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The 'Huangguan' pear is one of the high-quality pear cultivars produced in China. However, the bagged fruit of the 'Huangguan' pear often suffers from peel browning spots after rain during their mature period. In this study, in an effort to discover the impact of bagging treatments on the occurrence of peel browning spots and fruit quality, fruits were covered by single-layer, two-layer, or triple-layer paper bags six weeks after reaching full bloom. The results showed that the bagged fruits were characterized by smooth surfaces and reduced lenticels compared with the unbagged ones. The unbagged and the two-layer bagged fruits had yellow/green peels, while the single- and triple-layer bagged ones had yellow/white peels. Compared with the unbagged fruits, the bagged fruits had higher vitamin C (Vc) contents and values of peel color indexes L and a and lower soluble solid contents (SSCs), titratable acid (TA) contents, absorbance index differences (IAD), and b values. Additionally, the triple-layer bagged group was superior to other groups in terms of fruit quality, but it also had the maximum incidence of peel browning spots. Before and after the appearance of peel browning spots, the bagged fruits had smoother and thinner cuticles compared with the unbagged ones. Furthermore, the triple-layer bagged fruits had minimum lignin contents and maximum phenolic contents in their peels, with minimum activity of lignin synthesis-related enzymes such as phenylalanine ammonia lyase (PAL), peroxidase (POD), and polyphenol oxidase (PPO), as well as minimum expressions of relevant genes such as cinnamyl alcohol dehydrogenase (CAD), cinnamoyl CoA reductase (CCR), 4-coumarate: coenzyme A ligase (4CL6), and cinnamate 4-hydroxylase (C4H1). It was deduced that POD activity and the relative expressions of CAD9, CCR3, CCR4, and CCR5 may play key roles in the occurrence of peel browning spots. In summary, lignin synthesis affected the incidence of peel browning spots in bagged 'Huangguan' pears. This study provides a theoretical basis for understanding the incidence of peel browning spots in 'Huangguan' pears. [ABSTRACT FROM AUTHOR]

Photovoltaic power generation prediction constitutes a significant research area within the realm of power system artificial intelligence. Accurate prediction of future photovoltaic output is imperative for the optimal dispatchment and secure operation of the power grid. This study introduces a photovoltaic prediction model, termed ICEEMDAN-Bagging-XGBoost, aimed at enhancing the accuracy of photovoltaic power generation predictions. In this paper, the original photovoltaic power data initially undergo decomposition utilizing the Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (ICEEMDAN) algorithm, with each intrinsic mode function (IMF) derived from this decomposition subsequently reconstructed into high-frequency, medium-frequency, and low-frequency components. Targeting the high-frequency and medium-frequency components of photovoltaic power, a limiting gradient boosting tree (XGBoost) is employed as the foundational learner in the Bagging parallel ensemble learning method, with the incorporation of a sparrow search algorithm (SSA) to refine the hyperparameters of XGBoost, thereby facilitating more nuanced tracking of the changes in the photovoltaic power's high-frequency and medium-frequency components. Regarding the low-frequency components, XGBoost-Linear is utilized to enable rapid and precise prediction. In contrast with the conventional superposition reconstruction approach, this study employs XGBoost for the reconstruction of the prediction output's high-frequency, intermediate-frequency, and low-frequency components. Ultimately, the efficacy of the proposed methodology is substantiated by the empirical operation data from a photovoltaic power station in Hebei Province, China. Relative to integrated and traditional single models, this paper's model exhibits a markedly enhanced prediction accuracy, thereby offering greater applicational value in scenarios involving short-term photovoltaic power prediction. [ABSTRACT FROM AUTHOR]

Landslide hazards have attracted increasing public attention over the past decades due to a series of catastrophic consequences of landslide occurrence. Thus, the mitigation and prevention of landslide hazards have been the topical issues. Thereinto, numerous research achievements on landslide susceptibility assessment have been springing up in recent years. In this paper, four benchmark models including best-first decision tree (BFTree), functional tree, support vector machine and classification regression tree (CART) and were integrated with bagging strategy. Then, these bagging-based models were applied to map regional landslide susceptibility in Jiange County, Sichuan Province, China. Fifteen conditioning factors were employed in establishing landslide susceptibility models, respectively, slope aspect, slope angle, elevation, plan curvature, profile curvature, TWI, SPI, STI, lithology, soil, land use, NDVI, distance to rivers, distance to roads and distance to lineaments. Then utilize correlation attribute evaluation method to weigh the contribution of each factor. Finally, the comprehensive performance of various bagging-based models and corresponding benchmark models was evaluated and systematically compared applying receiver operating characteristic curve and area under curve (AUC) values. Results demonstrated that bagging-based ensemble models significantly outperformed their corresponding benchmark models with validation dataset. Among them the Bag-CART model has the highest AUC value of 0.874; however, the AUC value of CART model is only 0.766, which reflected satisfying predictive capacity of integrated models in some degree. The achievements obtained in this study have some reference values for landslides prevention and land resource planning in Jiange County. [ABSTRACT FROM AUTHOR]

[Objective] The present paper aimed to explore the effects of different types of fruit bags on the formation of fruit quality and the change of peel pigment of Qiumitao No. 1, so as to provide reference for the high-quality production of Qiumitao No. 1 in southern China. [Method] Taking the fruit of Qiumitao No. 1 as the experimental material, four different types of fruit bags (yellow outside and black inside, single yellow bag, single white bag, single semi white translucent bag) were bagged after the first physiological fruit drop. The changes of pigment content in single fruit weight, vertical and horizontal diameters, fruit size, peel pigment, and pulp glyc acid content and relative enzyme activities were measured and analyzed every 7 days (5 times), before plucking fruit, and the change rule was analyzed. [Result] The results showed that the surface of fruit covered with yellow outside and black inside double-layer bag was smooth, the chlorophyll content was significantly lower than that of single-layer bag and showing white jade color (P < 0. OS, the same as below), the longitudinal diameter, transverse diameter and single fruit weight were higher than those of the other three treatments, and the content of quinic acid, malic acid, sucrose, sorbitol and total sugar of fruit covered with yellow outside and black inside double-layer bag were significantly lower than those of other single-layer bag treatments, which match with the light taste at maturity. Among the three single-layer bags, the yellow singlelayer bag had higher sucrose and fructose content, lower citric acid and quinic acid content, the highest total sugar content, the lowest total acid content and the highest sugar acid ratio. The results of correlation analysis showed that there was no significant correlation between the acid invertase activity and neutral invertase activity with sucrose content at late stage of fruit development (P > 0. OS). [Conclusion] Qiumitao No. 1 bagged with double-layer yellow outside and black inside has low pigment content and beautiful appearance, but the content of sugar and acid was lower, and the taste was lighter; the peel pigment content of Qiumitao No. 1 bagged with single-layer yellow fruit bag was higher than that of double-layer bag, and the fruit appearance was green and dull, but the content of sugar and acid in the fruit was higher than that of other bagged fruits. In production and markting, the type of fruit bag can be selected according to the needs of sales, which can improve the overall economic benefits. [ABSTRACT FROM AUTHOR]