Abstract
Tea trees are the main economic crop in Zhejiang Province. However, spring cold is a frequent occurrence there, causing frost damage to the valuable tea buds. To address this, a regional frost-hazard early-warning system is needed. In this study, frost damage area was estimated based on topography and meteorology, as well as longitude and latitude. Based on support vector machine (SVM) and artificial neural networks (ANNs), a multi-class classification model was proposed to estimate occurrence of regional frost disasters using tea frost cases from 2017. Results of the two models were compared, and optimal parameters were adjusted through multiple iterations. The highest accuracies of the two models were 83.8% and 75%, average accuracies were 79.3% and 71.3%, and Kappa coefficients were 79.1% and 67.37%. The SVM model was selected to establish spatial distribution of spring frost damage to tea trees in Zhejiang Province in 2016. Pearson’s correlation coefficient between prediction results and meteorological yield was 0.79 (p < 0.01), indicating consistency. Finally, the importance of model factors was assessed using sensitivity analysis. Results show that relative humidity and wind speed are key factors influencing accuracy of predictions. This study supports decision-making for hazard prediction and defense for tea trees facing frost.
Highlights
Tea is a traditional drink, with a history that can be traced back 5000 years, and which has profound cultural and economic significance [1]
The overall accuracy of the artificial neural networks (ANNs) model is lower than that of support vector machine (SVM), and it is better than SVM in 0 category classification, but it is not ideal
The same as SVM is that the recognition accuracy of Categories 3 and 4 is high, which is related to the large number of training samples
Summary
Tea is a traditional drink, with a history that can be traced back 5000 years, and which has profound cultural and economic significance [1]. Tea plants are a type of warm-leaf plant. The shrub-type tea plants in the middle and lower reaches of the Yangtze River in China maintain a good growth state in 25–30 ◦C, and the sprout temperature of tea plants is 6–12 ◦C [2,3]. As the temperature rises in the early spring, the cold-resistant ability of tea trees decreases after the sprouting of tea buds, which can be damaged by freezing if the temperature drops sharply to below 0 ◦C. Frost disasters cause destruction of the tea protoplasm when the water in tea-leaf cells freezes, and this reduces tea yield [4]. Frost damage to the tea bud affects the quality and taste of tea, and stops the germination of tea buds, causes bud death, and delays the picking period for spring tea [5,6]
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