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2327条记录
Deeply functional identification of TCS1 alleles provides efficient technical paths for low-caffeine breeding of tea plants

SCI

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来源:HORTICULTURE RESEARCH年份:2023
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Morphological and molecular analyses reveal two new species of Termitomyces (Agaricales, Lyophyllaceae) and morphological variability of T. intermedius

SCI

机构:

来源:MYCOKEYS年份:2023

关键词: 2 new species; morphology; multi-gene phylogeny; taxonomy; tropical Asia; Yunnan

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Southern rice black-streaked dwarf virus induces incomplete autophagy for persistence in gut epithelial cells of its vector insect

SCI

机构:

来源:PLOS PATHOGENS年份:2023
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Genome-wide assessment of genetic variation and differentiation for Gastrodia elata germplasm based on SLAF sequencing

SCI

机构:

来源:GENETIC RESOURCES AND CROP EVOLUTION年份:2023

关键词: Gastrodia elata BI; Genetic diversity; SLAF-seq SNP

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Loss of Rose Fragrance under Chilling Stress Is Associated with Changes in DNA Methylation and Volatile Biosynthesis

SCI

机构:

来源:GENES年份:2023

关键词: rose; flower scent; DNA methylation; chilling stress; gene expression

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Population Growth of Fall Armyworm, Spodoptera frugiperda Fed on Cereal and Pulse Host Plants Cultivated in Yunnan Province, China

SCI

机构:

来源:PLANTS-BASEL年份:2023

关键词: Spodoptera frugiperda; host plants; life table; survival rate; maize; wheat; barley; faba beans; soya beans

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Predicting heterosis via genetic distance and the number of SNPs in selected segments of chromosomes in maize

SCI

机构:

来源:FRONTIERS IN PLANT SCIENCE年份:2023

关键词: maize; grain yield; heterosis prediction; SNP; genetic distance

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First Report of Tobacco Mosaic Virus Infection in Paris polyphylla var. yunnanensis in China

SCI

机构:

来源:PLANT DISEASE年份:2023

关键词: China; Paris polyphylla var; yunnanensis; tobacco mosaic virus

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A parsimonious model for predicting the NO3--N concentration in shallow groundwater in intensive agricultural areas using few easily accessible indicators and small datasets based on machine learning

SCI

机构:

来源:JOURNAL OF HYDROLOGY年份:2023

关键词: E; Brookfield; Associate Editor; Shallow groundwater; NO 3; -N prediction; Machine learning; Intensive agricultural area

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