Adoption of precision technologies by brazilian dairy farms: the farmer's perception.

Detalhes bibliográficos
Autor(a) principal: SILVI, R.
Data de Publicação: 2021
Outros Autores: PEREIRA, L. G. R., PAIVA, C. A. V., TOMICH, T. R., TEIXEIRA, V. A., SACRAMENTO, J. P., FERREIRA, R. E. P., COELHO, S. G., MACHADO, F. S., CAMPOS, M. M., DÓREA, J. R. R.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
Texto Completo: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1137526
https://doi.org/10.3390/ani11123488
Resumo: The use of precision farming technologies, such as milking robots, automated calf feeders, wearable sensors, and others, has significantly increased in dairy operations over the last few years. The growing interest in farming technologies to reduce labor, maximize productivity, and increase profitability is becoming noticeable in several countries, including Brazil. Information regarding technology adoption, perception, and effectiveness in dairy farms could shed light on challenges that need to be addressed by scientific research and extension programs. The objective of this study was to characterize Brazilian dairy farms based on technology usage. Factors such as willingness to invest in precision technologies, adoption of sensor systems, farmer profile, farm characteristics, and production indexes were investigated in 378 dairy farms located in Brazil. A survey with 22 questions was developed and distributed via Google Forms from July 2018 to July 2020. The farms were then classified into seven clusters: (1) top yield farms; (2) medium?high yield, medium‐tech; (3) medium yield and top high‐tech; (4) medium yield and medium‐tech; (5) young medium?low yield and low‐tech; (6) elderly medium?low yield and low‐tech; and (7) low‐tech grazing. The most frequent technologies adopted by producers were milk meters systems (31.7%), milking parlor smart gate (14.5%), sensor systems to detect mastitis (8.4%), cow activity meter (7.1%), and body temperature (7.9%). Based on a scale containing numerical values (1?5), producers indicated ?available technical support? (mean; σ2) (4.55; 0.80) as the most important decision criterion involved in adopting technology, followed by ?return on investment?ROI? (4.48; 0.80), ?user‐ friendliness? (4.39; 0.88), ?upfront investment cost? (4.36; 0.81), and ?compatibility with farm management software? (4.2; 1.02). The most important factors precluding investment in precision dairy technologies were the need for investment in other sectors of the farm (36%), the uncertainty of ROI (24%), and lack of integration with otherfarm systems and software (11%). Farmers indicated that the most useful technologies were automatic milk meters systems (mean; σ2) (4.05; 1.66), sensor systems for mastitis detection (4.00; 1.57), automatic feeding systems (3.50; 2.05), cow activity meter (3.45; 1.95), and in‐line milk analyzers (3.45; 1.95). Overall, the concerns related to data integration, ROI, and user‐friendliness of technologies are similar to those of dairy farms located in other countries. Increasing available technical support for sensing technology can have a positive impact on technology adoption.
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spelling Adoption of precision technologies by brazilian dairy farms: the farmer's perception.Fazenda inteligenteBovinoGadoPecuáriaThe use of precision farming technologies, such as milking robots, automated calf feeders, wearable sensors, and others, has significantly increased in dairy operations over the last few years. The growing interest in farming technologies to reduce labor, maximize productivity, and increase profitability is becoming noticeable in several countries, including Brazil. Information regarding technology adoption, perception, and effectiveness in dairy farms could shed light on challenges that need to be addressed by scientific research and extension programs. The objective of this study was to characterize Brazilian dairy farms based on technology usage. Factors such as willingness to invest in precision technologies, adoption of sensor systems, farmer profile, farm characteristics, and production indexes were investigated in 378 dairy farms located in Brazil. A survey with 22 questions was developed and distributed via Google Forms from July 2018 to July 2020. The farms were then classified into seven clusters: (1) top yield farms; (2) medium?high yield, medium‐tech; (3) medium yield and top high‐tech; (4) medium yield and medium‐tech; (5) young medium?low yield and low‐tech; (6) elderly medium?low yield and low‐tech; and (7) low‐tech grazing. The most frequent technologies adopted by producers were milk meters systems (31.7%), milking parlor smart gate (14.5%), sensor systems to detect mastitis (8.4%), cow activity meter (7.1%), and body temperature (7.9%). Based on a scale containing numerical values (1?5), producers indicated ?available technical support? (mean; σ2) (4.55; 0.80) as the most important decision criterion involved in adopting technology, followed by ?return on investment?ROI? (4.48; 0.80), ?user‐ friendliness? (4.39; 0.88), ?upfront investment cost? (4.36; 0.81), and ?compatibility with farm management software? (4.2; 1.02). The most important factors precluding investment in precision dairy technologies were the need for investment in other sectors of the farm (36%), the uncertainty of ROI (24%), and lack of integration with otherfarm systems and software (11%). Farmers indicated that the most useful technologies were automatic milk meters systems (mean; σ2) (4.05; 1.66), sensor systems for mastitis detection (4.00; 1.57), automatic feeding systems (3.50; 2.05), cow activity meter (3.45; 1.95), and in‐line milk analyzers (3.45; 1.95). Overall, the concerns related to data integration, ROI, and user‐friendliness of technologies are similar to those of dairy farms located in other countries. Increasing available technical support for sensing technology can have a positive impact on technology adoption.REBECA SILVI, Universidade Estadual de Santa Cruz; LUIZ GUSTAVO RIBEIRO PEREIRA, CNPGL; CLAUDIO ANTONIO VERSIANI PAIVA, CNPGL; THIERRY RIBEIRO TOMICH, CNPGL; VANESSA A. TEIXEIRA, Universidade Federal de Minas Gerais; JOÃO PAULO SACRAMENTO, Universidade Federal de São João del-Rei; RAFAEL E. P. FERREIRA, University of Wisconsin; SANDRA G. COELHO, Universidade Federal de Minas Gerais; FERNANDA SAMARINI MACHADO, CNPGL; MARIANA MAGALHAES CAMPOS, CNPGL; JOÃO RICARDO. R. DÓREA, University of Wisconsin.SILVI, R.PEREIRA, L. G. R.PAIVA, C. A. V.TOMICH, T. R.TEIXEIRA, V. A.SACRAMENTO, J. P.FERREIRA, R. E. P.COELHO, S. G.MACHADO, F. S.CAMPOS, M. M.DÓREA, J. R. R.2021-12-10T14:01:22Z2021-12-10T14:01:22Z2021-12-102021info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleAnimals, v. 11, 3488, 2021.http://www.alice.cnptia.embrapa.br/alice/handle/doc/1137526https://doi.org/10.3390/ani11123488enginfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPA2021-12-10T14:01:33Zoai:www.alice.cnptia.embrapa.br:doc/1137526Repositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestopendoar:21542021-12-10T14:01:33falseRepositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestcg-riaa@embrapa.bropendoar:21542021-12-10T14:01:33Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false
dc.title.none.fl_str_mv Adoption of precision technologies by brazilian dairy farms: the farmer's perception.
title Adoption of precision technologies by brazilian dairy farms: the farmer's perception.
spellingShingle Adoption of precision technologies by brazilian dairy farms: the farmer's perception.
SILVI, R.
Fazenda inteligente
Bovino
Gado
Pecuária
title_short Adoption of precision technologies by brazilian dairy farms: the farmer's perception.
title_full Adoption of precision technologies by brazilian dairy farms: the farmer's perception.
title_fullStr Adoption of precision technologies by brazilian dairy farms: the farmer's perception.
title_full_unstemmed Adoption of precision technologies by brazilian dairy farms: the farmer's perception.
title_sort Adoption of precision technologies by brazilian dairy farms: the farmer's perception.
author SILVI, R.
author_facet SILVI, R.
PEREIRA, L. G. R.
PAIVA, C. A. V.
TOMICH, T. R.
TEIXEIRA, V. A.
SACRAMENTO, J. P.
FERREIRA, R. E. P.
COELHO, S. G.
MACHADO, F. S.
CAMPOS, M. M.
DÓREA, J. R. R.
author_role author
author2 PEREIRA, L. G. R.
PAIVA, C. A. V.
TOMICH, T. R.
TEIXEIRA, V. A.
SACRAMENTO, J. P.
FERREIRA, R. E. P.
COELHO, S. G.
MACHADO, F. S.
CAMPOS, M. M.
DÓREA, J. R. R.
author2_role author
author
author
author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv REBECA SILVI, Universidade Estadual de Santa Cruz; LUIZ GUSTAVO RIBEIRO PEREIRA, CNPGL; CLAUDIO ANTONIO VERSIANI PAIVA, CNPGL; THIERRY RIBEIRO TOMICH, CNPGL; VANESSA A. TEIXEIRA, Universidade Federal de Minas Gerais; JOÃO PAULO SACRAMENTO, Universidade Federal de São João del-Rei; RAFAEL E. P. FERREIRA, University of Wisconsin; SANDRA G. COELHO, Universidade Federal de Minas Gerais; FERNANDA SAMARINI MACHADO, CNPGL; MARIANA MAGALHAES CAMPOS, CNPGL; JOÃO RICARDO. R. DÓREA, University of Wisconsin.
dc.contributor.author.fl_str_mv SILVI, R.
PEREIRA, L. G. R.
PAIVA, C. A. V.
TOMICH, T. R.
TEIXEIRA, V. A.
SACRAMENTO, J. P.
FERREIRA, R. E. P.
COELHO, S. G.
MACHADO, F. S.
CAMPOS, M. M.
DÓREA, J. R. R.
dc.subject.por.fl_str_mv Fazenda inteligente
Bovino
Gado
Pecuária
topic Fazenda inteligente
Bovino
Gado
Pecuária
description The use of precision farming technologies, such as milking robots, automated calf feeders, wearable sensors, and others, has significantly increased in dairy operations over the last few years. The growing interest in farming technologies to reduce labor, maximize productivity, and increase profitability is becoming noticeable in several countries, including Brazil. Information regarding technology adoption, perception, and effectiveness in dairy farms could shed light on challenges that need to be addressed by scientific research and extension programs. The objective of this study was to characterize Brazilian dairy farms based on technology usage. Factors such as willingness to invest in precision technologies, adoption of sensor systems, farmer profile, farm characteristics, and production indexes were investigated in 378 dairy farms located in Brazil. A survey with 22 questions was developed and distributed via Google Forms from July 2018 to July 2020. The farms were then classified into seven clusters: (1) top yield farms; (2) medium?high yield, medium‐tech; (3) medium yield and top high‐tech; (4) medium yield and medium‐tech; (5) young medium?low yield and low‐tech; (6) elderly medium?low yield and low‐tech; and (7) low‐tech grazing. The most frequent technologies adopted by producers were milk meters systems (31.7%), milking parlor smart gate (14.5%), sensor systems to detect mastitis (8.4%), cow activity meter (7.1%), and body temperature (7.9%). Based on a scale containing numerical values (1?5), producers indicated ?available technical support? (mean; σ2) (4.55; 0.80) as the most important decision criterion involved in adopting technology, followed by ?return on investment?ROI? (4.48; 0.80), ?user‐ friendliness? (4.39; 0.88), ?upfront investment cost? (4.36; 0.81), and ?compatibility with farm management software? (4.2; 1.02). The most important factors precluding investment in precision dairy technologies were the need for investment in other sectors of the farm (36%), the uncertainty of ROI (24%), and lack of integration with otherfarm systems and software (11%). Farmers indicated that the most useful technologies were automatic milk meters systems (mean; σ2) (4.05; 1.66), sensor systems for mastitis detection (4.00; 1.57), automatic feeding systems (3.50; 2.05), cow activity meter (3.45; 1.95), and in‐line milk analyzers (3.45; 1.95). Overall, the concerns related to data integration, ROI, and user‐friendliness of technologies are similar to those of dairy farms located in other countries. Increasing available technical support for sensing technology can have a positive impact on technology adoption.
publishDate 2021
dc.date.none.fl_str_mv 2021-12-10T14:01:22Z
2021-12-10T14:01:22Z
2021-12-10
2021
dc.type.driver.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv Animals, v. 11, 3488, 2021.
http://www.alice.cnptia.embrapa.br/alice/handle/doc/1137526
https://doi.org/10.3390/ani11123488
identifier_str_mv Animals, v. 11, 3488, 2021.
url http://www.alice.cnptia.embrapa.br/alice/handle/doc/1137526
https://doi.org/10.3390/ani11123488
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron:EMBRAPA
instname_str Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
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reponame_str Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
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repository.mail.fl_str_mv cg-riaa@embrapa.br
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