天蓬
穗
水稻
播种
产量(工程)
空气温度
农学
园艺
植物
数学
化学
生物
材料科学
大气科学
物理
生物化学
冶金
基因
作者
Ziwei Li,Lei Huang,Huo ZhongYang,Min Jiang
出处
期刊:Phyton-international Journal of Experimental Botany
日期:2023-01-01
卷期号:92 (11): 2999-3019
标识
DOI:10.32604/phyton.2023.030627
摘要
The canopy temperature of rice is an important index that directly reflects the growth and physiological state of rice, and affects the yield of rice plants to a great extent. The correlation between the temperatures of different rice organs and canopy in different growth stages and the grain yield is complex. The stability and universality of these correlations must be verified. We conducted a pot experiment using two rice varieties and two temperature treatments (high temperature treatment was carried out at the beginning of heading stage for 10 days). We measured rice organ temperature during seven stages of growth using a high-precision infrared thermal imager. Results showed that the optimal observation period for the rice canopy temperature was 13:00. Although the rice variety did not significantly impact the canopy or organ temperature (p > 0.05), the different organs and canopy exhibited significantly different temperatures (p < 0.05). The correlations between the leaf, stem, panicle, canopy–air temperature differences and seed setting rate, theoretical and actual yields were the strongest during the milk stage. Among them, the correlation coefficient between ΔTs and theoretical and actual yields was the highest, the relationship between theoretical yield (Y) and ΔTs (X) was Y = −5.6965X + 27.778, R2 = 0.9155. Compared with ΔTl, ΔTp and ΔTc, ΔTs was closely related to the main traits of plants. ΔTs could better reflect the growth characteristics of rice than ΔTc, such as dry matter accumulation (r = −0.931), SPAD (r = 0.699), N concentration (r = 0.714), transpiration rate (r = −0.722). In conclusion, stem temperature was more important indicator than canopy temperature. Stem temperature is a better screening index for rice breeding and cultivation management in the future.
科研通智能强力驱动
Strongly Powered by AbleSci AI