Consulta: subjectFacets:"Precision agriculture technologies"
Registros recuperados: 2
Data/hora: 27/07/2024 02:49:12

Factors Influencing the Selection of Precision Farming Information Sources by Cotton Producers
Provedor de dados: Research in Agricultural & Applied Economics (AgEcon Searh)
Autores: Jenkins,   Amanda; Velandia,   Margarita M.; Lambert,   Dayton M.; Roberts,   Roland K.; Larson,   James A.; English,   Burton C.; Martin,   Steven W.
Precision farming information demanded by cotton producers is provided by various suppliers, including consultants, farm input dealerships, University Extension systems, and media sources. Factors associated with the decisions to select among information sources to search for precision farming information are analyzed using a multivariate probit regression accounting for correlation among the different selection decisions. Factors influencing these decisions are age, education, and income. These findings should be valuable to precision farming information providers who may be able to better meet their target clientele needs.
Tipo: Journal Article
Palavras-chave: Extension; Information-source-use decisions; Media; Multivariate probit; Precision agriculture technologies; Private sources; Farm Management; Teaching/Communication/Extension/Profession.
Ano: 2011
URL: http://purl.umn.edu/117779

Precision production environments for sugarcane fields
Provedor de dados: Scientia Agricola
Autores: Sanches,Guilherme Martineli; Paula,Maria Thereza Nonato de; Magalhães,Paulo Sérgio Graziano; Duft,Daniel Garbellini; Vitti,André César; Kolln,Oriel Tiago; Borges,Bernardo Melo Montes Nogueira; Franco,Henrique Coutinho Junqueira.
ABSTRACT: Sugarcane (saccharum spp.) in Brazil is managed on the basis of “production environments”. These “production environments” are used for many purposes, such as variety allocation, application of fertilizers and definition of the planting and harvesting periods. A quality classification is essential to ensure high economic returns. However, the classification is carried out by few and, most of the time, non-representative soil samples, showing unreal local conditions of soil spatial variability and resulting in classifications that are imprecise. One of the important tools in the precision agriculture technological package is the apparent electrical conductivity (ECa) sensors that can quickly map soil spatial variability with high-resolution and at...
Tipo: Info:eu-repo/semantics/article
Palavras-chave: Proximal soil sensors; Site-specific soil management; Soil apparent electrical conductivity; Precision agriculture technologies.
Ano: 2019
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162019000100010