Matches in SemOpenAlex for { <https://semopenalex.org/work/W4200068132> ?p ?o ?g. }
- W4200068132 endingPage "3488" @default.
- W4200068132 startingPage "3488" @default.
- W4200068132 abstract "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 other farm 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." @default.
- W4200068132 created "2021-12-31" @default.
- W4200068132 creator A5002147054 @default.
- W4200068132 creator A5008542499 @default.
- W4200068132 creator A5025114802 @default.
- W4200068132 creator A5026560471 @default.
- W4200068132 creator A5028163694 @default.
- W4200068132 creator A5044022244 @default.
- W4200068132 creator A5050107352 @default.
- W4200068132 creator A5072773583 @default.
- W4200068132 creator A5076288337 @default.
- W4200068132 creator A5084884466 @default.
- W4200068132 creator A5089492427 @default.
- W4200068132 date "2021-12-07" @default.
- W4200068132 modified "2023-09-30" @default.
- W4200068132 title "Adoption of Precision Technologies by Brazilian Dairy Farms: The Farmer’s Perception" @default.
- W4200068132 cites W1984411630 @default.
- W4200068132 cites W2010962925 @default.
- W4200068132 cites W2026587157 @default.
- W4200068132 cites W2052772815 @default.
- W4200068132 cites W2071949631 @default.
- W4200068132 cites W2073459066 @default.
- W4200068132 cites W2091145344 @default.
- W4200068132 cites W2100133057 @default.
- W4200068132 cites W2113268976 @default.
- W4200068132 cites W2133917095 @default.
- W4200068132 cites W2134606727 @default.
- W4200068132 cites W2148821412 @default.
- W4200068132 cites W2148973966 @default.
- W4200068132 cites W2156637045 @default.
- W4200068132 cites W2168560110 @default.
- W4200068132 cites W2490522477 @default.
- W4200068132 cites W2571665215 @default.
- W4200068132 cites W2789170334 @default.
- W4200068132 cites W2789752908 @default.
- W4200068132 cites W2898039066 @default.
- W4200068132 cites W2964229318 @default.
- W4200068132 cites W3019894198 @default.
- W4200068132 cites W3134361317 @default.
- W4200068132 cites W3191007633 @default.
- W4200068132 doi "https://doi.org/10.3390/ani11123488" @default.
- W4200068132 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/34944264" @default.
- W4200068132 hasPublicationYear "2021" @default.
- W4200068132 type Work @default.
- W4200068132 citedByCount "8" @default.
- W4200068132 countsByYear W42000681322022 @default.
- W4200068132 countsByYear W42000681322023 @default.
- W4200068132 crossrefType "journal-article" @default.
- W4200068132 hasAuthorship W4200068132A5002147054 @default.
- W4200068132 hasAuthorship W4200068132A5008542499 @default.
- W4200068132 hasAuthorship W4200068132A5025114802 @default.
- W4200068132 hasAuthorship W4200068132A5026560471 @default.
- W4200068132 hasAuthorship W4200068132A5028163694 @default.
- W4200068132 hasAuthorship W4200068132A5044022244 @default.
- W4200068132 hasAuthorship W4200068132A5050107352 @default.
- W4200068132 hasAuthorship W4200068132A5072773583 @default.
- W4200068132 hasAuthorship W4200068132A5076288337 @default.
- W4200068132 hasAuthorship W4200068132A5084884466 @default.
- W4200068132 hasAuthorship W4200068132A5089492427 @default.
- W4200068132 hasBestOaLocation W42000681321 @default.
- W4200068132 hasConcept C10138342 @default.
- W4200068132 hasConcept C118518473 @default.
- W4200068132 hasConcept C120217122 @default.
- W4200068132 hasConcept C127413603 @default.
- W4200068132 hasConcept C129361004 @default.
- W4200068132 hasConcept C134121241 @default.
- W4200068132 hasConcept C144133560 @default.
- W4200068132 hasConcept C154945302 @default.
- W4200068132 hasConcept C162324750 @default.
- W4200068132 hasConcept C166957645 @default.
- W4200068132 hasConcept C191897082 @default.
- W4200068132 hasConcept C192562407 @default.
- W4200068132 hasConcept C204983608 @default.
- W4200068132 hasConcept C205649164 @default.
- W4200068132 hasConcept C207267971 @default.
- W4200068132 hasConcept C2778691696 @default.
- W4200068132 hasConcept C2779885849 @default.
- W4200068132 hasConcept C37621935 @default.
- W4200068132 hasConcept C39432304 @default.
- W4200068132 hasConcept C41008148 @default.
- W4200068132 hasConcept C48824518 @default.
- W4200068132 hasConcept C50522688 @default.
- W4200068132 hasConcept C88463610 @default.
- W4200068132 hasConceptScore W4200068132C10138342 @default.
- W4200068132 hasConceptScore W4200068132C118518473 @default.
- W4200068132 hasConceptScore W4200068132C120217122 @default.
- W4200068132 hasConceptScore W4200068132C127413603 @default.
- W4200068132 hasConceptScore W4200068132C129361004 @default.
- W4200068132 hasConceptScore W4200068132C134121241 @default.
- W4200068132 hasConceptScore W4200068132C144133560 @default.
- W4200068132 hasConceptScore W4200068132C154945302 @default.
- W4200068132 hasConceptScore W4200068132C162324750 @default.
- W4200068132 hasConceptScore W4200068132C166957645 @default.
- W4200068132 hasConceptScore W4200068132C191897082 @default.
- W4200068132 hasConceptScore W4200068132C192562407 @default.
- W4200068132 hasConceptScore W4200068132C204983608 @default.
- W4200068132 hasConceptScore W4200068132C205649164 @default.
- W4200068132 hasConceptScore W4200068132C207267971 @default.