Although leaf area index (LAI) is a useful index of crop growth, evaluating LAI by destructive sampling is laborious and time-consuming. In the present study, we developed a novel technique to determine rice LAI non-destructively and accurately throughout growth period in paddy field. Near-infrared radiation (NIR) and photosynthetically active radiation (PAR) were measured by a pair of optical sensors inside and outside rice canopy at 1-min intervals. Simple ratio (SR) and NIR to PAR ratio (N/P) were measured depending on growth stage, and the criteria to extract valid SR and N/P that represent LAI accurately were determined. SR and N/P obtained under cloudy conditions were found to represent LAI with high accuracy (R² = 0.91), and seasonal dynamics of canopy growth curves were successfully drawn for two rice cultivars at two experimental fields. Mathematical analysis revealed that not cumulative PAR but cumulative temperature could trigger exponential canopy growth. The present technique can be used as a powerful tool for evaluating, modelling, and phenotyping crop growth characteristics in various rice cultivars as well as other crops.

尽管叶面积指数（LAI）是作物生长的有用指标，但是通过破坏性采样评估LAI既费力又费时。在本研究中，我们开发了一种新技术，可以无损，准确地确定稻田整个生育期的水稻LAI。水稻冠层内部和外部的一对光学传感器以1分钟的间隔测量近红外辐射（NIR）和光合有效辐射（PAR）。根据生长阶段测量简单比率（SR）和NIR与PAR比率（N / P），并确定提取准确代表LAI的有效SR和N / P的标准。发现在多云条件下获得的SR和N / P可以高精度表示LAI（R ²= 0.91），并成功地绘制了两个试验田的两个水稻品种的冠层生长曲线的季节动态。数学分析表明，不是累积的PAR，而是累积的温度可以触发指数冠层生长。本技术可以用作评估，建模和表型化各种水稻品种以及其他作物中作物生长特性的有力工具。