Yedan He

1 Hangzhou Fuyang Aizi Fresh Peach Professional Cooperative, Hangzhou 311404, Zhejiang, China
2 Zhejiang Agronomist College, Hangzhou 310021, Zhejiang, China
Author    Correspondence author
Computational Molecular Biology, 2026, Vol. 16, No. 3   
Received: 09 Apr., 2026    Accepted: 14 May, 2026    Published: 29 May, 2026

This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Peach production is highly sensitive to variations in air temperature; as a critical climatic factor, temperature plays a pivotal role in the phenological development of peach trees, yield formation, and the regulation of fruit quality. Focusing on the mechanisms by which temperature influences peach yield and quality, this paper systematically analyzes its regulatory effects across different growth stages—specifically, the temperature response characteristics observed during bud break and flowering, fruit development, and the ripening process. Building upon this foundation, and by integrating meteorological data with orchard production records, a predictive model for peach yield and quality based on temperature indicators was constructed. This model places particular emphasis on incorporating variables such as accumulated temperature, extreme heat events, and seasonal temperature fluctuations, while employing a hybrid approach that combines statistical analysis with machine learning techniques for modeling and optimization. Through model performance evaluation and sensitivity analysis, key temperature thresholds and dominant factors influencing yield and quality were identified, thereby further elucidating the mechanisms by which heat stress and low-temperature impacts contribute to yield loss and quality deterioration. Case studies demonstrate that the developed model effectively predicts regional trends in peach yield and quality, exhibiting high applicability and stability. The findings of this study provide a theoretical basis for orchard temperature management, variety selection, and disaster risk management; furthermore, they offer technical support for the advancement of precision agriculture and intelligent decision-support systems, holding significant implications for enhancing the climate adaptability and production efficiency of the peach industry.

Peach yield prediction; Temperature stress; Fruit quality modeling; Growing degree days; Precision agriculture