Models for predicting pineapple flowering and harvest dates_Production_Article

November 02, 2023 | The Horticulture Journal |

Conducted by the National Agriculture and Food Research Organization (NARO), this study addresses the inadequacies of existing growing-degree-days (GDD) models for predicting flowering and harvest dates in pineapple cultivation, particularly in Japan's diverse climate conditions. While the GDD model has been used previously, its accuracy in Japan's fluctuating temperatures is limited.

To enhance prediction accuracy, the study analyzed extensive phenological data from Japan's primary (Nago) and warmer (Ishigaki) pineapple production regions. It found that the number of days between budding and flowering decreased with air temperatures up to approximately 25°C, leveling off thereafter. Similarly, the days between flowering and harvest decreased until around 23°C, with minimal influence from day length.

The study developed improved models incorporating both GDD and exponential functions, considering upper limit temperatures. These models showed enhanced accuracy, particularly in predicting harvest dates. The exponential function model, reflecting the non-linear relationship between temperature and developmental rate, proved especially effective in forecasting flowering dates.

Overall, the most accurate models achieved root-mean-square errors ranging from 3.7 to 6.1 days for flowering dates and 6.1 to 10.2 days for harvest dates. These findings offer valuable insights for pineapple cultivation management and shipment planning, especially in regions like Japan with wide temperature variations and facing the challenges of climate change.