Modeling of a photosynthetic crop production index for early warning using NDVI and meteorological data

This paper aims to develop a remote sensing method of monitoring grain production in the early stages of crop growth. It is important to oversee the quantity of grain in production at an early stage in order to raise the alarm well in advance if a poor harvest is looming, especially in view of the rapid population increase in Asia and the long-term squeeze on water resources. Grain production monitoring would allow orderly crisis management to maintain food security in Japan, which is far from producing enough grain for its own population. We propose a photosynthesis-based crop production index CPI that takes into account all of: solar radiation, effective air temperature, vegetation biomass, the effect of temperature on photosynthesis by leaves of grain plants, low-temperature sterility, and high-temperature injury. These later factors, which extend the model of Rasmussen, are significant around the heading period of crops. The proposed photosynthesis-based crop production index CPI has accurately predicted the rice yield expressed by the Japanese Crop Situation Index in three years, including the worst yield in recent years, at a test site in Japan.