A Modified Shape Model Incorporating Continuous Accumulated Growing Degree Days for Phenology Detection of Early Rice

Abstract

Using a shape model (SM) is a typical method to determine the phenological phases of crops with long-time-series satellite remote sensing data. The average AGDD-based shape model (AAGDD-SM) takes temperature into account compared to SM, however, the commonly used daily average temperature is not sufficient to determine the exact AGDD owing to the possibly significant changes in temperatures throughout the day. In this paper, a modified shape model was proposed for the better estimation of phenological dates and it is incorporated into the continuous AGDD (CAGDD) which was calculated based on temperatures from a continuous 24 h within a day, different from the calendar day or the average AGDD indicators. In this study, the CAGDD replaced the abscissa of the NDVI growth curve over a 5-year period (2014 to 2018, excluding 2015) for a test site of early rice in Jiangxi province of China. Four key phenological phases, including the reviving, tillering, heading and anthesis phases, were selected and determined with reference to the field-observed phenological data. The results show that compared with the AAGDD-SM, the method proposed in this paper has basically improved the prediction of each phenological period. For those cases where the average temperature is lower than the minimum temperatures (K1) but the effective accumulated temperature is not zero, more accurate AGDD can be calculated according to the method in this paper.

Functional growth analysis of diploid potato varieties (Solanum tuberosum Phureja group)

“…Historically, potato growers have used calendar days and experience to predict key plant developmental stages. However, there may be better indicators than the calendar day to measure the growth situation of crops (Liao et al, 2022). Developing and utilizing the growing degree day system may be a more accurate predictor of these stages throughout the season to determine optimal planting dates and yields compared to calendar days (Worthington and Hutchinson, 2005).…”

“…Developing and utilizing the growing degree day system may be a more accurate predictor of these stages throughout the season to determine optimal planting dates and yields compared to calendar days (Worthington and Hutchinson, 2005). According to the accumulated growing degree days (AGDD) concept, the crops can only continue to grow when a certain accumulative heat is reached for a specific phenological phase (Liao et al, 2022).…”