The application of machine learning techniques to determine bioparameters, such as the leaf area index (LAI) and chlorophyll content, has shown significant potential, particularly with the use of unmanned aerial vehicles (UAVs). This study evaluated the use of RGB images obtained from UAVs to estimate bioparameters in sesame crops, utilizing machine learning techniques and data selection methods. The experiment was conducted at the Federal Rural University of Pernambuco and involved using a portable AccuPAR ceptometer to measure the LAI and spectrophotometry to determine photosynthetic pigments. Field images were captured using a DJI Mavic 2 Enterprise Dual remotely piloted aircraft equipped with RGB and thermal cameras. To manage the high dimensionality of the data, CRITIC and Pearson correlation methods were applied to select the most relevant indices for the XGBoost model. The data were divided into training, testing, and validation sets to ensure model generalization, with performance assessed using the R², MAE, and RMSE metrics. XGBoost effectively estimated the LAI, chlorophyll a, total chlorophyll, and carotenoids (R² > 0.7) but had limited performance for chlorophyll b. Pearson correlation was found to be the most effective data selection method for the algorithm.

O semiárido brasileiro possui mais de 1.260 municípios, formado pelos Estados do nordeste e norte de Minas Gerais. Devido a período de estiagem prolongada, os moradores armazenam água indiscriminadamente, favorecendo a proliferação do Aedes aegypti, transmissor de arboviroses. Portanto, objetivou-se analisar a distribuição dos casos confirmados, bem como, número de ovos coletados por ovitrampas, correlacionado-os com variáveis meteorológicas, em um município de região semiárida. Coletou-se dados secundários a respeito do número de casos, número de ovos por ovitrampa (infestação), variáveis meteorológicas referentes ao período de 2010 a 2013. Em seguida, confeccionou-se um banco de dados espacial e subsequente análise de distribuição espacial com método do Inverso da Distância (IDW), além da análise estatística de correlação entre as variáveis meteorológicas, número de casos confirmados e infestação. Observou-se que a correlação entre temperatura e umidade, com casos confirmados, foi considerada fraca, enquanto a precipitação em 2012 apresentou uma correlação forte. Porém, estas mesmas variáveis foram consideradas fraca em 2013. Em relação a distribuição espacial dos casos confirmados, houve uma concentração nos bairros de maior densidade populacional. Assim, a geotecnologia possibilita a identificação de áreas de risco, auxiliando na construção de estratégias eficientes.

Caatinga forest species are commonly used for the recovery of degraded areas, normally for the production of seedlings the seeds are placed to germinate on substrates. With that, the objective of this research was to evaluate different types of substrates for the germination of A. cearensis seeds, seeking to determine the most suitable to promote the initial development of the species. The experiment was carried out in a completely randomized design, with five substrates, being sand, fine texture vermiculite, thick texture vermiculite, humus and coconut fiber, with four replications of 25 seeds. After sowing, irrigation was performed daily until the 30th day after sowing. The percentage of emergence, mean time of emergence, emergency speed index, height of seedlings, root length, dry mass of the aerial part and root system and the total dry mass of seedlings were evaluated. The medium texture vermiculite substrate provided the best results regarding the percentage of emergence, the emergence speed index, the length of the aerial part and the root system. The medium texture vermiculite is the most suitable substrate for the initial development of A. cearensis.

Remote sensing is a technology that allows the monitoring of the environment with low cost and high periodicity, being the product of the Moderate Resolution Imaging Spectroradiometer (MODIS), one of the most used. Thus, we seek to present the applications of the MODIS sensor and the seasonal patterns of land use and land cover forms in the analysis with biophysical parameters in semi-arid regions, being divided into three sections: the first is about the MODIS sensor, explaining its characteristics; the second is a bibliometric review of the application of biophysical parameters obtained with MODIS in a semi-arid environment; finally, the third session contextualizes the methods of detection of land use and land cover changes. For this, the database used was the Web of Science (WOS), which has access to databases such as ProQuest, Scopus, and Wiley. The period considered was from 2000 to 2019, and the keywords searched were: MODIS, Semiarid, and Biophysical. With this review, it was concluded that the MODIS sensor could offer relevant products for environmental monitoring, highlighting MOD13, MYD13, MOD09, MOD11, MCD 15, MCD43, MCDB3, MOD16, and MOD17. The studies that seek to verify the impacts of climate change need to be cautious in analyzing the results obtained due to the contamination of products by atmospheric factors. Furthermore, to evaluate the changes in a region, some studies prioritize using descriptive statistics of the images. Future studies should consider using time trend analysis in a collection of remote sensing products.

Dada a importância de se verificar o potencial germinativo das sementes, a fim de se subsidiar a escolha da cultivar de soja a ser instalada no campo, objetivou-se analisar o potencial fisiológico de sementes das cultivares 84185RSF IPRO (OH JURURENA), SYN 1687 IPRO, BRAMAX DOMÍNIO IPRO, NS 8400 IPRO e M 8349 IPRO, em condições de campo no Oeste Baiano. A pesquisa foi conduzida em Barreiras-BA, área da fazenda Araucária, município referência junto com Luiz Eduardo Magalhães e São Desidério na produção da cultura de soja na região Nordeste do Brasil. Utilizou-se o delineamento em blocos casualizados com cinco tratamentos (cultivares) e quatro blocos. Foram avaliados o peso de mil sementes, o teor de água, a emergência (E), o índice de velocidade de emergência (IVE) e a velocidade de emergência (VE). O maior e menor peso de mil sementes foram verificados para as sementes das cultivares 84185RSF IPRO e NS 8400 IPRO333, respectivamente. As cultivares de soja analisadas se diferenciaram significativamente em relação à emergência e ao índice de velocidade de emergência. As sementes da cultivar SYN 1687 IPRO apresentaram um menor potencial fisiológico em relação as sementes das cultivares NS 8400 IPRO e M 8349 IPRO; o que poderia comprometer o seu estabelecimento no campo, principalmente em condições desfavoráveis.

The adequate management of irrigation with brackish water associated with balanced nutrition with potassium (K) should be investigated to reduce the deleterious effects of salt stress and increase the yield of sweet sorghum, which is suitable for forage exploration and in the biofuel industry. This investigation evaluated the effects of irrigation depth of brackish water and different doses of potassium on the growth and production of sweet sorghum, with the aim of obtaining better performance of this crop under different management of these inputs in the semi-arid region of Pernambuco, Brazil. Thus, the growth and yield of sweet sorghum were investigated under five irrigation depths (IDand 40 kg ha-1) in a randomized complete block design. Plant height, stem diameter, fresh mass of the stem, leaves, panicle, and total 1 = 222, ID2 = 388, ID3 = 554, ID4 = 720, and ID5 = 886 mm) with brackish water and five K2O doses (0, 10, 20, 30, fresh mass were evaluated in this investigation. Total fresh mass exhibited a surface response, with the highest estimated value (39.10 Mg ha⁻1) observed under an irrigation depth of 760 mm combined with a K₂O application rate of 40 kg ha⁻1. The study of different irrigation depths and their interaction with doses of Kin the semi-arid region, enabling a more appropriate irrigation and nutrition regime for the crop in the region.2O indicates the requirements for a greater supply of nutrients and water to sweet sorghum