Large citrus areas in Tamaulipas are affected by Anastrepha ludens (Loew) populations. Here we report the findings of a spatio-temporal analysis of A. ludens on an extended citrus area from 2008-2011 aimed at analyzing the probabilities of A. ludens infestation and developing an infestation risk classification for citrus production. A Geographic Information System combined with the indicator kriging geostatistics technique was used to assess A. ludens adult densities in the spring and fall. During the spring, our models predicted higher probabilities of infestation in the western region, close to the Sierra Madre Oriental, than in the east. Although a patchy distribution of probabilities was observed in the fall, there was a trend toward higher probabilities of infestation in the west than east. The final raster models summarized the probability maps using a three-tiered infestation risk classification (low-, medium-, and high risk). These models confirmed the greater infestation risk in the west in both seasons. These risk classification data support arguments for the use of the sterile insect technique and biological control in this extended citrus area and will have practical implications for the area-wide integrated pest management carried out by the National Program Against Fruit Flies in Tamaulipas, Mexico.
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http://dx.doi.org/10.1093/jee/tov134 | DOI Listing |
Front Plant Sci
January 2025
Information and Communication Engineering, Yeungnam University, Gyeongsan, Republic of Korea.
Smart farming is a hot research area for experts globally to fulfill the soaring demand for food. Automated approaches, based on convolutional neural networks (CNN), for crop disease identification, weed classification, and monitoring have substantially helped increase crop yields. Plant diseases and pests are posing a significant danger to the health of plants, thus causing a reduction in crop production.
View Article and Find Full Text PDFFront Immunol
January 2025
Key Laboratory of Longevity and Aging-related Diseases of Chinese Ministry of Education, Guangxi Medical University, Nanning, China.
Background: () infection is a significant risk factor for hepatocellular carcinoma (HCC), yet its underlying mechanisms remain poorly understood. This study aimed to investigate the impact of infection on the serum proteomic and metabolomic profiling of HCC patients, focusing on the potential mechanisms.
Method: A retrospective clinical analysis was conducted on 1121 HCC patients, comparing those with and without infection.
Front Cell Infect Microbiol
January 2025
College of Veterinary Medicine, Henan Agricultural University, Zhengzhou, China.
Background: Sheep coccidiosis could disturb the balance of intestinal microbiota, causing diarrhea, and even death in lambs. Chemical drugs are the primary method of treating sheep coccidiosis, but their use will bring drug resistance, toxic side effects, drug residues, and other problems. Chinese herbal medicines are investigated as alternative methods for controlling coccidian infections.
View Article and Find Full Text PDFZhongguo Xue Xi Chong Bing Fang Zhi Za Zhi
July 2024
Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China.
Objective: To investigate the prevalence of parasitic infections in market-sold aquatic products in Shanghai Municipality, and to understand the knowledge and practice towards food-borne parasitic diseases among residents, so as to provide insights into the surveillance and control of food-borne parasitic diseases.
Methods: Freshwater products, seawater products and pickled products were randomly obtained from agricultural trade markets, supermarkets, retail stores and restaurants in Huangpu, Putuo, Minhang and Qingpu districts of Shanghai Municipality from 2020 to 2023. Parasite metacercariae and larvae were detected in these aquatic products using pressing method, digestion method and the dissection method, and the detection of parasitic infection was compared in different types of aquatic products.
Zhongguo Xue Xi Chong Bing Fang Zhi Za Zhi
June 2024
Anqing Municipal Institute of Schistosomiasis Control, Anqing, Anhui 246001, China.
Objective: To investigate the distribution of snails in different water systems in Anqing City from 2016 to 2022, so as to provide insights into snail control in the city.
Methods: Snail survey data and distribution of water systems in snail-infested environments were collected from schistosomiasis-endemic areas of Anqing City from 2016 to 2022. The vector maps of towns and water systems in Anqing City were downloaded from National Geomatics Center of China.
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