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Successful plant breeding in saline environments requires high-throughput phenotyping techniques to differentiate genotypes for salinity tolerance. This study employed advanced, non-destructive sensing technologies to identify traits contributing to salinity tolerance in wheat (Triticum aestivum L.). Plants were grown in large containers to simulate field conditions for control, salinity stress alone, and combined salinity and drought stress treatments. The comparative performance of spectral reflectance sensing, thermography, digital imaging, and the assessment of physiological traits of two wheat cultivars were tested at booting, anthesis and grain filling. Variation in grain yield between the two cultivars was significant for all treatments (controls, P < 0.01; others, P < 0.001), whereas there were no significant differences in straw DW regardless of treatment. Among the spectral and thermographic assessments, spectral indices were sufficiently sensitive to detect genotypic differences in salinity tolerance among the wheat cultivars after anthesis for the salinity alone and combined treatments. In contrast, physiological traits such as leaf water status and photosynthetic properties demonstrated no differences between the wheat cultivars for either the salinity alone or the combined treatments. These results suggest that spectral sensing has the potential for high-throughput screening of phenotypic traits associated with salinity tolerance of wheat cultivars. [ABSTRACT FROM AUTHOR]

Many physiological mechanisms associated with nutrient supply have been implicated as improving plant growth under drought conditions. However, benefits to plant growth under drought might derive from an increased recovery of soil water through osmotic adjustment in the shoots and especially in the roots. Thus, experiments were carried out to investigate the effects of the nutrients N, P and K applied singly or in combination, on the osmotic adjustment and turgor maintenance in the roots and leaves of maize seedlings. The seedlings were harvested between 18 and 37 days after sowing according to the soil matric threshold potentials. Soil matric potentials and shoot and root biomass were determined at harvest. Turgor pressure and osmotic adjustment of the leaves and roots were estimated by measurements of their water and osmotic potentials. Results showed that plants with either of the combined fertilisation treatments NPK or NP grew faster at a given level of drought stress than those with no fertilisation, N, P or K applied individually or the combined nutrient treatments PK and NK. Among the fertiliser applications with either a single or two combined nutrients, plants treated with any of N, P or NP grew faster than those with either K or NK. The association between the interactive effects of nutrients and drought stress on the osmotic adjustment and turgor maintenance in roots may partially explain the role of nutrients in drought tolerance of maize seedlings. In particular, the roots exhibited a higher osmotic adjustment than the leaves for all nutrient treatments, suggesting that shoot growth shows a higher sensitivity to water deficit compared to root growth. We conclude that the maintained turgor of roots under drought stress obtained with an optimal nutrient supply results in better root growth and apparently promotes overall plant growth, suggesting that osmotic adjustment is an adaptation not only for surviving stress, but also for growth under such conditions. [ABSTRACT FROM AUTHOR]

Examines the kinetics and spatial distribution of wheat leaf elongation under saline soil conditions. Use of linear variable differential transducer to measure leaf elongation rate; Efficacy of a modified Hoagland nutrient solution for wheat growth; Correlation between the leaf area and the shoot fresh mass during vegetative stages.

Plastic Mulching (PM) is criticized for causing environmental problems in spite of the benefits to increase crop yield. Accurate map of Plastic-Mulched Farmland (PMF) is demanded to monitor the usage of plastic mulches and to mitigate its environmental damages. However, mapping PMF with remote sensing data over large scale is still technically challenging due to its variable spectral characteristic. This paper proposed a Random Forest (RF) workflow to map PMF by coupling multi-resource satellite observations, including high- and medium- resolution optical imageries and Synthetic Aperture Radar (SAR) imageries. Under the context of two typical PMF regions, Jizhou and Guyuan, China, we test the performance of the proposed method. Results indicated that coupling optical and SAR remote sensing data improved the mapping accuracy significantly. There were different strategies for optimal data coupling. Coupling of three data, which are the GaoFen-1 (GF-1) data, Landsat-8 data and Radarsat-2 data, generated the highest mapping accuracy. Besides, coupling the GF-1 data with SAR data produced better accuracy than coupling the Landsat-8 data with SAR data. Compared with the accuracies derived from the coupling of two data (such as coupling GF-1 data with Radarsat-2 data and coupling Landsat-8 data with Radarsat-2 data), coupling the three data improved the overall accuracies by 0.39 to 4.93%. Compared with the mapping accuracy produced from Radarsat-2 data alone, the overall accuracies generated from the optimum coupling increased by 20.96 and 26.06%, respectively, in Jizhou and Guyuan. When compared with the mapping accuracy of GF-1 data alone, the overall accuracies generated from the optimum coupling improved by 4.77% both in Jizhou and Guyuan. In general, contribution of optical remote sensing data was greater than that of SAR data for mapping PMF. Whereas, the SAR data also made great contribution to improve the mapping accuracy of PMF. [ABSTRACT FROM AUTHOR]