Journal of Agriculture and Forestry is an international, peer-reviewed open access journal dedicated to advancing research the field of agricultural and forestry sciences. The journal provides a rapid publication process to ensure wide dissemination of high-quality articles to scientists, professionals, and interested individuals worldwide. Our goal is to serve as an efficient, reliable, and trusted platform for scholars and readers, publishing cutting-edge research in the field.
Abstract: Topping is a key technical measure in cotton production, which directly affects yield and quality of cotton. Taking the cotton variety Tahe-2, the main cotton variety of the eighth Regiment of the First Division of the Corps, as the research object, three topping time treatments (T1, T2, T3) and one CK treatment were set to analyze the influence of the growth and yield of cotton Tahe-2 on different topping time, so as to determine the appropriate topping time and technology in this region. The results showed that with the delay of topping time, the number of fruit branches increased by 0.97, the height of plant and the height of fruit branches increased in 5.82cm, 2.16cm, respectively; the average length of fruit branches and the average degree of three nodes decreased in 3.88cm, 6.37cm, respectively; and the length of internode first increased and then decreased. The number of bolls in the lower part was the largest, accounting for 44.0%, while that in the middle and upper part was close, accounting for 32.9%, 23.1%, respectively. The number of inner ring bolls was the largest, accounting for 81.33-88.61%. The number of peripheral ring bolls wasrelatively small, accounting for 11.39-18.67%. The overall production showed a trend of first increase and then decrease, and the production of T2 treatment was the highest, reaching 6849.15 kg/hm2, and the yield Tahe 2 peaked around July 1. Therefore, timely and early topping can effectively improve cotton plant type, control apex dominance, promote reproductive growth and rational nutrient distribution, increase boll setting rate and boll weight, so as to achieve early maturity, high yield and stable yield.Abstract: Topping is a key technical measure in cotton production, which directly affects yield and quality of cotton. Taking the cotton variety Tahe-2, the main cotton variety of the eighth Regiment of the First Division of the Corps, as the research object, three topping time treatments (T1, T2, T3) and one CK treatment were set to analyze the influence of...Learn More
Abstract: Forest fires represent a global environmental issue, posing severe threats to ecosystems, economic development, and social security. Accurate prediction of forest fires is crucial for formulating effective preventive measures and minimizing the associated losses. With the advancement of machine learning technologies, their application in forest fire risk prediction has become an emerging research focus. Diverse machine learning algorithms exhibit varying data processing capabilities and predictive accuracies; hence, comparing and selecting the most suitable algorithms is significant for enhancing the performance of predictive models. This study analyzed meteorological data and corresponding fire severity information from Guangxi Province between 1990 and 2019, employing 10 machine learning algorithms in experiments. Initial data preprocessing, including handling of missing and outlier values, ensured data quality. Subsequently, predictive performance across algorithms was assessed using accuracy, precision, recall, F1 score, and the Receiver Operating Characteristic (ROC) curve. To further examine the stability and robustness of the models, a 5-fold cross-validation was implemented. Results indicated that SVM, Bayesian classifiers, BP neural networks, logistic regression, AdaBoost, Gradient Boost, and XGBoost demonstrated superior performance in terms of AUC, while KNN and Random Forest algorithms showed advantages in precision and accuracy. The 5-fold cross-validation confirmed the stability and robustness of the models, revealing that most models maintained stable predictive performance across different datasets. The study suggests that integrating multiple algorithms can improve the accuracy and reliability of predictions and recommends that future research consider additional influencing factors and employ deep learning techniques to further enhance predictive performance.Abstract: Forest fires represent a global environmental issue, posing severe threats to ecosystems, economic development, and social security. Accurate prediction of forest fires is crucial for formulating effective preventive measures and minimizing the associated losses. With the advancement of machine learning technologies, their application in forest fir...Learn More
Abstract: Inspired by farmers' practice of boiling tobacco stems and rosin together to create a biopesticide for controlling pests and diseases, the author has developed a drug specifically for controlling tea scale insects. This drug was invented after more than a decade of experimental research, addressing the urgent need for effective treatment against the widespread and severe infestation of scale insects in tea and fruit crops. The drug is made by mixing 2.5Kg-3.0Kg of tobacco stems and leaves with 0.1-0.3Kg of pine resin (commonly known as rosin) in 86-90Kg of a 32% sodium hydroxide solution. After boiling for 1-2 hours, the mixture is filtered, and the filtrate is centrifuged and separated into upper and lower layers. Phosphoric acid is then added to both layers to adjust the pH of the upper layer to 7, and soap is added for emulsification to obtain solution A. The pH of the lower layer is adjusted to 11, and potassium dihydrogen phosphate is added for activation to obtain solution B. When used, equal volumes of solutions A and B are mixed to create an emulsion oil with a concentration of 25%. Because the main ingredients are phosphoric acid (Pinyin initial L) and rosin (Pinyin initial S), it is named 25% LS emulsion oil. When applying, solutions A and B are mixed with water in a volume ratio of 1:1:80-120. The mixture is prepared and used immediately, and applied to the target area through atomization. Field trials comparing this invention with the commonly used pesticide Youlede for controlling scale insects have shown that spraying 25% LS emulsion oil can achieve a control effect of 90.5-98% against scale insects before they reach the third instar stage, significantly higher than other pesticides and the control effect of the control group. Acute toxicity tests on rats and mice conducted by the Sichuan Institute for Drug Control and the former West China University of Medical Sciences, as well as tests on the irritation of rabbit skin and eyes, have demonstrated that this invention is a low-toxicity pesticide. Furthermore, the pesticide residue and heavy metal content in tea leaves after application are both in compliance with the National "Tea Hygiene Standards" GB9679-88 of the People's Republic of China, indicating that it is a low-residue pesticide. The application of this drug can save direct economic losses of 600-1000 yuan per mu of tea garden (or orchard). The invention has been filed with the State Intellectual Property Office of the People's Republic of China and has obtained a national invention patent (authorization number: ZL200610054191.5).Abstract: Inspired by farmers' practice of boiling tobacco stems and rosin together to create a biopesticide for controlling pests and diseases, the author has developed a drug specifically for controlling tea scale insects. This drug was invented after more than a decade of experimental research, addressing the urgent need for effective treatment against th...Learn More
