https://www.alice.cnptia.embrapa.br/alice/handle/item/250 Artigo em periódico indexado (CNPMS) Fri, 12 Jun 2026 00:07:34 GMT 2026-06-12T00:07:34Z https://www.alice.cnptia.embrapa.br/alice/handle/doc/1187362 Título: Draft genome of six tropical Azospirillum argentinense strains associated with maize and sorghum with potential for plant growth promotion. Autoria: CRUZ-MAGALHÃES, V.; RIBEIRO, V. P.; LANA, U. G. de P.; FERREIRA, L. V. S.; MARINS, M. S.; OLIVEIRA, M. C.; FIGUEIREDO, J. E. F.; REIS, D. P. dos; DINIZ, G. de F. D.; GUIEIRO, C. dos S. M.; SOUZA, F. A. de; GOMES, E. A.; OLIVEIRA-PAIVA, C. A.; SOUSA, S. M. de; MARRIEL, I. E. Conteúdo: This report presents draft genome sequences of six Azospirillum argentinense strains (CMS1626, CMS1630, CMS05, CMS07, CMS11, and CMS18) isolated frommaize rhizosphere soil or from sorghum stems grown on oxisols in the Brazilian Cerrado.These diazotrophic strains are promising bioinoculants for sustainable agriculture. Thu, 01 Jan 2026 00:00:00 GMT https://www.alice.cnptia.embrapa.br/alice/handle/doc/1187362 2026-01-01T00:00:00Z https://www.alice.cnptia.embrapa.br/alice/handle/doc/1187185 Título: Distribuição de água no solo pelo microaspersor ED2. Autoria: MEDEIROS, J. D. F. de; BRITO, R. A. L.; AZEVEDO, H. M. de; SAMPAIO, F. M. A. S. Conteúdo: O trabalho teve como objetivo determinar, sob condições de campo, alguns parâmetros do microaspersor ED,como, área superficial molhada, formação do bulbo úmido e eficiência de aplicação. O estudo foi conduzido num RegossoloEutn5fico com Fragipan e consistiu na aplicação de três volumes de água (300, 450 e 600 litros) com o acompanhamento da distribuição de água no solo. A área superficial molhada pelo microaspersor ED 2 foi 11,89; 12,79 e 13,43 m', para os volumes de água aplicados de 300, 450 e 600 litros, respectivamente, mostrando alta sensibilidade à velocidade do vento. A análise do conteúdo de água no solo mostrou que, para os 300, 450 e 600 litros de água aplicados, o bulbo efetivo alcançou as profundidades médias de 8,12 e 19 em e a frente de umedecimento, as profundidades médias de 31,40 e 48 em, respectivamente. Nas condições de clima estudado, a eficiência de aplicação média foi de 82,51% com uma perda, por evaporação, de 17,49%. Sun, 01 Jan 1995 00:00:00 GMT https://www.alice.cnptia.embrapa.br/alice/handle/doc/1187185 1995-01-01T00:00:00Z https://www.alice.cnptia.embrapa.br/alice/handle/doc/1186660 Título: Machine learning algorithms to predict the crops most susceptible to weed occurrence in integrated crop-livestock systems. Autoria: LUZ, A. L. G.; FERNANDES, A. M. da R.; COELHO, F. V.; OLIVEIRA, M. F. de; ALVARENGA, R. C. Conteúdo: ABSTRACT – The objective of this work was to investigate the use of machine learning algorithms to predict the crops most susceptible to weed occurrence in integrated crop-livestock systems, based on environmental factors of climate, soil, and cropping systems, to establish correlations between these elements and the occurrence of weeds. Three datasets were used for this purpose: the first provided quantitative information on the invasive species, the second contained data about the soil, and the last had records of the region’s climate. The algorithms used were Support Vector Machine, Decision Tree, Random Forest, and K-Nearest Neighbors. The application of machine learning algorithms to predict the susceptibility of crops to weed emergence is technically feasible and effective. The Decision Tree and Random Forest algorithms demonstrated the best performance, with both models achieving 99% accuracy. Robust relationships were established between environmental factors (climate, soil, and planting) and the appearance of invasive species in certain crops. The algorithms reproduced the patterns of weed emergence observed under field conditions. RESUMO –O objetivo deste trabalho foi investigar o uso de algoritmos de aprendizado de máquina para prever as culturas mais suscetíveis à ocorrência de plantas daninhas em sistemas de integração de lavoura-pecuária, com base em fatores ambientais de clima, solo e sistemas de cultivo para estabelecer correlações entre esses elementos e a incidência de plantas invasoras. Três conjuntos de dados foram utilizados para esse propósito: o primeiro forneceu informações quantitativas sobre as espécies invasoras, o segundo continha dados sobre o solo e o último possuía registros do clima da região. Os algoritmos utilizados foram Support Vector Machine, Decision Tree, Random Forest e K-Nearest Neighbors. A aplicação de algoritmos de aprendizado de máquina para prever a suscetibilidade das culturas à emergência de plantas daninhas é tecnicamente viável e eficaz. Os algoritmos Decision Tree e Random Forest demonstraram o melhor desempenho, com ambos os modelos atingindo 99% de acurácia. Relações robustas foram estabelecidas entre os fatores ambientais (clima, solo e plantio) e o surgimento de espécies invasoras em determinadas culturas. Os algoritmos reproduziram com sucesso os padrões de emergência de plantas daninhas observados em condições de campo. Thu, 01 Jan 2026 00:00:00 GMT https://www.alice.cnptia.embrapa.br/alice/handle/doc/1186660 2026-01-01T00:00:00Z https://www.alice.cnptia.embrapa.br/alice/handle/doc/1186312 Título: Degraded soils in the Brazilian semiarid region harbor bacteria with high phosphate solubilization potential. Autoria: BUZÓ, L. N.; FRACETTO, F. J. C.; OLIVEIRA-PAIVA, C. A.; NASCIMENTO, C. W. A. do; SOUZA JÚNIOR, V. S. de; SILVA, W. R. da; SILVA, C. C. G. da; FRACETTO, G. G. M. Conteúdo: The widespread deficiency of available phosphorus (P) in soils, particularly in tropical regions, necessitates the application of phosphate fertilizers due to their high adsorption. However, excessive use engenders significant economic costs and contributes to eutrophication of aquatic ecosystems and the mobilization of heavy metals. One viable alternative is the use of phosphate-solubilizing bacteria (PSB), which can solubilize phosphate through the production of acids and enzymes. This study aimed to assess the cultivable PSB community in different pedogenetic horizons of degraded and preserved Planosols and Luvisols (Planossolos and Luvissolos) in the semiarid and subhumid regions of Brazil, as these soils exhibit a high P availability, particularly in deeper layers. Furthermore, the biotechnological potential of the most promising PSB was evaluated in corn. A total of 170 PSB strains were collected, with 96 bacteria isolated from Planosol and 74 from Luvisol. The majority of the PSB exhibited a medium solubilization index and a broad morphophysiological diversity, and all solubilized calcium phosphate in liquid media. To investigate the biotechnological potential of these bacteria, eight PSB strains were selected based on their ability to solubilize calcium phosphate (>160 mg L-1) and to promote plant growth through mechanisms such as high auxin production, exopolysaccharide synthesis, zinc solubilization, and antagonism against the pathogen Fusarium sp. The PSB were identified as follows: PL1A, PL2L (Priestia sp.), PL1B (Neobacillus sp.), PL3J and LU13C (Streptomyces sp.), PL6A (Fictibacillus sp.), and PL18E and LU10E (Bacillus sp.). The PSB were inoculated into corn with the treatments based on the absence of phosphorus (-P) (control), simple superphosphate (SSP), reactive natural phosphate (RP), and the SSP + RP combination. The maximum available P value in the soil was observed in the RP treatment, where LU10E (78.70 mg dm-3) was inoculated, and in the SSP treatment, where LUC13C (69.9 mg dm-3) was inoculated. Isolates LU13C, LU10E, and PL3J exhibited the highest efficiency in phosphorus mobilization, PL1B and PL18E were moderately efficient, while PL1A, PL2L, and PL6A were the least efficient. This study assessed the diversity of phosphate-solubilizing bacteria (PSB) across soil profiles of degraded and vegetated Planosols and Luvisols in the Borborema Province, Northeastern Brazil, resulting in the establishment of the first bacterial collection comprising 170 strains with confirmed potential for phosphorus solubilization and corn growth promotion. Thu, 01 Jan 2026 00:00:00 GMT https://www.alice.cnptia.embrapa.br/alice/handle/doc/1186312 2026-01-01T00:00:00Z