Journal of Crop Improvement · 2020 · 16 citations · 23 references
AgricultureCrop SciencesPlant SciencesCrop-weed CompetitionWeed BiologyWeed EcologyCompetitive AbilityCrop CompetitionCrop-weed InteractionsWeed CompetitionWeed ManagementWeed SuppressionCrop Tolerance To WeedsCrop Yield ImprovementCrop-weed Competitiveness AssessmentGreenhouse BiocontrolSustainable Weed ManagementWeed Growth SuppressionWeed Seedling SuppressionWeed Suppressive Traits
Rice (Oryza sativa L.) is a vital crop for achieving global food security. Unfortunately, weeds are the major yield-constraining factor in rice production systems worldwide. Development of rice with higher competitive ability than weeds will help achieve sustainable weed management, as robust rice cultivars will have a competitive advantage over weeds. As wild relatives are often explored by plant breeders in crop improvement programs, greenhouse studies were conducted to evaluate weed-suppressive potential of 54 weedy rice accessions (weedy relatives of cultivated rice) against barnyardgrass (Echinochloa crus-galli) and Amazon sprangletop (Leptochloa panicoides). Three allelopathic rice cultivars (PI312777, PI338046, and Rondo), and two commercial rice cultivars (CL163 and REX) were included as a positive and negative control, respectively. Among all the test accessions of weedy rice, B2 suppressed the growth of E. crus-galli by 52%, whereas accession B81 suppressed L. panicoides growth by 61%. Accession B81 caused greater than 50% growth inhibition of both E. crus-galli and L. panicoides. Thus, B2 and B81 were identified as the most weed-suppressive weedy rice accessions. Weed-suppressive potential in weedy rice was associated morphologically with hull type and awn length. Weed-suppressive weedy rice accessions identified from this study can be used as a source of raw genetic material in rice improvement programs. Future research should focus on identifying the underlying mechanism for a high weed-suppressive potential of specific weedy rice accessions.
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R: A Language and Environment for Statistical Computing
R Core Team · 2000 · 353K citations · Full text
Natural Sciences, Computer Science, Statistical Computing +10
Signatures of adaptation in the weedy rice genome
Linfeng Li, Yaling Li, Yulin Jia et al. · Nature Genetics · 2017 · 202 citations