Brazilian Agricultural Research Corporation
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Putting abandoned farmlands in the legend of land use and land cover maps of the Brazilian tropical savanna.
No full textFarmland abandonment is becoming a growing land use challenge in the Brazilian Cerrado, yet its extent, spatial distribution, and underlying drivers remain poorly understood. This study addresses the following question: Can deep learning methods reliably identify abandoned farmlands in tropical savanna environments using multispectral satellite images? To answer this question, we used a Fully Connected Neural Network (FCNN) classifier to map abandoned farmlands in the municipality of Buritizeiro, Minas Gerais State, Brazil, using Sentinel-2 images acquired in 2018 and 2022. Seven land use and land cover (LULC) classes were mapped using visible and near-infrared bands, spectral indices, spectral mixture components, and principal components as input parameters for the CNN. The LULC map for 2022 achieved high classification performance (overall accuracy = 94.7%; Kappa coefficient = 0.93). Agricultural areas classified in 2018 as annual croplands, cultivated pastures, eucalyptus plantations, or harvested eucalyptus that transitioned to grasslands or shrublands in 2022 were considered abandoned. Based on this definition, we identified 13,147 hectares of abandoned land in 2022, representing 4.7% of the municipality’s agricultural area in 2018. Most abandoned areas corresponded to eucalyptus plantations established for charcoal production. This study provides the first deep learning-based assessment of farmland abandonment in the Cerrado. Our findings demonstrated the potential of FCNN classifiers for detecting abandoned farmlands in this biome and provide important contribution for public policies focused on ecological restoration, carbon sequestration, and sustainable agricultural planning.Na publicação: Gustavo Bayma
Selection of morphoagronomic traits for screening tropical forage genotypes for waterlogging tolerance under controlled conditions.
Full text linkThis study aimed to identify morphoagronomic traits that discriminate waterlogging tolerance in tropical forage grasses and to assess the performance of genotypes with contrasting responses under controlled conditions, providing practical criteria for earlystage selection in breeding programs
Color analysis and UV-VIS-NIR spectroscopy in the selection of Passiflora edulis hybrids for fresh consumption.
Full text linkABSTRACT. In this study, an alternative method was developed to evaluate fruit and pulp color, using the CIE-L*a*b* kernel space and near-infrared reflectance spectroscopy in predicting the chemical characteristics of Passiflora edulis fruits. Five passion fruit hybrids were evaluated, four with purple-skinned (H09-163, H09-164, H09-166, and H09-125) and one with yellow--skinned (H09-165), in addition to BGP418 (control, yellow-skinned). BGP418 stood out for most physical characters, mainly in the weight of the fruits (224.67 g) and the pulp with seeds (112.77 g). However, its pulp yield was 11% lower compared to other genotypes. Cluster analysis based on fruit skin and pulp color using CIE-L*a*b* space, revealed greater consistency of groups compared to using the conventional method with a color palette. A higher soluble solids content was recorded in fruits with light purple-skinned and light-yellow pulp. Based on the skin and pulp color, the other chemical characteristics did not differ between the groups formed. With UV-VIS-NIR spectra, it was possible to distinguish the genotypes in the 350 and 2,500 nm spectra and the separation between the purple and yellow-skinned l genotypes. However, there was no consistent grouping in relation to the skin and pulp color or relationship with the chemical characteristics of the fruits. The breeding program can utilize the information generated to continue the development of cultivars for fresh consumption
Factors affecting the technologies adoption intensity and effect in milk production in Minas Gerais, Brazil.
Full text linkAbstract: Brazilian milk production has increased over the last decade, mainly due to the adoption of technologies and yield gains. However, huge technological heterogeneity persists among farmers. This paper adopts a beta regression model to evaluate the factors influencing the intensity of adoption of milk production technologies by 271 dairy farms in Minas Gerais, the major milk-producing state in Brazil. The dependent variable is an index that measures the intensity of adoption of the most updated technologies in the milk production system. The set of technologies comprises all stages of the milk production system include feeding management, herd management, environmental management and controls, equipment, and facilities. The explanatory variables refer to farmer and farm characteristics, access to information and milk commercialisation channels. The results suggest that the adoption of technologies is positively influenced by access to information through radio, magazines, the Internet, field days and rural extension service. In addition, risk-taking behaviour of farmers and dependence on the supply chain also foster the adoption of technologies. Multiple correspondence analysis demonstrates the positive association of intensity technology adoption and milk productivity indicators. The results have implications for diffusion and technology-transfer programmes through policies or strategies by the industry and collective actions
Thermochemical conversion of oil palm empty fruit bunch into fuel gas in a fluidized bed gasifier.
Full text linkWith increasing energy demand and agro-industrial waste generation, sustainable solutions for biomass valorization become essential. This study investigates the thermochemical conversion of oil palm empty fruit bunches (OPEFB) in a pilot-scale fluidized bed gasifier using air, steam, and nitrogen as gasifying agents. OPEFB characterization confirmed its favorable composition for energy purposes, including high volatile matter and lignocellulosic content. Gasification experiments revealed that the choice of gasifying agent strongly influenced syngas composition and yield. Air gasification maximized CO production, reaching 0.56 g/g biomass at an equivalence ratio (ER) of 0.43. Steam gasification produced the highest hydrogen and methane yields, with up to 52 % v/v H2 and 0.05 g CH4/g biomass, which are comparable to, or even higher than, those reported elsewhere for other lignocellulosic biomasses under similar conditions. Nitrogen atmosphere suppressed oxidation and promoted moderate H2 formation. These findings demonstrate that steam is the most effective agent for hydrogen-rich syngas generation, while air favors CO production. Overall, the study highlights OPEFB as a promising feedstock for clean energy and biorefinery applications, supporting the transition toward a circular and sustainable bioeconomy
How can production levels influence decision making on organic dairy farms in Brazil?
Full text linkThe aim of this study was to characterize organic dairy systems in Brazil. It was hypothesized that the production level of the herd influences the productivity and marketing aspects of organic milk production systems. A descriptive analysis was carried out in which the variables were geographical location, herd size, animal production, feed used, health and reproduction management, organic inputs used, feed production management, and transportation of products. The characteristics of the systems were evaluated according to the level of production, with farmers divided into 3 groups, with the upper extract comprising farms with an average production of over 16 L/cow per day (HIG), the medium extract with a production between 10.5 and 16 L/cow per day (MED), and the lower extract with an average production of less than 10.5 L/cow per day (LO). The variables were subjected to binomial logistic regression and comparisons were made by odds ratio. The average area of the properties was 107 ha (minimum 3 ha and maximum 1,450 ha); the area for organic milk production was 44 ha (minimum 1 ha and maximum 550 ha). The average daily milk production was 645 L/d (minimum of 12 L/d and maximum of 5,000 L/d), with an average production of 13 L/cow per day (minimum of 4 L/cow per day and maximum of 25 L/cow per day). The herds had an average of 58 cows (minimum 2 cows and maximum 310 cows) and 40 lactating cows (minimum 2 and maximum 255 cows). The average annual production was 7,517 L/ha per year (minimum 21 L/ha per year and maximum 29,877 L/ha per year). The average number of family workers was 2 (minimum 2 and maximum 7); the average number of external workers was 3 (minimum 2 and maximum 16). The HIG and MED farms were found to be 90% less likely to produce cheese. In addition, HIG and MED farms were 10.7 and 6.6 times more likely to have Holstein × Jersey crosses in their herd, respectively. The MED farms were 80% less likely to have Urochloa spp. pastures, whereas HIG farms were 93.2% less likely to have Urochloa spp. pastures and 92% less likely to use chopped grass to supplement the herd. However, the odds of having Megathyrsus maximus pastures was 4.66 times greater for HIG. In addition, HIG farms were 4.5 times more likely to use any type of management software. The analysis of certified organic dairy farms revealed a concentration in the Southeast region of Brazil, where production is mainly focused on milk, whereas other regions have more diversified organic production. The HIG farms are more likely to use specialized cattle breeds, herd supplementation, pastures formed by higher-yielding forage species with greater nutritional value, and management software. These results emphasize the need for public policies that promote the adoption of technological and sustainable practices to increase the efficiency and productivity of the organic dairy sector
Evaluation of laboratory-scale composting reactors to simulate compost barn bedding dynamics.
Full text linkEfficient management of compost bedding is essential for sustainability and animal welfare in Compost Barns (CBs). This study evaluated laboratory-scale bioreactors as tools to simulate CB composting dynamics, focusing on temperature control, aeration, and wood shaving supplementation. Three sequential experiments were conducted. Test 1 used a 50:50 mix of shavings and compost bedding for three months. Test 2 operated 1-week cycles with 100% compost bedding without temperature control. Test 3, also lasting 1 week, applied active temperature regulation at 39◦C with 100%bedding. Aeration wasset at15 mL/min in Tests 2 and 3. All experiments included initial and final measurements of pH, total solids (TS), and microbiological indicators. Results indicated that temperature control in Test 3 improved organic matter degradation and suggested enhanced pathogen reduction. These findings demonstrate that laboratory-scale bioreactors are effective for simulating CB composting and underscore the importance of temperature and aeration management. Future studies should further optimize temperature control and reactor design to enhance microbial activity and compost stabilization. To our knowledge, this is the first study to validate 3‑L laboratory-scale bioreactors specifically for simulating CB bedding dynamics
Towards a Global Soil Biodiversity Observatory (GLOSOB): science and policy backgrounds.
Full text linkThe world’s soils harbor an immense but as of yet inadequately measured and understood biodiversity, that perform essential ecosystem services in both undisturbed and agroecological and industrial agricultural systems. However, this vast natural resource is threatened by climate and land use change as well as unsustainable management practices, although the extent of these impacts on soil biodiversity and its vital functions for sustaining soil health and food security have not been adequately assessed worldwide. As part of the updated action plan of the International Initiative for the Conservation and Sustainable Use of Soil Biodiversity, established originally by the Convention on Biological Diversity (CBD) in 2002, a Global Soil Biodiversity Observatory was proposed in 2020 to assess and monitor soil biodiversity worldwide. Here, we review the historical background (particularly as it relates to the CBD), as well as the scientific and political context of this decision. Furthermore, we provide guidance on and a framework to assess the potential to undertake soil biodiversity monitoring in different countries, using scientifically based and agreed criteria related to a minimum set and wider optional range of soil biological variables. Finally, recommendations for improving understanding and monitoring capacity as well as funding mechanisms and political support for these activities are also reviewed
GIS for aquatic animal health management: a framework for tailored project development.
Full text linkAlthough Geographic Information Systems (GIS) have proved to be reliable tools for animal health management, their implementations in the aquatic animal health (AAH) domain are scarce, likely because they require expertise in GIS technologies, the specific characteristics of aquatic environments, and epidemiology. Considering the lack of GIS approaches tailored to AAH, this study presents a framework conceived to guide GIS users through the development of GIS operative designs for disease surveillance and response. Its practical application and actual accessibility within two case studies in an Italian marine environment and in a Brazilian freshwater aquaculture site were investigated. The main take-home message emerging from both the framework and its applications is the key importance of project planning in GIS development. Without a structured planning phase, GIS projects are likely to produce inconsistent, incomplete, or unsustainable outcomes. The framework accompanies GIS users, including those with little GIS knowledge, through all the stages of GIS project development, encouraging them to include the fundamental planning elements based on the principles of applicability, sustainability, appropriateness and opportunity of implementation. However, the framework must be used consciously, not as rigid instructions but, rather, as a tool that provides orientation to navigate GIS planning in the complex aquatic contexts
Air-water interfacial and foaming properties of crude and purified globulins from pigeon pea seeds.
Full text linkProtein concentrates or isolates are widely used by the food industry to produce aerated foods. Although the foamability is primarily attributed to proteins, highly surface-active minor compounds are also present in these ingredients, and their presence must be considered when investigating their air-water interfacial properties. In this study, the air-water interfacial and foaming properties of crude and purified globulin extracts from pigeon pea seeds were evaluated. At low bulk concentration, no difference in the interfacial behavior was observed between crude and purified globulins. At high bulk concentration, crude globulin extracts formed less rigid interfacial films compared to purified globulins, with the latter leading to viscoelastic solid-like interfacial layers. This suggests that in more concentrated suspensions, minor compounds of the crude extracts accumulate more at the interface, competing with globulins for adsorption, which leads to a reduction in the mechanical rigidity of the interfacial film. Purified globulins demonstrated superior aqueous foam stability compared to whey protein isolate and bovine serum albumin, highlighting the potential of pigeon pea globulins as effective foaming agents in food applications