Journal of Integrative Agriculture (Mar 2024)

Rice canopy temperature is affected by nitrogen fertilizer

  • Min Jiang,
  • Zhang Chen,
  • Yuan Li,
  • Xiaomin Huang,
  • Lifen Huang,
  • Zhongyang Huo

Journal volume & issue
Vol. 23, no. 3
pp. 824 – 835

Abstract

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Canopy temperature strongly influences crop yield formation and is closely related to plant physiological traits. However, the effects of nitrogen treatment on canopy temperature and rice growth have yet to be comprehensively examined. We conducted a two-year field experiment with three rice varieties (HD-5, NJ-9108, and YJ-805) and three nitrogen treatments (zero-N control (CK), 200 kg ha−1 (MN), and 300 kg ha−1 (HN)). We measured canopy temperature using a drone equipped with a high-precision camera at the six stages of the growth period. Generally, canopy temperature was significantly higher for CK than for MN and HN during the tillering, jointing, booting, and heading stages. The temperature was not significantly different among the nitrogen treatments between the milky and waxy stages. The canopy temperature of different rice varieties was found to follow the order: HD-5>NJ-9108>YJ-805, but the difference was not significant. The canopy temperature of rice was mainly related to plant traits, such as shoot fresh weight (correlation coefficient r=–0.895), plant water content (–0.912), net photosynthesis (–0.84), stomatal conductance (–0.91), transpiration rate (–0.90), and leaf stomatal area (–0.83). A structural equation model (SEM) showed that nitrogen fertilizer was an important factor affecting the rice canopy temperature. Our study revealed: (1) A suite of plant traits was associated with the nitrogen effects on canopy temperature, (2) the heading stage was the best time to observe rice canopy temperature, and (3) at that stage, canopy temperature was negatively correlated with rice yield, panicle number, and grain number per panicle. This study suggests that canopy temperature can be a convenient and accurate indicator of rice growth and yield prediction.

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