Crop performance is severely affected by high salt concentrations in soils. To engineer more salt-tolerant plants it is crucial to unravel the key components of the plant salt tolerance network. Here we review our understanding of the core salt-tolerance mechanisms in plants. Recent studies have shown that stress sensing and signaling components may play important roles in regulating the plant salinity stress response. We also review key Na+ transport and detoxification pathways and the impact of epigenetic chromatin modifications on salinity tolerance. In addition, we discuss the progress that has been made toward engineering salt tolerance in crops, including marker assisted selection and gene stacking techniques. We also identify key open questions that remain to be addressed in the future.

Elevated CO2 and temperature strongly affect crop production, but understanding of the crop response to combined CO2 and temperature increases under field conditions is still limited while data are scarce. We grew wheat (Triticum aestivum L.) and rice (Oryza sativa L.) under two levels of CO2 (ambient and enriched up to 500 μmol mol(-1) ) and two levels of canopy temperature (ambient and increased by 1.5-2.0 °C) in free-air CO2 enrichment (FACE) systems and carried out a detailed growth and yield component analysis during two growing seasons for both crops. An increase in CO2 resulted in higher grain yield, whereas an increase in temperature reduced grain yield, in both crops. An increase in CO2 was unable to compensate for the negative impact of an increase in temperature on biomass and yield of wheat and rice. Yields of wheat and rice were decreased by 10-12% and 17-35%, respectively, under the combination of elevated CO2 and temperature. The number of filled grains per unit area was the most important yield component accounting for the effects of elevated CO2 and temperature in wheat and rice. Our data showed complex treatment effects on the interplay between preheading duration, nitrogen uptake, tillering, leaf area index, and radiation-use efficiency, and thus on yield components and yield. Nitrogen uptake before heading was crucial in minimizing yield loss due to climate change in both crops. For rice, however, a breeding strategy to increase grain number per m(2) and % filled grains (or to reduce spikelet sterility) at high temperature is also required to prevent yield reduction under conditions of global change.

Magnesium (Mg) is known as one of the essential nutrients for higher plants; yet, the preliminary physiological responses of field crops to its deficiency or excess, particularly to its interaction with potassium (K), remain largely unknown. In this study, we observed that Mg deficiency in rice (Oryza sativa) [less than 1.1 mg g 21 dry weight (DW) in the shoot] resulted in significant reduction in shoot biomass, decrease in total chlorophyll concentration and net photosynthetic rate and reduction in activities of both nitrate reductase [NR; enzyme classification (EC) 1.6.6.1] and glutamine synthetase (EC 6.3.1.2) in the leaves. However, the Mg-deficient plant contained higher starch in the leaves, and partitioned larger biomass into roots. Excess of Mg (more than 3.0 mg g 21 DW in the shoot), together with low K supply, suppressed NR activity and decreased concentration of soluble sugar in the leaves. There were great antagonistic and moderately synergistic effects between K and Mg, but the effects of K were much more significant than those of Mg on their uptake and translocation, NR activity and net photosynthetic rate in the leaves. The optimum weight ratio of K to Mg ranged between 22 and 25 in the leaves at tillering stage. Mg deficiency was not compensated for by moderate supply of K but was aggravated by excess supply of K, suggesting specific roles of Mg in both dry matter production and partition of carbon assimilates in rice.

instantaneous results and has been demonstrated as an effective tool to schedule N fertilization for rice (Oryza Nondestructive monitoring and diagnosis of plant N status is necsativa L.) on an as-needed basis (Turner and Jund, 1991; essary for precision N management. The present study was conducted to determine if canopy reflectance could be used to evaluate leaf Peng et al., 1993). However, there are two factors that N status in rice (Oryza sativa L.). Ground-based canopy spectral limit the use of SPAD meters for N fertilization. First, reflectance and N concentration and accumulation in leaves were a within-field reference (usually an adequately fertilized measured over the entire rice growing season under various treatments area or strip within the field) is required to accurately of N fertilization, irrigation, and plant population. Analyses were quantify N deficiencies. Second, the SPAD meter colmade on the relationships of seasonal canopy spectral reflectance, lects point measurements from a single leaf on a single ratio indices, and normalized difference indices to leaf N concentration plant. Consequently, many leaves from a number of plants and N accumulation in rice under different N treatments. The results must be sampled to obtain a representative average showed that at each sampling date, leaf N concentration was negatively value for a particular sampling date and to adequately asrelated to the reflectance at the green band (560 nm) while positively sess the spatial variability. In contrast, remote sensing related to ratio index, with the best correlation at jointing. However, the relationships between leaf N accumulation and reflectance at of canopy reflectance has the capability to sample a plant green band and ratio index were consistent across the whole growth population or community rather than individual plants period. The ratio of near infrared (NIR) to green (R 810 /R 560 ) was esand to rapidly assess the spatial variability of a crop field. pecially linearly related to total leaf N accumulation, independent of The possibility of predicting crop N status using can-N level and growth stage. Tests of the linear regression model with opy reflectance spectra has been examined for major agrodifferent field experiment data sets involving different plant densities, nomic crops (Thomas and Oerther, 1972; Shibayama N fertilization, and irrigation treatments exhibited good agreement and Akiyama, 1986; Fernandez et al., 1994; Blackmer between the predicted and observed values, with an estimation accuet al.racy of 96.69%, root mean square error of 0.7072, and relative error Shen et al., 2001). For a crop canopy, reflectance is low of Ϫ0.0052. These results indicate that the ratio index of NIR to green near the 480-and 680-nm region due to the strong ab-(R 810 /R 560 ) should be useful for nondestructive monitoring of N status in rice plants.