https://www.alice.cnptia.embrapa.br/alice/handle/item/196 Artigo em periódico indexado (CNPTIA) 2026-07-23T17:35:54Z https://www.alice.cnptia.embrapa.br/alice/handle/doc/1188487 Título: Avaliação do processo de fermentação para produção de etanol a partir do amido da mandioca: análise de viabilidade técnica e comparativa com o etanol da cana-de-açúcar e milho. Autoria: RAMOS, R. da C.; SILVA, F. C. da; SERRA, E. S.; FERNANDES, G. D. Conteúdo: A crescente demanda por fontes alternativas de energia renovável impulsionou o desenvolvimento de biocombustíveis, com destaque para o etanol. Tradicionalmente produzido a partir da cana-de-açúcar e do milho, já atingindo 25% do etanol produzido no país. Nesse cenário, a mandioca surge como uma alternativa promissora devido ao seu alto teor de amido, que pode ser convertido em açúcares fermentáveis após a hidrólise. A mandioca apresenta vantagens, como adaptabilidade a diferentes solos e climas, baixo custo de produção e resistência a pragas. Sua utilização pode impulsionar o desenvolvimento socioeconômico em regiões menos industrializadas, gerando emprego e renda, ao mesmo tempo, em que contribui para a redução de emissões de gases de efeito estufa por se tratar de um biocombustível renovável com menor impacto Ambiental. A diversificação de matérias-primas para a produção do etanol, fortalece a segurança energética, diminui a dependência de culturas tradicionais. Além disso, mitiga riscos associados a variações de mercado e condições climáticas. Dessa forma, investir em pesquisa e tecnologia voltadas à produção de etanol a partir da mandioca representa uma estratégia sustentável, capaz de integrar avanços ambientais, sociais e econômicos. Além de ampliar a matriz energética renovável do Brasil, essa alternativa reforça o compromisso com soluções que conciliam eficiência produtiva e preservação ambiental, contribuindo de forma decisiva para o futuro energético do País. Assim, o presente estudo, por meio de uma revisão bibliográfica, realiza uma comparação detalhada entre a produção de etanol a partir do amido de mandioca e do milho, considerando variáveis como produtividade agrícola, açúcares totais, conversão teórica, produtividade do etanol e preço CIF. Os dados disponíveis indicam que o milho é uma matéria-prima viável para a produção de etanol, apresentando produtividade significativa e custo unitário competitivo. A cana-de-açúcar, por sua vez, constitui uma matéria-prima tradicional e amplamente consolidada no Brasil, com elevada produtividade em etanol e balanço energético favorável. Palavras-chave: biocombustível, etanol, mandioca, hidrólise de amido. 2026-01-01T00:00:00Z https://www.alice.cnptia.embrapa.br/alice/handle/doc/1188259 Título: A blockchain system for scalable tokenized equity and efficient dividend distribution in agricultural cooperatives. Autoria: MINANGO, J.; PARADISI, A.; MARION, S.; LONA, A.; BERGIER, I. Conteúdo: Agricultural cooperatives in developing economies struggle with capital access and typically depend on subsidized credit with rigid repayment schedules that create vulnerability during low-production cycles. In this paper, we present a mathematical framework implemented through a smart contract to tokenize cooperative capital. Our mathematical framework uses magnified accumulators (scaled accumulator variables) to maintain temporal fairness, allocating dividends proportionally based on token holding periods through correction factors. The dividend distribution model operates with O(1) computational complexity, regardless of cooperative size. The CooperativeToken smart contract combines ERC20 standards with automated dividend distribution, democratic governance mechanisms, and a hybrid payment architecture supporting both cryptocurrency and fiat transactions. Deployment verification and a gas analysis demonstrate operational viability with consistent performance and minimal transaction costs, enabling scalability from small to large cooperatives. The proposed system offers agricultural cooperatives a debt-free alternative to conventional financing, democratizing access to tokenized capital structures that were previously restricted to large agribusinesses. While the model is validated via Ethereum Sepolia testnet simulation, real-world deployment and field testing in active cooperatives remain necessary to confirm practical feasibility. This study provides the algorithmic and economic foundation for such pilots. 2026-01-01T00:00:00Z https://www.alice.cnptia.embrapa.br/alice/handle/doc/1188020 Título: From empirical evidence to canonical modeling: an agent-based model of the Brazilian cattle trade network. Autoria: SILVA, R. F. M. da; OLIVEIRA, S. R. de M.; BERGIER, I. Conteúdo: The beef production chain plays a strategic role in Brazilian and global agri-food systems and faces growing demands for sustainability, transparency, and traceability. Building on official Animal Transit Guide (GTA) records from Mato Grosso do Sul, Brazil, this study examines whether a parsimonious agent-based model (ABM) can generate the main structural signatures of an observed cattle-trade network. The empirical benchmark is a directed and weighted network with 20,827 nodes and 258,120 weighted edges. The ABM represents producers and slaughterhouses as spatial agents connected by trade decisions based on three mechanisms: destination attractiveness, defined as the accumulated pull of a slaughterhouse based on previous simulated throughput; geographic distance, representing spatial friction; and relational memory, representing the tendency to repeat previous commercial ties. Producer choice is formalized through a local utility function that combines attractiveness, distance penalty, and relational memory under capacity, sourcing-radius, and saturation constraints. In the simulated scenarios, the top-five slaughterhouses accounted for 38.49 ± 2.56% of throughput at reduced scale and 14.40 ± 0.65% at intermediate scale, while weighted mean distances were 11.94 ± 0.56 and 9.07 ± 0.39 model units, respectively. The model reproduced, in structural and mechanistic terms, the emergence of dominant hubs, the concentration of flows, and the bounded increase in transaction distance with connectivity around the empirical threshold of kw ≈ 256. Sensitivity analyses indicated that attractiveness increases concentration, distance localizes transactions, and relational memory can stabilize repeated ties when recurrent activation is represented. Rather than reconstructing individual transactions, estimating policy impacts, or identifying a unique parameter vector, the model provides a generative explanation of how local trade rules can produce macro-level network patterns consistent with the observed cattle-trade regime. These findings support future prospective analyses of cattle governance, traceability, and sustainability within the broader context of Livestock 4.0. 2026-01-01T00:00:00Z https://www.alice.cnptia.embrapa.br/alice/handle/doc/1187841 Título: Cloud-based fusion of Sentinel-1 Radar, MODIS and soil moisture data for resolution-refined evapotranspiration mapping in mountain coffee systems. Autoria: KLINKE NETO, G.; OLIVEIRA, A. H.; BOLFE, E. L.; BERGIER, I.; GOULART, A. J. H. Conteúdo: Accurate monitoring of hydrological dynamics in complex perennial landscapes is a cornerstone for tropical agricultural sustainability. Traditional energy balance models based on orbital optical data often face methodological bottlenecks due to cloud cover and the “greening myth,” where optical indices fail to capture immediate water stress due to the non-linear decoupling between stomatal closure and pigment loss. This study developed a cloud-integrated multisensor framework to estimate actual evapotranspiration (ETa) at a refined 100 m resolution in mountain coffee systems, utilizing active microwave proxies from Sentinel-1. We fused polarimetric metrics—Degree of Polarization (DoP) and Shannon Entropy (SE)—with land surface temperature and soil moisture data. Multiple Linear Regression (MLR) was compared against non-linear algorithms (Random Forest and SVR) to prioritize model parsimony and physical interpretability. The results show that MLR emerged as the most parsimonious and suitable model within this localized dataset scope (R2 = 0.872; RMSE = 2.916 mm/8-day), outperforming complex “black-box” architectures. Soil moisture emerged as the dominant environmental driver of ETa variability, while SAR-based metrics served as sensitive mechanical proxies for canopy geometric heterogeneity and macro-structural variations. Cross-correlation analysis revealed a 16-day lag, empirically indicating that biophysical water shifts temporally precede geometric canopy alterations. Operationally, this framework ensures temporal continuity under persistent cloud cover and provides high-fidelity spatial detailing for precision water management. This approach offers an auditable and scalable tool for watershed planning and climate resilience in tropical agriculture. 2026-01-01T00:00:00Z