCRs) share unique climatic regimes of mild, wet winters and warm and dry summers. Agriculture in these regions is threatened by increases in the occurrence of drought and high temperature events associated with climate change (CC). In this review we analyze what would be the effects of CC on crops (including orchards and vineyards), how crops and cropping and farming systems could adapt to CC, and what are the social and economic impacts, as well as the strategies used by producers to adapt to CC. In rainfed areas, water deficit occurs mostly during the flowering and grain filling stages (terminal drought stress), which has large detrimental effects on the productivity of crops. Orchards and vineyards, which are mostly cultivated in irrigated areas, will also be vulnerable to water deficit due to a reduction in water available for irrigation and an increase in evapotranspiration. Adaptation of agriculture to CC in MCRs requires integrated strategies that encompass different levels of organization: the crop (including orchards and vineyards), the cropping system (sequence of crops and management techniques used on a particular agricultural field) and the farming system, which includes the farmer.

In most legume nodules, the di-nitrogen (N₂)-fixing rhizobia are present as organelle-like structures inside their root host cells. Many processes operate and interact within the symbiotic relationship between plants and nodules, including nitrogen (N)/carbon (C) metabolisms, oxygen flow through nodules, oxidative stress, and phosphorous (P) levels. These processes, which influence the regulation of N₂ fixation and are finely tuned on a whole-plant basis, are extensively reviewed in this paper. The carbonic anhydrase (CA)-phosphoenolpyruvate carboxylase (PEPC)-malate dehydrogenase (MDH) is a key pathway inside nodules involved in this regulation, and malate seems to play a crucial role in many aspects of symbiotic N₂ fixation control. How legumes specifically sense N-status and how this stimulates all of the regulatory factors are key issues for understanding N₂ fixation regulation on a whole-plant basis. This must be thoroughly studied in the future since there is no unifying theory that explains all of the aspects involved in regulating N₂ fixation rates to date. Finally, high-throughput functional genomics and molecular tools (i.e., miRNAs) are currently very valuable for the identification of many regulatory elements that are good candidates for accurately dissecting the particular N₂ fixation control mechanisms associated with physiological responses to abiotic stresses. In combination with existing information, utilizing these abundant genetic molecular tools will enable us to identify the specific mechanisms underlying the regulation of N₂ fixation.

Different physiological traits have been proposed as key traits associated with yield potential as well as performance under water stress. The aim of this paper is to examine the genotypic variability of leaf chlorophyll, stem water-soluble carbohydrate content and carbon isotope discrimination (Δ13C), and their relationship with grain yield (GY) and other agronomical traits, under contrasting water conditions in a Mediterranean environment. The study was performed on a large collection of 384 wheat genotypes grown under water stress (WS, rainfed), mild water stress (MWS, deficit irrigation) and full irrigation (FI). The average GY of two growing seasons was 2.4, 4.8 and 8.9 Mg ha-1 under WS, MWS and FI, respectively. Chlorophyll content at anthesis was positively correlated with GY (except under FI in 2011) and the agronomical components kernels per spike (KS) and thousand kernel weight (TKW). The WSC content at anthesis (WSCCa) was negatively correlated with spikes per square meter (SM2), but positively correlated with KS and TKW under WS and FI conditions. As a consequence, the relationships between WSCCa with GY were low or not significant. Therefore, selecting for high stem WSC would not necessary lead to genotypes of GY potential. The relationship between Δ13C and GY was positive under FI and MWS but negative under severe WS (in 2011), indicating higher water use under yield potential and MWS conditions.

Plant breeding based on grain yield (GY) is an expensive and time-consuming method, so new indirect estimation techniques to evaluate the performance of crops represent an alternative method to improve grain yield. The present study evaluated the ability of canopy reflectance spectroscopy at the range from 350 to 2500 nm to predict GY in a large panel (368 genotypes) of wheat (Triticum aestivum L.) through multivariate ridge regression models. Plants were treated under three water regimes in the Mediterranean conditions of central Chile: severe water stress (SWS, rain fed), mild water stress (MWS; one irrigation event around booting) and full irrigation (FI) with mean GYs of 1655, 4739, and 7967 kg∙ha⁻¹, respectively. Models developed from reflectance data during anthesis and grain filling under all water regimes explained between 77% and 91% of the GY variability, with the highest values in SWS condition. When individual models were used to predict yield in the rest of the trials assessed, models fitted during anthesis under MWS performed best. Combined models using data from different water regimes and each phenological stage were used to predict grain yield, and the coefficients of determination (R²) increased to 89.9% and 92.0% for anthesis and grain filling, respectively. The model generated during anthesis in MWS was the best at predicting yields when it was applied to other conditions. Comparisons against conventional reflectance indices were made, showing lower predictive abilities. It was concluded that a Ridge Regression Model using a data set based on spectral reflectance at anthesis or grain filling represents an effective method to predict grain yield in genotypes under different water regimes.

Drought is likely the main abiotic stress that affects wheat yield. The identification of drought-tolerant genotypes represents an effective way of dealing with the continuous decrease in water resources as well as the increase in world population. The aim of this study was to identify single nucleotide polymorphisms (SNP) associated with drought tolerance indices in wheat by using a genome-wide association study (GWAS) under fully irrigated and rain-fed conditions. The drought tolerance indices (i.e., Stress Susceptibility Index, Stress Tolerance Index, Tolerance Index and Yield Stability Index) were calculated based on grain yield, 1,000-kernel weight and kernels per spike. The association panel was genotyped using genotyping-bysequencing (GBS). A total of 175 SNPs exhibited statistical evidence of association with at least one drought tolerance index, explaining up to 6 % of the phenotypic variation. Forty-five SNPs were associated with more than one tolerance index (up to 4 agronomic traits). Most associations were located on chromosome 4A, supporting the hypothesis that this chromosome has a key role in drought tolerance which should be exploited for wheat improvement. In addition, statistical analysis detected SNPs associated with tolerance indices in both growing seasons, providing information about genetic regions with stable effects under different environmental conditions. This GWAS experiment serves as one of the few studies on association mapping for drought tolerance indices in wheat, which could increase the efficiency of rain-fed and irrigated crop production.