Precision agriculture in the United States: A comprehensive meta-review inspiring further research, innovation, and adoption

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Barbosa Junior, Marcelo Rodrigues ; Moreira, Bruno Rafael de Almeida ; Carreira, Vinicius dos Santos ; de Brito Filho, Armando Lopes ; Trentin, Carolina ; de Souza, Favia Luize Pereira ; Tedesco, Danilo ; Setiyono, Tri ; Flores, Joao Paulo ; Ampatzidis, Yiannis ; da Silva, Rouverson Pereira ; Shiratsuchi, Luciano Shozo

• Tipo de documento: Artigo Científico
• Fonte: COMPUTERS AND ELECTRONICS IN AGRICULTURE; v. 221, p. 22-pg., 2024-05-09.

Resumo

Precision agriculture has emerged as a dominant force in the United States, with widespread adoption of advanced technologies and decision support systems (DSS) since the 1980s. Key tools such as variable rate application (VRA), autopilot systems, and remote sensing have become integral for U.S. farmers, offering invaluable insights from crop, soil, and weather information to optimize agricultural production while minimizing environmental impact. To synthesize and categorize the extensive research available on precision agriculture, a systematic review protocol has been designed. Our objective is to offer clear and authoritative insights into the nature, scope, and volume of this field. Implementing a rigorous search strategy, we utilized renowned databases such as Scopus (R) and Web of ScienceTM to gather relevant and significant materiality. The retrieval process involved the use of indexing terms and Boolean operators, with a focus on 'precision agriculture' and 'precision farming', striking a balance between specificity and comprehensiveness. To ensure the credibility of our findings, only peer-reviewed papers authored by individuals affiliated with U.S. institutions have been included. Expert reviewers with deep knowledge in the field independently assessed the selected papers, thoroughly evaluating titles, abstracts, keywords, methods, conclusions, and declarations. Consistency and eligibility were paramount in determining which papers met the criteria for inclusion. Any discrepancies or disagreements were resolved through rigorous consensus-building discussions among the reviewers. Through this comprehensive meta-review, we provide a scientific contribution that enhances our understanding of precision agriculture, highlighting focus areas for further research and development (R&D). By synthesizing and categorizing the existing literature, we offer authoritative insights into the research landscape, informing future investigations and fostering innovation. Focusing specifically on the U.S., we shed light on the unique aspects and pioneering (AU)

• Processo FAPESP: 22/16084-8 - Estrutura de trabalho para sensoriamento remoto de alta resolução na tomaticultura utilizando minicomputador e computação em nuvem
• Beneficiário: Vinicius dos Santos Carreira
• Modalidade de apoio: Bolsas no Brasil - Doutorado
• Processo FAPESP: 22/13992-0 - Imagens uav e machine learning: uma fusão que impulsiona modelagem biofísica de matérias-primas sacarinas e bioenergéticas em cana-de-açúcar
• Beneficiário: Marcelo Rodrigues Barbosa Júnior
• Modalidade de apoio: Bolsas no Brasil - Doutorado