Gaps between farmer and attainable yields across rainfed sunflower growing regions of Argentina

We computed three estimators of attainable yield for each of between 5 and 8 rainfed sunflower-growing regions of Argentina using between 5 and 9 years of data over the 2000-2007 interval. The estimators were based on comparative yield trial [CYT] data for commercial hybrids, on individual commercia...

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Otros Autores: Hall, Antonio Juan, Feoli, Carlos, Ingaramo, Jorge, Balzarini, Mónica Graciela
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Lenguaje:Inglés
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Acceso en línea:http://ri.agro.uba.ar/files/intranet/articulo/2013hall.pdf
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245 0 0 |a Gaps between farmer and attainable yields across rainfed sunflower growing regions of Argentina 
520 |a We computed three estimators of attainable yield for each of between 5 and 8 rainfed sunflower-growing regions of Argentina using between 5 and 9 years of data over the 2000-2007 interval. The estimators were based on comparative yield trial [CYT] data for commercial hybrids, on individual commercial field [ICF] data, and on reporting district [RD] yield information. Contrasts between these estimators led us to prefer the attainable [CYT] yield estimator over the other two. Attainable [CYT] yields ranged from 2.21 to 2.83tha-1 across regions. Yield gaps between mean farmer [RD data] and attainable [CYT] yields were computed using best linear unbiased estimator [BLUE] values for both variables obtained using mixed linear models. These gaps were statistically significant [p less or equal to 0.05] for all 8 regions and ranged from 0.37 to 1.18tha-1 across regions, for a country average of 0.75tha-1, equivalent to 41percent of the mean country yield of 1.85tha-1. We also used CYT data to examine the issue of recurrent, albeit infrequent, reports of unusually high yields. Mean yields for the top decile of comparative yield trial data ranged from 3.2 to 4.2tha-1 across regions, and the highest yields for this decile in any of the years of record ranged from 3.9 to 4.8tha-1 across regions. Individual commercial field yields were available for 5 regions. Gaps between BLUEs for this variable and attainable [CYT] yields were smaller than those between reporting district and attainable [CYT] yields, but were nevertheless significant in all 5 regions. A notable feature of reporting district, individual field, and yield trial data was their variability. At reporting district level within regions, contributions of spatial and temporal variability were roughly similar. The mean relative contribution of the trial effect to non-error variance of the CYT data exceeded 85 percent across regions, dominating the contributions of genotype and of genotype by trial effects. We conclude that the magnitude of mean farmer/attainable [CYT] yield gaps for this crop in Argentina justifies further research aimed at reducing regional gaps; and that CYT data can be used to generate an appropriate benchmark for attainable yields. 
653 0 |a COMPARATIVE YIELD TRIALS 
653 0 |a RAINFED CROPPING 
653 0 |a REGIONALISATION 
653 0 |a REPORTING DISTRICT 
653 0 |a YIELD GAPS 
653 0 |a CROP YIELD 
653 0 |a CULTIVATION 
653 0 |a DICOTYLEDON 
653 0 |a RAINFED AGRICULTURE 
653 0 |a REGIONALIZATION 
653 0 |a TEMPORAL VARIATION 
653 0 |a ARGENTINA 
653 0 |a HELIANTHUS 
653 0 |a POLYOMMATINAE 
700 1 |9 24024  |a Hall, Antonio Juan 
700 1 |a Feoli, Carlos  |9 40051 
700 1 |a Ingaramo, Jorge  |9 40073 
700 1 |a Balzarini, Mónica Graciela  |9 49606 
773 |t Field Crops Research  |g vol.143 (2013), p.119-129 
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900 |a ^aBalzarini, M.^tCátedra de Estadística y Biometría, Facultad de Ciencias Agropecuarias, Universidad Nacional de Córdoba/CONICET, Av. Valparaíso s/n, CC 509, 5000 Córdoba, Argentina 
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900 |a REGIONALISATION 
900 |a REPORTING DISTRICT 
900 |a YIELD GAPS 
900 |a CROP YIELD 
900 |a CULTIVATION 
900 |a DICOTYLEDON 
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900 |a REGIONALIZATION 
900 |a TEMPORAL VARIATION 
900 |a ARGENTINA 
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900 |a We computed three estimators of attainable yield for each of between 5 and 8 rainfed sunflower-growing regions of Argentina using between 5 and 9 years of data over the 2000-2007 interval. The estimators were based on comparative yield trial [CYT] data for commercial hybrids, on individual commercial field [ICF] data, and on reporting district [RD] yield information. Contrasts between these estimators led us to prefer the attainable [CYT] yield estimator over the other two. Attainable [CYT] yields ranged from 2.21 to 2.83tha-1 across regions. Yield gaps between mean farmer [RD data] and attainable [CYT] yields were computed using best linear unbiased estimator [BLUE] values for both variables obtained using mixed linear models. These gaps were statistically significant [p less or equal to 0.05] for all 8 regions and ranged from 0.37 to 1.18tha-1 across regions, for a country average of 0.75tha-1, equivalent to 41percent of the mean country yield of 1.85tha-1. We also used CYT data to examine the issue of recurrent, albeit infrequent, reports of unusually high yields. Mean yields for the top decile of comparative yield trial data ranged from 3.2 to 4.2tha-1 across regions, and the highest yields for this decile in any of the years of record ranged from 3.9 to 4.8tha-1 across regions. Individual commercial field yields were available for 5 regions. Gaps between BLUEs for this variable and attainable [CYT] yields were smaller than those between reporting district and attainable [CYT] yields, but were nevertheless significant in all 5 regions. A notable feature of reporting district, individual field, and yield trial data was their variability. At reporting district level within regions, contributions of spatial and temporal variability were roughly similar. The mean relative contribution of the trial effect to non-error variance of the CYT data exceeded 85 percent across regions, dominating the contributions of genotype and of genotype by trial effects. We conclude that the magnitude of mean farmer/attainable [CYT] yield gaps for this crop in Argentina justifies further research aimed at reducing regional gaps; and that CYT data can be used to generate an appropriate benchmark for attainable yields. 
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