ABSTRACT
ABSTRACT Water catchment to subsidize agricultural activities is estimated at 70% of world consumption. In the western region of Bahia, the main agricultural center of the state, there is intensive use of water for the production of agricultural commodities. In regions with high water demand, quantification of the use of this resource can be performed using anthropic pressure indicators, such as the Water Footprint. Thus, this work determined the Water Footprint of the soybean, cotton, and corn crops produced in the western region of Bahia State. In order to determine the Water Footprint, data of the environmental characteristics and crop production in the region were used, were obtained from different Brazilian public and private institutions. The calculation of Water Footprint of the crops was performed by the sum of the green, blue, and gray components. The average Water Footprint between 2012 and 2017 for soybean corresponded to 1,972.3 m3 t-1, with cotton at 1,825.2 m3 t-1, and corn 512.4 m3 t-1. The analyses of the results and the comparison with the values of the Water Footprint of other regions demonstrate that the edaphoclimatic conditions of the western region of Bahia are propitious to the development of these crops.
RESUMO A captação de água doce para subsidiar as atividades agrícolas é estimada em 70% do consumo mundial. Na região oeste da Bahia, maior polo agrícola do estado, verifica-se o uso intensivo de água para a produção de commodities agrícolas. Em regiões com elevada demanda de água, a quantificação do uso desse recurso pode ser realizada utilizando indicadores da pressão antrópica, como a Pegada Hídrica. Deste modo, este trabalho determinou as Pegadas Hídricas das culturas de soja, algodão e milho produzidas na região oeste do Estado da Bahia. A fim de se determinar a Pegada Hídrica foram utilizados dados das características ambientais e de produção das culturas na região, os quais foram obtidos de diferentes instituições públicas e privadas do país. O cálculo das Pegadas Hídricas das culturas foi realizado pela soma das componentes verde, azul e cinza. A Pegada Hídrica média entre 2012 e 2017 para a soja correspondeu a 1.972,3 m3 t-1, sendo a do algodão de 1.825,2 m3 t-1 e a do milho de 512,4 m3 t-1. Na análise dos resultados obtidos e na comparação com os valores de Pegada Hídrica de outras regiões, demonstrou-se que as condições edafoclimáticas da região oeste da Bahia são propícias ao desenvolvimento dessas culturas.
ABSTRACT
The natural increase of the world's population implies boosting agricultural demand. In the current non-optimistic global scenario, where adverse climate changes come associated with substantial population growth, the main challenge in agribusiness is food security. Recently, the CRISPR/Cas system has emerged as a friendly gene editing biotechnological tool, enabling a precise manipulation of genomes and enhancement of desirable traits in several organisms. This review highlights the CRISPR/Cas system as a paramount tool for the improvement of agribusiness products and brings up-to-date findings showing its potential applications in improving agricultural-related traits in major plant crops and farm animals, all representing economic-relevant commodities responsible for feeding the world. Several applied pieces of research have successfully demonstrated the CRISPR/Cas ability in boosting interesting traits in agribusiness products, including animal productivity and welfare, crop yield growth, and seed quality, reflecting positive impacts in both socioeconomics and human health aspects. Hence, the CRISPR/Cas system has revolutionized bioscience and biotechnology, and its concrete application in agribusiness goods is on the horizon.
Subject(s)
Clustered Regularly Interspaced Short Palindromic Repeats , Gene Editing , Animals , CRISPR-Cas Systems , Genome, Plant , Humans , Plants, Genetically Modified/geneticsABSTRACT
Transport costs can play a significant role in agricultural exports and businesses profitability. It can also influence farmers' decisions regarding cropland expansion, intensification or land abandonment. Thus, transport is useful to take into account when modeling and evaluating land use and cover change related to agriculture production. The dataset described in this article represents the Infrastructure Capital in the work presented by Millington et al. (2021) [1], in which the CRAFTY-Brazil model is used to evaluate the impacts of changing global demand for agricultural products on land use and cover change. This modeling required a transport cost dataset that spanned the model calibration period, was consistent through time and covered the entire study area. The most recent federal road network (for year 2017) obtained in vector format (shapefile) was joined to road section surface status tables for past years (2000, 2005 and 2010) in order to reconstruct the historic road network. Export ports handling agricultural commodities, and their years of operation, were identified. Both datasets were used to derive the relative transport cost to the nearest port for Brazil, for years 2000, 2005, 2010 and 2017.
ABSTRACT
Although soybean production has been increasing in the state of Rondônia in the last decade, soybean planted area has been estimated indirectly using secondary datasets, which has limited understanding of its spatiotemporal distribution patterns. This study aimed to map and analyze spatial patterns of soybean expansion in Rondônia. We developed a classification technique based on Spectral Mixture Analysis (SMA) derived from Landsat imagery and Decision Tree Classification to detect and map soybean plantations in 2000, 2005, 2010, and 2014. The soybean classification map showed 93% global accuracy, 23% omission and 0% of commission errors for soybean crop fields. The greatest increases of soybean cropped area in the state of Rondônia were observed between 2000-2005 and 2005-2010 time-periods (33,239 ha and 59,628 ha, respectively), mostly located in Southern Rondônia. The expansion of soybean areas to Northern Rondônia (25,627 ha) has mostly occurred in the 2010-2014 time period. We estimate that 95.4% of all newly created soybean plantations, detected by 2014, were established on lands deforested nine or more years earlier. We concluded that the incursion of soybean plantations on lands deforested for other land uses (e.g. ranching) is contributing to their displacement (pastures) from older colonization zones toward more remote frontier areas of the Amazon, exacerbating new deforestation there.(AU)
Os plantios de soja têm aumentado ao Norte e Sul dos municípios de Rondônia na última década, entretanto a área plantada de soja tem sido estimada utilizando dados secundários, o que limita o entendimento da distribuição espaço temporal da soja. Este estudo buscou analisar e mapear os padrões espaciais de expansão da soja em Rondônia. O mapeamento de plantios de soja nos anos 2000, 2005, 2010 e 2014 foi feito a partir de uma técnica de classificação baseada na análise de mistura espectral de imagens Landsat e em uma árvore de decisão. A acurácia global, erros de omissão e comissão para o mapeamento da soja foram 93%, 23% e 0%, respectivamente. Os resultados mostraram que os maiores incrementos da área de soja ocorreram no estado de Rondônia entre os períodos de 2000-2005 e 2005-2010 (33,239 ha e 59,628 ha, respectivamente). A expansão das áreas de soja para o norte de Rondônia (25,627 ha) ocorreu em sua maioria no período de 2010 a 2014. Observou-se que 95,4% de todos os plantios de soja detectados em 2014 ocorreram em áreas com pelo menos nove anos de desmatamento. Além disso, encontramos evidências de que os plantios de soja estão contribuindo para o deslocamento de usos da terra prévios de antigas zonas de colonização, predominantemente pastos que foram empurrados para outras áreas de fronteiras da Amazônia, e lá exacerbando novos desmatamentos.(AU)