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Agricultural Sciences ; 13(02):105-116, 2022.
Article in English | CAB Abstracts | ID: covidwho-1818486


The aim of the study is to assess the factors that influence the sustainability of agricultural development. The study was carried out in the municipality of Bobonaro for about four months, from July to October 2021. Slovin's method was used to determine the sample size, with a desired percentage of 10% of the total population. Thus, 154 producers were interviewed as respondents and key persons in the area of agriculture. The variables interviewed are the main factors of agricultural productivity and the factors that affect sustainable agricultural development. The results of the descriptive statistical analysis of the data showed that about 94.87% of the respondents' productive area is in operation, with an average of 1.84 ha per respondent and the abandoned area around 0.11 ha per respondent. The average value of rice production is 2.38 ton per ha and corn 1.07 ton per ha. About 87% of producers raised the main types of animals such as cattle, pigs, goats with an average density of 2 to 5 animals per establishment. About 61% of producers have access to the market at a normal price for agricultural products. The factors that hinder less successful agricultural development, such as: those of nature with the greatest impact are climate changes, which influence changes in cultivation sessions and in the characteristics of productive soils, availability of water for irrigation and animal feed. On the socioeconomic side, it includes the willingness or interest of young people who want to work as farmers, less investment and the impact of the Covid-19 pandemic. It is concluded that natural and socioeconomic impacts can reduce agricultural productivity, so that this will be a major challenge for the development of the agricultural sector in the future.

Cell ; 185(6): 1025-1040.e14, 2022 03 17.
Article in English | MEDLINE | ID: covidwho-1649487


During the SARS-CoV-2 pandemic, novel and traditional vaccine strategies have been deployed globally. We investigated whether antibodies stimulated by mRNA vaccination (BNT162b2), including third-dose boosting, differ from those generated by infection or adenoviral (ChAdOx1-S and Gam-COVID-Vac) or inactivated viral (BBIBP-CorV) vaccines. We analyzed human lymph nodes after infection or mRNA vaccination for correlates of serological differences. Antibody breadth against viral variants is lower after infection compared with all vaccines evaluated but improves over several months. Viral variant infection elicits variant-specific antibodies, but prior mRNA vaccination imprints serological responses toward Wuhan-Hu-1 rather than variant antigens. In contrast to disrupted germinal centers (GCs) in lymph nodes during infection, mRNA vaccination stimulates robust GCs containing vaccine mRNA and spike antigen up to 8 weeks postvaccination in some cases. SARS-CoV-2 antibody specificity, breadth, and maturation are affected by imprinting from exposure history and distinct histological and antigenic contexts in infection compared with vaccination.

Antibodies, Viral , BNT162 Vaccine , COVID-19 , Germinal Center , Antigens, Viral , COVID-19/prevention & control , Humans , SARS-CoV-2/genetics , Spike Glycoprotein, Coronavirus , Vaccination