Rice Yield Estimation Based on an NPP Model With a Changing Harvest Index

Abstract

Paddy rice is one of the most widely planted crops in Asia. Yield estimation of paddy rice is crucial to food security. Gross primary productivity or net primary productivity (NPP) models are some of the most commonly used methods for crop yield estimation as they have a theoretical basis and are simple to use. The harvest index (HI) of paddy rice, one of the input parameters in yield estimation models, has been increasingly used with the improvement of paddy rice cultivars over the past four decades. However, in many previous researches, this parameter was arbitrarily determined to fit the observed yield data values, without considering its changing trend. In the present study, we developed an NPP-based rice yield estimation model with HI being a changing parameter. The accuracy of the proposed method is tested over the Jiangsu Province, Southeast China. The results showed that the rice HI increases linearly in study area. Compared with yield estimation with a fixed HI, yield estimations using a changing HI are greatly improved, with the average estimation accuracy greater than 96%, and the relative errors within ±5%. The results proved that the NPP-based yield estimation model with a changing HI can be a promising alternative for rice yield estimation. Index Terms-Gross primary productivity (GPP), harvest index (HI), net primary productivity (NPP), paddy rice yield estimation, rectangular hyperbolic model. I. INTRODUCTION T HE global human population is estimated to reach 9.7 billion by the year 2050 [1] and this makes the availability of the rice grain extremely important for food security. A range of factors, including sharp increase of population, decline in arable area, water pollution and water resource shortage, environmental pollution and global climate change, significantly affects agricultural production and threatens grain security [2]. Grain security has become a tremendous challenge in many countries and regions. Paddy rice is one of the most important and widely planted crops in the world, especially in Asia [3], providing an half of mankind's calories. More than 65% Chinese Manuscript

Increased Grain Crop Production Intensifies the Water Crisis in Northern China

“…For rice, the average HI varied from 0.14 to 0.43, with higher values concentrated in eastern China. The HI values for the three staple crops were within the ranges reported in the literature (M. He et al., 2018; Marshall et al., 2018; Reeves et al., 2005; F. Wang et al., 2020), indicating that our results are valid and reliable. The average HI values for each crop type were then assigned to each 0.0125° grid cell within each province to estimate the gridded yield.…”

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“…Satellite remote sensing can overcome the limitations of ground-based single-point measurements, helping to expand observations from fixed points to regional scales [17]. Remote sensing data, characterized by long time series and wide coverage, has become an essential means for estimating the spatiotemporal characteristics and driving mechanisms of global vegetation NPP through top-down research methods based on remote sensing data inversion [17]. Currently, both domestically and internationally, the monitoring of large-scale vegetation NPP relies mainly on remote sensing interpretation estimates [18].…”