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Grain yield performance of hybrid rice in relation to inbred cultivars in long-term multi-environment tests in India

印度长期多环境试验中杂交水稻与近交品种的产量表现

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来源:
CROP SCIENCE
来源地址:
//agri.nais.net.cn/topic/downloadFile/ad7217f0-4cd7-410d-a304-0e0685c3199b
类型:
学术文献
语种:
英语
原文发布日期:
2022-05-01
摘要:
We analyzed the yield data of 2,070 rice hybrid F-1 genotypes with inbred local cultivars (ILCv) evaluated over 32 yr (from 1988 to 2019) in 2,376 multi-environment experiments executed at 102 locations in the irrigated ecosystem across India. The genetic gain or loss in yield of hybrid F-1 genotypes estimated over the test duration was nonsignificant. The differences were highly significant between the means of group of F-1 hybrid genotypes with yields higher than ILCvs in 985 experiments and the group of F-1 hybrid genotypes with yields lower than ILCvs in 962 experiments. Hybrids produced 10% more yield (728-2,588 kg ha(-1)) than ILCvs in 672 experiments at several locations. Our analyses have established that grain yields of 7.0-7.9 Mg ha(-1), were harvested in hybrid F-1 genotypes with early- (110-120 d), mid-early- (121-130 d), and medium- (131-140 d) maturity duration, and in those with medium slender grains (130 +/- 5 d) at many locations in 374 out of the 985 experiments. A higher level of rice (Oryza sativa L.) productivity per day (62-63 kg ha(-1)) was recorded with the early-maturing and mid-early-maturing hybrid genotypes. Both the hybrid F-1 genotypes and ILCvs produced grain yields (>= 10 Mg ha(-1)) similar to values that were recorded previously with commercial inbred cultivars since 1968 at many locations. The attainable grain yield records of ILCvs were not broken by the yields of hybrid F-1 genotypes. Hence the doubt arises whether there was any overestimation of hybrid genotypes or an underestimation of inbred yields. Therefore, any genetic gain or loss for grain yields in new genotypes developed in experiments can be estimated only when ILCvs produce their attainable yield recorded previously. There is scope for breeders to limit test locations to represent specific target areas to avoid data loss.
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