1.
A high-quality genome assembly highlights rye genomic characteristics and agronomically important genes.
Li, G, Wang, L, Yang, J, He, H, Jin, H, Li, X, Ren, T, Ren, Z, Li, F, Han, X, et al
Nature genetics. 2021;(4):574-584
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Abstract
Rye is a valuable food and forage crop, an important genetic resource for wheat and triticale improvement and an indispensable material for efficient comparative genomic studies in grasses. Here, we sequenced the genome of Weining rye, an elite Chinese rye variety. The assembled contigs (7.74 Gb) accounted for 98.47% of the estimated genome size (7.86 Gb), with 93.67% of the contigs (7.25 Gb) assigned to seven chromosomes. Repetitive elements constituted 90.31% of the assembled genome. Compared to previously sequenced Triticeae genomes, Daniela, Sumaya and Sumana retrotransposons showed strong expansion in rye. Further analyses of the Weining assembly shed new light on genome-wide gene duplications and their impact on starch biosynthesis genes, physical organization of complex prolamin loci, gene expression features underlying early heading trait and putative domestication-associated chromosomal regions and loci in rye. This genome sequence promises to accelerate genomic and breeding studies in rye and related cereal crops.
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Eco-Friendly Nanoplatforms for Crop Quality Control, Protection, and Nutrition.
Wang, CY, Yang, J, Qin, JC, Yang, YW
Advanced science (Weinheim, Baden-Wurttemberg, Germany). 2021;(9):2004525
Abstract
Agricultural chemicals have been widely utilized to manage pests, weeds, and plant pathogens for maximizing crop yields. However, the excessive use of these organic substances to compensate their instability in the environment has caused severe environmental consequences, threatened human health, and consumed enormous economic costs. In order to improve the utilization efficiency of these agricultural chemicals, one strategy that attracted researchers is to design novel eco-friendly nanoplatforms. To date, numerous advanced nanoplatforms with functional components have been applied in the agricultural field, such as silica-based materials for pesticides delivery, metal/metal oxide nanoparticles for pesticides/mycotoxins detection, and carbon nanoparticles for fertilizers delivery. In this review, the synthesis, applications, and mechanisms of recent eco-friendly nanoplatforms in the agricultural field, including pesticides and mycotoxins on-site detection, phytopathogen inactivation, pest control, and crops growth regulation for guaranteeing food security, enhancing the utilization efficiency of agricultural chemicals and increasing crop yields are highlighted. The review also stimulates new thinking for improving the existing agricultural technologies, protecting crops from biotic and abiotic stress, alleviating the global food crisis, and ensuring food security. In addition, the challenges to overcome the constrained applications of functional nanoplatforms in the agricultural field are also discussed.
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Potential of vegetation indices combined with laser-induced fluorescence parameters for monitoring leaf nitrogen content in paddy rice.
Yang, J, Du, L, Gong, W, Shi, S, Sun, J, Chen, B
PloS one. 2018;(1):e0191068
Abstract
Nitrogen (N) is important for the growth of crops. Leaf nitrogen content (LNC) serves as a crucial indicator of the growth status of crops and can help determine the dose of N fertilizer. Laser-induced fluorescence (LIF) technology and the reflectance spectra of crops are widely used to detect the biochemical content of leaves. Many vegetation indices (VIs) and fluorescence parameters have been developed to estimate LNC. However, the comparison among VIs and between fluorescence parameters and VIs has been rarely studied in the estimation of LNC. In this study, the performances of several published empirical VIs and fluorescence parameters for the estimation of paddy rice LNC were analyzed using the support vector machine (SVM) algorithm. Then, the optimal VIs (TVI, MTVI1, MTVI2, and MSAVI) and fluorescence parameters (F735/F460 and F685/F460), which were suitable for LNC monitoring in this study, were chosen. In addition, the combination of the VIs and fluorescence parameters was proposed as the input variables in the SVM model and used to estimate the LNC. Experimental results exhibited the promising potential of the LIF technology combined with reflectance for the accurate estimation of LNC, which provided guidance for monitoring the LNC.