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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha : |
16/04/2024 |
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Actualizado : |
18/04/2024 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Autor : |
MACEDO, I.; PITTELKOW, C.M.; TERRA, J.A.; CASTILLO, J.; ROEL, A. |
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Afiliación : |
IGNACIO MACEDO YAPOR, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; Department of Plant Sciences, Univ. of California, Davis, CA, USA; CAMERON M. PITTELKOW, Department of Plant Sciences, Univ. of California, Davis, CA, USA; JOSÉ ALFREDO TERRA FERNÁNDEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; EMILSE JESUS CASTILLO VELAZQUEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ALVARO ROEL DELLAZOPPA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
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Título : |
The power of on-farm data for improved agronomy. |
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Fecha de publicación : |
2024 |
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Fuente / Imprenta : |
Global Food Security. 2024, Volume 40, 100752. https://doi.org/10.1016/j.gfs.2024.100752 -- OPEN ACCESS. |
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ISSN : |
2211-9124 |
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DOI : |
10.1016/j.gfs.2024.100752 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received 24 November 2023, Revised 27 February 2024, Accepted 3 March 2024, Available online 16 March 2024, Version of Record 16 March 2024. -- Correspondence: Macedo, I.; Department of Plant Sciences, Univ. of California, Davis, CA, United States; email:imacedo@inia.org.uy -- Document type: Article Hybrid Gold Open Access. -- Incluye Appendix A. Supplementary data -- Data availability:
Data will be made available on request. -- License: Under Creative Commons license http://creativecommons.org/licenses/by-nc-nd/4.0/ -- |
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Contenido : |
ABSTRACT.- Advances in technology and analytics to support data-driven agriculture has important implications for global food security and environmental sustainability. However, relatively few studies have investigated the potential to leverage the power of on-farm data for improved agronomy at scale using geospatial machine learning methods. Working in high-yielding rice systems of Uruguay, we developed a geospatial framework to identify yield-limiting factors across 55,000 ha annually of cropland over four seasons (2018?2021 harvest years), while also testing for tradeoffs in the environmental footprint related to nitrogen (N) fertilizer use. Our application of geographically-weighted random forest models showed that crop management decisions influenced rice yield more than variation in soil properties, highlighting the potential for improved agronomy to boost crop production by 1.4-1.8 Mg ha-1 across regions. Seeding date, variety, P rate, and K rate were the most important variables controlling yield, but with significant variation across fields. When these factors were optimized by farmers, the risk of environmental N losses or soil N mining did not increase, highlighting the potential for sustainable intensification by improving N use efficiency. These findings present a pathway for harnessing the benefits of increasingly available on-farm data to identify yield-limiting factors while minimizing negative environmental externalities at the field-level. To enable the development of such geospatial frameworks in other regions, new partnerships are required to engage stakeholders and promote data sharing and collaboration among farmers, researchers, and industry, helping guide regional extension programs and orient future investments in agricultural research. © 2024 The Authors MenosABSTRACT.- Advances in technology and analytics to support data-driven agriculture has important implications for global food security and environmental sustainability. However, relatively few studies have investigated the potential to leverage the power of on-farm data for improved agronomy at scale using geospatial machine learning methods. Working in high-yielding rice systems of Uruguay, we developed a geospatial framework to identify yield-limiting factors across 55,000 ha annually of cropland over four seasons (2018?2021 harvest years), while also testing for tradeoffs in the environmental footprint related to nitrogen (N) fertilizer use. Our application of geographically-weighted random forest models showed that crop management decisions influenced rice yield more than variation in soil properties, highlighting the potential for improved agronomy to boost crop production by 1.4-1.8 Mg ha-1 across regions. Seeding date, variety, P rate, and K rate were the most important variables controlling yield, but with significant variation across fields. When these factors were optimized by farmers, the risk of environmental N losses or soil N mining did not increase, highlighting the potential for sustainable intensification by improving N use efficiency. These findings present a pathway for harnessing the benefits of increasingly available on-farm data to identify yield-limiting factors while minimizing negative environmental externalities at the field-level. To enable the dev... Presentar Todo |
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Palabras claves : |
Data-driven research; Decent work and economic growth - Goal 8; Geospatial data; Industry, innovation and infrastructure - Goal 9; Life on land - Goal 15; Nitrogen balance; Partnership for the goals - Goal 17; Responsible consumption and production - Goal 12; Rice; SISTEMA ARROZ-GANADERÍA - INIA; Sustainability; Sustainable Development Goals (SDGs); Zero hunger - Goal 2. |
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Asunto categoría : |
F01 Cultivo |
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URL : |
https://www.sciencedirect.com/science/article/pii/S2211912424000142/pdf
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Marc : |
LEADER 03526naa a2200361 a 4500
001 1064590
005 2024-04-18
008 2024 bl uuuu u00u1 u #d
022 $a2211-9124
024 7 $a10.1016/j.gfs.2024.100752$2DOI
100 1 $aMACEDO, I.
245 $aThe power of on-farm data for improved agronomy.$h[electronic resource]
260 $c2024
500 $aArticle history: Received 24 November 2023, Revised 27 February 2024, Accepted 3 March 2024, Available online 16 March 2024, Version of Record 16 March 2024. -- Correspondence: Macedo, I.; Department of Plant Sciences, Univ. of California, Davis, CA, United States; email:imacedo@inia.org.uy -- Document type: Article Hybrid Gold Open Access. -- Incluye Appendix A. Supplementary data -- Data availability: Data will be made available on request. -- License: Under Creative Commons license http://creativecommons.org/licenses/by-nc-nd/4.0/ --
520 $aABSTRACT.- Advances in technology and analytics to support data-driven agriculture has important implications for global food security and environmental sustainability. However, relatively few studies have investigated the potential to leverage the power of on-farm data for improved agronomy at scale using geospatial machine learning methods. Working in high-yielding rice systems of Uruguay, we developed a geospatial framework to identify yield-limiting factors across 55,000 ha annually of cropland over four seasons (2018?2021 harvest years), while also testing for tradeoffs in the environmental footprint related to nitrogen (N) fertilizer use. Our application of geographically-weighted random forest models showed that crop management decisions influenced rice yield more than variation in soil properties, highlighting the potential for improved agronomy to boost crop production by 1.4-1.8 Mg ha-1 across regions. Seeding date, variety, P rate, and K rate were the most important variables controlling yield, but with significant variation across fields. When these factors were optimized by farmers, the risk of environmental N losses or soil N mining did not increase, highlighting the potential for sustainable intensification by improving N use efficiency. These findings present a pathway for harnessing the benefits of increasingly available on-farm data to identify yield-limiting factors while minimizing negative environmental externalities at the field-level. To enable the development of such geospatial frameworks in other regions, new partnerships are required to engage stakeholders and promote data sharing and collaboration among farmers, researchers, and industry, helping guide regional extension programs and orient future investments in agricultural research. © 2024 The Authors
653 $aData-driven research
653 $aDecent work and economic growth - Goal 8
653 $aGeospatial data
653 $aIndustry, innovation and infrastructure - Goal 9
653 $aLife on land - Goal 15
653 $aNitrogen balance
653 $aPartnership for the goals - Goal 17
653 $aResponsible consumption and production - Goal 12
653 $aRice
653 $aSISTEMA ARROZ-GANADERÍA - INIA
653 $aSustainability
653 $aSustainable Development Goals (SDGs)
653 $aZero hunger - Goal 2
700 1 $aPITTELKOW, C.M.
700 1 $aTERRA, J.A.
700 1 $aCASTILLO, J.
700 1 $aROEL, A.
773 $tGlobal Food Security. 2024, Volume 40, 100752. https://doi.org/10.1016/j.gfs.2024.100752 -- OPEN ACCESS.
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Registro original : |
INIA Las Brujas (LB) |
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 | Acceso al texto completo restringido a Biblioteca INIA La Estanzuela. Por información adicional contacte bib_le@inia.org.uy. |
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Registro completo
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Biblioteca (s) : |
INIA La Estanzuela. |
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Fecha actual : |
23/03/2018 |
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Actualizado : |
24/06/2021 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Circulación / Nivel : |
Internacional - -- |
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Autor : |
SILVA, V. C.; OLIVEIRA, L. A. DE; LACERDA, M. DOS S. C.; PIMENTEL, L. A.; SANTOS, W. S.; MACÊDO, J. T. S. A. E; RIET-CORREA, F.; PEDROSO P. M. O. |
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Afiliación : |
Setor de Patologia Veterinária, Hospital Universitário de Medicina Veterinária, Universidade Federal do Recôncavo da Bahia (UFRB), Brazil.; Embrapa Mandioca e Fruticultura, Rua Embrapa s/n, Cruz das Almas, BA 44380-000, Brazil.; Setor de Patologia Veterinária, Hospital Universitário de Medicina Veterinária, Universidade Federal do Recôncavo da Bahia (UFRB),Brasil.; Setor de Patologia Veterinária, Hospital Universitário de Medicina Veterinária, Universidade Federal do Recôncavo da Bahia (UFRB), Brasil.; Setor de Patologia Veterinária, Hospital Universitário de Medicina Veterinária, Universidade Federal do Recôncavo da Bahia (UFRB), Brasil.; Laboratório de Patologia Veterinária, Fundação Universidade de Brasília (UnB), Campus Universitário Darcy Ribeiro, Via L4 Norte s/n, Brasília, DF 70910-970, Brazil.; FRANKLIN RIET-CORREA AMARAL, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; Laboratório de Patologia Veterinária, Fundação Universidade de Brasília (UnB), Campus Universitário Darcy Ribeiro, Via L4 Norte s/n, Brasília, DF 70910-970, Brazil. |
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Título : |
Experimental poisoning by cassava wastewater in sheep. (Intoxicação experimental por manipueira em ovinos). |
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Fecha de publicación : |
2017 |
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Fuente / Imprenta : |
Pesquisa Veterinária Brasileira, Rio de Janeiro v. 37, n. 11, p. 1241-1246, novembro. 2017. |
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DOI : |
10.1590/s0100-736x2017001100008 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received: November 23, 2016// Accepted: March 17, 2017. |
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Contenido : |
Abstracts: The processing of Manihot esculenta (cassava) tubers yield different by-products, including cassava wastewater, which is the liquid pressed out of the tuber after it has been mechanically crushed. Cyanide poisoning after ingestion of cassava wastewater has been reported in ruminants and pigs in Northeastern Brazil. With the aim of studying its toxicity, cassava wastewater was administered orally to six sheep at doses of 0.99, 0.75, 0.70, 0.63, and 0.5 mg of hydrocyanic acid kg-1 body weight, which corresponded to 14.2, 10.6, 9.8, 8.89, and 7.1 mL of wastewater kg-1. On the second day, the sheep received a volume of wastewater which corresponded to 0.46, 0.34, 0.31, 0.28, and 0.23 mg of HCN kg-1. A sheep used as control received 9.9 mL of water kg-1 BW. Sheep that received from 0.75 to 0.99 mg kg-1 of HCN on the first day exhibited severe clinical signs of poisoning, and the sheep that received 0.63 and 0.5 mg kg-1 exhibited mild clinical signs. All sheep were successfully treated with sodium thiosulfate. On the second day, only the sheep that received 0.46 mg kg-1 and 0.34 mg kg-1 exhibited mild clinical signs and recovered spontaneously. The concentration of HCN in the wastewater was 71.69±2.19 ?g mL-1 immediately after production, 30.56±2.45 ?g mL-1 after 24 hours, and 24.25±1.28 ?g mL-1 after 48 hours. The picric acid paper test was strongly positive 5 minutes after production; moderately positive 24 hours after production, and negative 48 hours after production. We conclude that cassava wastewater is highly toxic to sheep if ingested immediately after production, but rapidly loses toxicity in 24-48 hours. MenosAbstracts: The processing of Manihot esculenta (cassava) tubers yield different by-products, including cassava wastewater, which is the liquid pressed out of the tuber after it has been mechanically crushed. Cyanide poisoning after ingestion of cassava wastewater has been reported in ruminants and pigs in Northeastern Brazil. With the aim of studying its toxicity, cassava wastewater was administered orally to six sheep at doses of 0.99, 0.75, 0.70, 0.63, and 0.5 mg of hydrocyanic acid kg-1 body weight, which corresponded to 14.2, 10.6, 9.8, 8.89, and 7.1 mL of wastewater kg-1. On the second day, the sheep received a volume of wastewater which corresponded to 0.46, 0.34, 0.31, 0.28, and 0.23 mg of HCN kg-1. A sheep used as control received 9.9 mL of water kg-1 BW. Sheep that received from 0.75 to 0.99 mg kg-1 of HCN on the first day exhibited severe clinical signs of poisoning, and the sheep that received 0.63 and 0.5 mg kg-1 exhibited mild clinical signs. All sheep were successfully treated with sodium thiosulfate. On the second day, only the sheep that received 0.46 mg kg-1 and 0.34 mg kg-1 exhibited mild clinical signs and recovered spontaneously. The concentration of HCN in the wastewater was 71.69±2.19 ?g mL-1 immediately after production, 30.56±2.45 ?g mL-1 after 24 hours, and 24.25±1.28 ?g mL-1 after 48 hours. The picric acid paper test was strongly positive 5 minutes after production; moderately positive 24 hours after production, and negative 48 hours after productio... Presentar Todo |
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Palabras claves : |
ACICO PRUSSICO; ACIDO CIANIDRICO; CASSAVA; HIDROGEN CYANIDE; MANDIOCA; NORDESTE DO BRASIL; NORTHEASTERN BRAZIL; PLATAFORMA SALUD ANIMAL; RUMINANTS; SHEEP; WASTEWATER. |
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Thesagro : |
ENFERMEDADES DE LOS ANIMALES; OVINO; RUMIANTES. |
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Asunto categoría : |
L73 Enfermedades de los animales |
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Marc : |
LEADER 02904naa a2200397 a 4500
001 1058312
005 2021-06-24
008 2017 bl uuuu u00u1 u #d
024 7 $a10.1590/s0100-736x2017001100008$2DOI
100 1 $aSILVA, V. C.
245 $aExperimental poisoning by cassava wastewater in sheep. (Intoxicação experimental por manipueira em ovinos).$h[electronic resource]
260 $c2017
500 $aArticle history: Received: November 23, 2016// Accepted: March 17, 2017.
520 $aAbstracts: The processing of Manihot esculenta (cassava) tubers yield different by-products, including cassava wastewater, which is the liquid pressed out of the tuber after it has been mechanically crushed. Cyanide poisoning after ingestion of cassava wastewater has been reported in ruminants and pigs in Northeastern Brazil. With the aim of studying its toxicity, cassava wastewater was administered orally to six sheep at doses of 0.99, 0.75, 0.70, 0.63, and 0.5 mg of hydrocyanic acid kg-1 body weight, which corresponded to 14.2, 10.6, 9.8, 8.89, and 7.1 mL of wastewater kg-1. On the second day, the sheep received a volume of wastewater which corresponded to 0.46, 0.34, 0.31, 0.28, and 0.23 mg of HCN kg-1. A sheep used as control received 9.9 mL of water kg-1 BW. Sheep that received from 0.75 to 0.99 mg kg-1 of HCN on the first day exhibited severe clinical signs of poisoning, and the sheep that received 0.63 and 0.5 mg kg-1 exhibited mild clinical signs. All sheep were successfully treated with sodium thiosulfate. On the second day, only the sheep that received 0.46 mg kg-1 and 0.34 mg kg-1 exhibited mild clinical signs and recovered spontaneously. The concentration of HCN in the wastewater was 71.69±2.19 ?g mL-1 immediately after production, 30.56±2.45 ?g mL-1 after 24 hours, and 24.25±1.28 ?g mL-1 after 48 hours. The picric acid paper test was strongly positive 5 minutes after production; moderately positive 24 hours after production, and negative 48 hours after production. We conclude that cassava wastewater is highly toxic to sheep if ingested immediately after production, but rapidly loses toxicity in 24-48 hours.
650 $aENFERMEDADES DE LOS ANIMALES
650 $aOVINO
650 $aRUMIANTES
653 $aACICO PRUSSICO
653 $aACIDO CIANIDRICO
653 $aCASSAVA
653 $aHIDROGEN CYANIDE
653 $aMANDIOCA
653 $aNORDESTE DO BRASIL
653 $aNORTHEASTERN BRAZIL
653 $aPLATAFORMA SALUD ANIMAL
653 $aRUMINANTS
653 $aSHEEP
653 $aWASTEWATER
700 1 $aOLIVEIRA, L. A. DE
700 1 $aLACERDA, M. DOS S. C.
700 1 $aPIMENTEL, L. A.
700 1 $aSANTOS, W. S.
700 1 $aMACÊDO, J. T. S. A. E
700 1 $aRIET-CORREA, F.
700 1 $aPEDROSO P. M. O.
773 $tPesquisa Veterinária Brasileira, Rio de Janeiro$gv. 37, n. 11, p. 1241-1246, novembro. 2017.
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