Forcing Temperature Effects on Plant Development for Containerized Blackberry Grown Using Long-Cane Techniques

Abstract

Dormant containerized blackberry plants grown as long canes are forced into protected environments, such as plastic tunnels or greenhouses, to schedule harvesting for important market weeks. The time needed to produce a crop is mainly a function of temperature. In this study, the objectives were to quantify the effects of temperature on plant development rates for long-cane blackberry and develop simple models predicting the time from forcing dormant plants to first open flowers and ripe fruit as a function of average daily temperature (ADT). The crop time and ADT at the first-flower and -fruit stages were measured for the cultivars ‘Loch Ness’, ‘Osage’, ‘Ponca’, and ‘Prime-Ark® 45′ grown as long canes during a greenhouse and high-tunnel experiment, and the days to flowering and fruiting were converted to rates by calculating the reciprocal. Nonlinear models relating flowering and fruiting rates to ADT were developed for each cultivar using a combination of the experimental data and base (6 °C), optimum (25 °C), and maximum (35 °C) temperature parameters derived from a previous blackberry heat unit study. Model accuracy was evaluated by comparing the predicted to observed times to first flower and fruit per cultivar. Average daily temperature was shown to have a main influence on crop timing, as shown by a strongly positive and near 1:1 relationship between predicted and observed days to flowering/fruiting. However, there was significant variability depending on the cultivar and model accuracy within ±7 days, ranging from 50% (‘Prime-Ark® 45) to 90% (‘Loch Ness’) for the flower models and from 60% (‘Prime-Ark® 45) to 100% (‘Loch Ness’) for the fruit models. To the best of our knowledge, this study is the first to characterize the relationship between temperature and crop timing for soilless long-cane blackberry, and it provides a framework for modeling temperature effects on crop timing for these systems. The authors discuss further methods to improve model accuracy and precision for commercial use. These models can also be used for general training purposes to help educate growers on how temperature influences crop scheduling during long-cane blackberry production.