In rice–wheat systems, late sowing of wheat is the major reason of low yield. This yield reduction is principally due to lower and erratic germination, and poor crop establishment because of low temperature prevailing. The present study was conducted to explore the possibility of improving late sown wheat performance by seed priming techniques. Seed priming strategies were: on‐farm seed priming, hydropriming for 24 h, seed hardening for 12 h and osmohardening with KCl or CaCl2 for 12 h. Seed priming improved emergence, stand establishment, tiller numbers, allometry, grain and straw yield, and harvest index. However, seed priming techniques did not affect plant height, number of spikelets, number of grains and 1000 grain weight. Osmohardening with CaCl2 gave more grain and straw yield and harvest index compared with control and other priming treatments, followed by osmohardening with KCl and on‐farm seed priming. Improved yield was attributed principally to better stand establishment and improved number of fertile tillers. Seed priming techniques can be effectively used to improve the performance of late sown wheat.
Drought stress encumbers the rice growth predominantly by oxidative damage to biological membranes and disturbed tissue water status. In this study, the role of salicylic acid (SA) to induce drought tolerance in aromatic fine grain rice cultivar Basmati 2000 was evaluated. SA was applied as seed and foliar treatments. For seed treatment, rice seeds were soaked in 50, 100 and 150 mg l−1 aerated solution of SA for 48 h and then dried back. Treated and untreated seeds were sown in plastic pots in a phytotron. At four leaf stage, one set of plants was subjected to drought stress, while the other remained well watered. Drought was maintained at 50 % of field capacity by watering every alternate day. For exogenous application, SA was applied 50, 100 and 150 mg l−1 at five leaf stage. In the control, SA was neither applied exogenously nor as seed treatment. Drought stress severely affected the seedling fresh and dry weight, photosynthesis, stomatal conductance, plant water relations and starch metabolism; however, SA application improved the performance of rice under both normal and stress conditions. Drought tolerance in rice was well associated with the accumulation of compatible solutes, maintenance of tissue water potential and enhanced potency of antioxidant system, which improved the integrity of cellular membranes and facilitated the rice plant to sustain photosynthesis and general metabolism. Foliar treatments were more effective than the seed treatments. Foliar application with 100 mg l−1 (FA 100) was the best treatment to induce the drought tolerance and improve the performance under normal and stress conditions compared with the control or other treatments used in this study.
Plants are as vulnerable by diseases as animals. Citrus is a major plant grown mainly in the tropical areas of the world due to its richness in vitamin C and other important nutrients. The production of the citrus fruit has been widely affected by citrus diseases which ultimately degrades the fruit quality and causes financial loss to the growers. During the past decade, image processing and computer vision methods have been broadly adopted for the detection and classification of plant diseases. Early detection of diseases in citrus plants helps in preventing them to spread in the orchards which minimize the financial loss to the farmers. In this article, an image dataset citrus fruits, leaves, and stem is presented. The dataset holds citrus fruits and leaves images of healthy and infected plants with diseases such as Black spot, Canker, Scab, Greening, and Melanose. Most of the images were captured in December from the Orchards in Sargodha region of Pakistan when the fruit was about to ripen and maximum diseases were found on citrus plants. The dataset is hosted by the Department of Computer Science, University of Gujrat and acquired under the mutual cooperation of the University of Gujrat and the Citrus Research Center, Government of Punjab, Pakistan. The dataset would potentially be helpful to researchers who use machine learning and computer vision algorithms to develop computer applications to help farmers in early detection of plant diseases. The dataset is freely available at https://data.mendeley.com/datasets/3f83gxmv57/2.
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