Prediction Models for Frost/Low-Temperature Stress in Subtropical Fruit Plantations
AbstractDuring winters, frost is a phenomenon of common occurrence in subtropical lower Himalayan region. In the recent past, it has caused considerable economic losses to fruit growers. Recommendations for protection against frost do exist, but benefits to orchards are rare due to lack of information on the level of low temperature these crops may experience in a frosty event. Studies have been conducted at Regional Horticultural and Forestry Research Station, Neri, Hamirpur, Himachal Pradesh on development of prediction models for minimum temperature and temperatureevolution during a frost event. Variables like sunset-time temperature, temperature drop and humidity increase from sunset time until two hours, have been found to explain about 74% of the total variation observed in minimum temperature. Evolution of temperature during a frosty night showed that temperature drop after sunset was an inverse exponential function of time after sunset. It justified about 67% of the total variation in temperature-evolution trend. Thiel's inequality coefficient for predicted versus actual values indicated good to very good forecasting performance of the regression lines developed. Further decomposition of inequality into bias, variance and covariance proportions also supported fitness of these lines for future prediction. Based on the information generated, a grower-friendly frost protection guide-chart (S-chart) has been developed. The chart provides information on intensity and duration of temperature below the critical level of damage for different fruit species. It also serves as a guide for the level of protection needed and for automation of protection methods against frost and low temperature damage.
Authors retain copyright. Articles published are made available as open access articles, distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original author and source are credited.
This journal permits and encourages authors to share their submitted versions (preprints), accepted versions (postprints) and/or published versions (publisher versions) freely under the CC BY-NC-SA 4.0 license while providing bibliographic details that credit, if applicable.