Soil salinity is a worldwide issue that affects wheat production. A comprehensive understanding of salt-tolerance mechanisms and the selection of reliable screening indices are crucial for breeding salt-tolerant wheat cultivars. In this study, 30 wheat genotypes (obtained from a rapid selection of 96 original varieties) were chosen to investigate the existing screening methods and clarify the salinity tolerance mechanisms in wheat. Ten-day-old seedlings were treated with 150 mM NaCl. Eighteen agronomic and physiological parameters were measured. The results indicated that the effects of salinity on the agronomic and physiological traits were significant. Salinity stress significantly decreased K⁺ content and K⁺/Na⁺ ratio in the whole plant, while the leaf K⁺/Na⁺ ratio was the strongest determinant of salinity tolerance and had a significantly positive correlation with salt tolerance. In contrast, salinity stress significantly increased Na⁺ concentration and relative gene expression (TaHKT1;5, TaSOS1, and TaAKT1-like). The Na⁺ transporter gene (TaHKT1;5) showed a significantly greater increase in expression than the K⁺ transporter gene (TaAKT1-like). We concluded that Na⁺ exclusion rather than K⁺ retention contributed to an optimal leaf K⁺/Na⁺ ratio. Furthermore, the present exploration revealed that, under salt stress, tolerant accessions had higher shoot water content, shoot dry weight and lower stomatal density, leaf sap osmolality, and a significantly negative correlation was observed between salt tolerance and stomatal density. This indicated that changes in stomata density may represent a fundamental mechanism by which a plant may optimize water productivity and maintain growth under saline conditions. Taken together, the leaf K⁺/Na⁺ ratio and stomatal density can be used as reliable screening indices for salt tolerance in wheat at the seedling stage.

SUMMARY: The effect of high temperatures (above 25°C) on starch concentration and the morphology of starch granules in the grains of wheat (Triticum aestivum L.) were studied. Wheat plants of cultivars Yangmai 9 (weak-gluten) and Yangmai 12 (medium-gluten) were treated with high temperatures for 3 days at different times after anthesis. The results showed that the starch concentration of grains given a heat-shock treatment above 30°C were lower than those developing at normal temperature in both cultivars. High temperature lowered starch concentration due to the decrease of amylopectin. Under the same temperature, the effect of heat shock from 6 to 8 days after anthesis (DAA) was the greatest, whereas from 36 to 38 DAA the effect was the least. The effects of high temperatures after anthesis on starch-pasting properties were similar to those on starch concentration, especially after 35–40°C treatments. The size, shape and structure of starch granules in wheat grains (determined by electron microscopy) after heat shock were visibly different from the control. When given heat shock during development, the starch granules in mature wheat grains were ellipsoid in shape and bound loosely with a protein sheath in Yangmai 9, while they were damaged and compressed with fissures in Yangmai 12, indicating the differences in resistance to high temperature between cultivars. Ratios of large (type-A) and small (type-B) starch granules significantly decreased under heat shock, which limited the potential sink size for dry matter deposition in the grain.

Background: The number grain per panicle of rice is an important phenotypic trait and a significant index for variety screening and cultivation management. The methods that are currently used to count the number of grains per panicle are manually conducted, making them labor intensive and time consuming. Existing image-based grain counting methods had difficulty in separating overlapped grains. Results: In this study, we aimed to develop an image analysis-based method to quickly quantify the number of rice grains per panicle. We compared the counting accuracy of several methods among different image acquisition devices and multiple panicle shapes on both Indica and Japonica subspecies of rice. The linear regression model developed in this study had a grain counting accuracy greater than 96% and 97% for Japonica and Indica rice, respectively. Moreover, while the deep learning model that we used was more time consuming than the linear regression model, the average counting accuracy was greater than 99%. Conclusions: We developed a rice grain counting method that accurately counts the number of grains on a detached panicle, and believe this method can be a huge asset for guiding the development of high throughput methods for counting the grain number per panicle in other crops.

Improving winter wheat water use efficiency in the North China Plain (NCP), China is essential in light of current irrigation water shortages. In this study, the AquaCrop model was used to calibrate, and validate winter wheat crop performance under various planting dates and irrigation application rates. All experiments were conducted at the Xiaotangshan experimental site in Beijing, China, during seasons of 2008/2009, 2009/2010, 2010/2011 and 2011/2012. This model was first calibrated using data from 2008/2009 and 2009/2010, and subsequently validated using data from 2010/2011 and 2011/2012. The results showed that the simulated canopy cover (CC), biomass yield (BY) and grain yield (GY) were consistent with the measured CC, BY and GY, with corresponding coefficients of determination (R²) of 0.93, 0.91 and 0.93, respectively. In addition, relationships between BY, GY and transpiration (T), (R² = 0.57 and 0.71, respectively) was observed. These results suggest that frequent irrigation with a small amount of water significantly improved BY and GY. Collectively, these results indicate that the AquaCrop model can be used in the evaluation of various winter wheat irrigation strategies. The AquaCrop model predicted winter wheat CC, BY and GY with acceptable accuracy. Therefore, we concluded that AquaCrop is a useful decision-making tool for use in efforts to optimize wheat winter planting dates, and irrigation strategies.