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Agriculture is one of the most important activities that produces crop and food that is crucial for the sustenance of a human being. In the present day, agricultural products and crops are not only used for local demand, but globalization has allowed us to export produce to other countries and import from other countries. India is an agricultural nation and depends a lot on its agricultural activities. Prediction of crop production and yield is a necessary activity that allows farmers to estimate storage, optimize resources, increase efficiency and decrease costs. However, farmers usually predict crops based on the region, soil, weather conditions and the crop itself based on experience and estimates which may not be very accurate especially with the constantly changing and unpredictable climactic conditions of the present day. To solve this problem, we aim to predict the production and yield of various crops such as rice, sorghum, cotton, sugarcane and rabi using Machine Learning (ML) models. We train these models with the weather, soil and crop data to predict future crop production and yields of these crops. We have compiled a dataset of attributes that impact crop production and yield from specific states in India and performed a comprehensive study of the performance of various ML Regression Models in predicting crop production and yield. The results indicated that the Extra Trees Regressor achieved the highest performance among the models examined. It attained a R-Squared score of 0.9615 and showed lowest Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) of 21.06 and 33.99. Following closely behind are the Random Forest Regressor and LGBM Regressor, achieving R-Squared scores of 0.9437 and 0.9398 respectively. Moreover, additional analysis revealed that tree-based models, showing a R-Squared score of 0.9353, demonstrate better performance compared to linear and neighbors-based models, which achieved R-Squared scores of 0.8568 and 0.9002 respectively. [ABSTRACT FROM AUTHOR]

In tropical areas, the simultaneous transmission of multiple vector-borne diseases is common due to ecological factors shared by arthropod vectors. Malaria and dengue virus, transmitted by Anopheles and Aedes mosquitoes, respectively, are among the top vector-borne diseases that cause significant morbidity and mortality in endemic areas. Notably, tropical areas often have suitable conditions for the co-existence of these mosquito species, highlighting the importance of identifying markers that accurately indicate the risk of acquiring each specific disease entity. Aedes are daytime-biting mosquitoes, while Anopheles preferentially bite during the night. These biting patterns raise the possibility of concurrent exposure to bites from both species. This is important because mosquito saliva, deposited in the skin during blood feeding, induces immune responses that modulate pathogen establishment and infection. Previous studies have focused on characterizing such effects on the vector–pathogen interface for an individual pathogen and its mosquito vector. In this study, we evaluated associations between immune responses to salivary proteins from non-dengue and non-malaria vector mosquito species with clinical characteristics of malaria and dengue, respectively. Surprisingly, antibody responses against Anopheles antigens in dengue patients correlated with red blood cell count and hematocrit, while antibody responses against Aedes proteins were associated with platelet count in malaria patients. Our data indicate that concurrent exposure to multiple disease-carrying mosquito vectors and their salivary proteins with differing immunomodulatory properties could influence the transmission, pathogenesis, and clinical presentation of malaria, dengue fever, and other vector-borne illnesses. [ABSTRACT FROM AUTHOR]

This study was aimed at determining the prevalence estimate and association of transfusion-transmitted infections (TTIs) with ABO and Rh blood groups among blood donors at the King Faisal Specialist Hospital and Research Center (KFSH & RC) in the western region of Saudi Arabia. A retrospective study was conducted at the blood bank center of KFSH and RC from 1 January 2013 to 31 December 2019. Data on ABO and Rh blood group testing, serological testing, molecular investigations, serological assays, nucleic acid testing (NATs), and socio-demographic information were gathered. During the study period, there were 959,431 blood donors at the KFSH and RC. The overall 7-year cumulative prevalence estimate of blood transfusion-transmitted infections among blood donors was low at 7.93%, with an average prevalence estimate of 0.66%. Donors with the O blood group, the O RhD +ve blood group, in particular, were more at risk of developing TTIs, whereas donors with the AB blood group, the AB RhD −ve blood group, in particular, were at the lowest risk of developing TTIs. In total, 96.9% of the blood donors were males (n = 916,567). Almost half of the blood donors belong to the O blood group (49.4%). A total of 861,279 (91.0%) donors were found to be RhD positive. The percentages of TTIs were found to be higher in RhD +ve donors compared with RhD −ve donors. The prevalence estimate of the hemoglobin C (HbC) infection was the most common TTI among the blood donors being 3.97%, followed by malaria being 2.21%. The least prevalence estimate of TTI in the present study was for NAT HIV being 0.02%. Significant associations were observed between RhD +ve and RhD −ve among the malaria-infected donors (A: χ2 = 26.618, p = 0.001; AB: χ2 = 23.540, p = 0.001; B: χ2 = 5.419, p = 0.020; O: χ2 = 68.701, p = 0.001). The current 7-year retrospective study showed a low level of TTIs among blood donors. However, we urge that more research encompassing the entire country be conducted in order to obtain more representative results in terms of the prevalence estimate and association of transfusion-transmitted infections with ABO and Rh blood groups in communities. [ABSTRACT FROM AUTHOR]

The objective of this work was to evaluate the effectiveness of ozone in the control of fungi and the degradation of fumonisins in maize and possible effects on the chemical composition of the product. Two cultivars of hybrid maize (30F53H and AS1581 PRO) were used. Initially, the saturation process of the porous medium with ozone was studied. The incidence of Fusarium verticillioides, Penicillium spp. and Aspergillus flavus; the suitability of ozone to detoxify grains contaminated by fumonisins and possible qualitative changes in the product were evaluated. Ozone was applied at an inlet ozone concentration of 13.5 mg L−1 and flow rate of 1.0 L min−1, in five exposure periods (0, 12, 24, 36, 48 and 60 h). The estimated daily intake of FB by horses from grains subjected to ozonation was obtained. For the hybrid AS1581PRO, the estimated saturation time and concentration were equivalent to 67.34 min and 5.91 mg L−1, respectively. With regard to the hybrid 30F53H, the saturation time and concentration were 41.74 min and 8.72 mg L−1, respectively. Ozone was an effective fungicidal agent. The use of a concentration of 13.5 mg L−1 over a 24 h-treatment led to a reduction of 81.2 and 86.2% in the concentrations of fumonisin B1 and fumonisin B2, respectively. The estimated daily intake of fumonisins was reduced to 17.21 µg kg−1BW per day, corresponding to half of the acceptable daily intake for equines. Ozone did not affect the chemical composition of the grain. Ozone is effective in controlling fungi and as a detoxifying agent in maize contaminated by fumonisins. [ABSTRACT FROM AUTHOR]