Abstract

Predictions of future crop growth and yield under a changing climate require a precise knowledge of plant responses to their environment. Since leaf growth increases the photosynthesizing area of the plant, it occupies a central position during the vegetative phase. Rice is cultivated in diverse ecological zones largely differing in temperature and relative air humidity (RH). To investigate the effects of temperature and RH during day and night on leaf growth, one variety (IR64) was grown in a growth chamber using 9 day/night regimes around the same mean temperature and RH, which were combinations of 3 temperature treatments (30/20 °C, 25/25 °C, 20/30 °C day/night temperature) and 3 RH treatments (40/90%, 65/65%, 90/40% day/night RH). Day/night leaf elongation rates (LER) were measured and compared to leaf gas exchange measurements and leaf area expansion on the plant level. While daytime LER was mainly temperature-dependent, nighttime LER was equally affected by temperature and RH and closely correlated with leaf area expansion at the plant level. We hypothesize that the same parameters increasing LER during the night also enhance leaf area expansion via shifts in partitioning to larger and thinner leaves. Further, base temperatures estimated from LERs varied with RH, emphasizing the need to take RH into consideration when modeling crop growth in response to temperature.

Highlights

  • Plant growth and its responses to the abiotic environment have probably been studied since humans first began to cultivate land

  • Daytime leaf elongation rates (LER) was closely correlated with daytime temperature, which had a much larger effect on LER than relative air humidity (RH)

  • In pressure chamber experiments using salt-treated barley, only daytime LER could be increased, as a result it has been argued that LER was controlled by the plant’s water status during the day, but not during the night [12]

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Summary

Introduction

Plant growth and its responses to the abiotic environment have probably been studied since humans first began to cultivate land. The difficulty arises when different plant processes respond differently to the abiotic environment, and this complexity can only be handled by models, which partly rely on assumptions. Abiotic factors, such as temperature, soil water availability, solar radiation, air humidity and wind, do not affect plants individually, but act in concert. A well-known example is the temperature response of photosynthesis which varies with incident light intensity and CO2 concentration [1]. For greater insight into this complexity, innovative and creative experiments are required which can contribute to model improvements for better predictions of crop responses in climate change scenarios

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