Modelling inter-annual variation in dry matter yield and precipitation use efficiency of perennial pastures and annual forage crops sequences

In livestock systems of the Argentinean Pampas, its forage production stability relies on the integration of two landcovers, annual forage crop sequences and perennial pastures. Despite the key role that these forage cropping systems have on current milk and beef production, it is unclear how year-by-year variability of precipitation affect forage dry matter (DM) yield and precipitation use efficiency (PUE, i.e. the quotient between forage DM yield and precipitation). The aims of this study were to analyze the impact (i) of year-by-year precipitation variability on DM yield and PUE of oats-maize (Avena sativa L. - Zea mays L.) double-crop and alfalfa (Medicago sativa L.) and (ii) of cumulative precipitation during the critical period of maize on DM yield and PUE of oatsmaize double-crop. We used a modelling approach to estimate DM yield and PUE of oats-maize (sequence) and alfalfa in five locations of the Argentinean Pampas, which differed in annual precipitation (AP) and variability of it. Coefficient of variation (CV) was used as the main statistical variable to compare the variability of AP (CVAP), DM yield (CVDM), and PUE (CVPUE). Mean DM yield of both landcovers was higher in locations with high AP (> 800 mm) than with low AP (< 800 mm). Although alfalfa had lower mean DM yield than sequence in all locations, it showed a lower CVDM than sequence. In contrast, sequence showed lower and higher CVDM than CVAP, depending on location. Moreover, changes in DM yield due to variations of AP were higher in sequence than in alfalfa. On the other hand, mean PUE was higher for sequence (2.2 g DM m−2mm−1) than that of alfalfa (1.6 g DM m−2mm−1). The CVPUE between locations, i.e. an index that reflects the spatial variability, ranged from 20 for the sequence to 68% for alfalfa, whereas CVPUE between years, i.e. an index that reflects the temporal variability, ranged from 16 to 31 % for both landcovers. Precipitation use efficiency tended to be similar across locations in years with low AP (< 800 mm) compared to years with high AP (> 800 mm). Our results provided valuable knowledge for decision making in livestock systems of this region through the development of spatial and temporal models between DM yield and AP. In a broader sense, they also showed that shifts from perennial to seasonal forage covers increased yields but also its inter-annual variability, posing a risk for farmers.

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Bibliographic Details
Main Authors: Ojeda, Jonathan Jesus, Caviglia, Octavio, Irisarri, Jorge Gonzalo Nicolás, Agnusdei, Monica Graciela
Format: info:ar-repo/semantics/artículo biblioteca
Language:eng
Published: 2018
Subjects:Pastizal Permanente, Plantas Forrajeras, Modelos de Simulación, Maíz, Medicago Sativa, Zea Mays, Periodicidad, Periodicity, Maize, Dry Matter, Simulation Models, Feed Crops, Permanent Pastures, APSIM, Temporal Patterns, Materia Seca, Alfalfa, Región Pampena,
Online Access:http://hdl.handle.net/20.500.12123/2839
https://www.sciencedirect.com/science/article/pii/S0168192318301369?via%3Dihub
https://doi.org/10.1016/j.agrformet.2018.04.014
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record_format koha
institution INTA AR
collection DSpace
country Argentina
countrycode AR
component Bibliográfico
access En linea
databasecode dig-inta-ar
tag biblioteca
region America del Sur
libraryname Biblioteca Central del INTA Argentina
language eng
topic Pastizal Permanente
Plantas Forrajeras
Modelos de Simulación
Maíz
Medicago Sativa
Zea Mays
Periodicidad
Periodicity
Maize
Dry Matter
Simulation Models
Feed Crops
Permanent Pastures
APSIM
Temporal Patterns
Materia Seca
Alfalfa
Región Pampena
Pastizal Permanente
Plantas Forrajeras
Modelos de Simulación
Maíz
Medicago Sativa
Zea Mays
Periodicidad
Periodicity
Maize
Dry Matter
Simulation Models
Feed Crops
Permanent Pastures
APSIM
Temporal Patterns
Materia Seca
Alfalfa
Región Pampena
spellingShingle Pastizal Permanente
Plantas Forrajeras
Modelos de Simulación
Maíz
Medicago Sativa
Zea Mays
Periodicidad
Periodicity
Maize
Dry Matter
Simulation Models
Feed Crops
Permanent Pastures
APSIM
Temporal Patterns
Materia Seca
Alfalfa
Región Pampena
Pastizal Permanente
Plantas Forrajeras
Modelos de Simulación
Maíz
Medicago Sativa
Zea Mays
Periodicidad
Periodicity
Maize
Dry Matter
Simulation Models
Feed Crops
Permanent Pastures
APSIM
Temporal Patterns
Materia Seca
Alfalfa
Región Pampena
Ojeda, Jonathan Jesus
Caviglia, Octavio
Irisarri, Jorge Gonzalo Nicolás
Agnusdei, Monica Graciela
Modelling inter-annual variation in dry matter yield and precipitation use efficiency of perennial pastures and annual forage crops sequences
description In livestock systems of the Argentinean Pampas, its forage production stability relies on the integration of two landcovers, annual forage crop sequences and perennial pastures. Despite the key role that these forage cropping systems have on current milk and beef production, it is unclear how year-by-year variability of precipitation affect forage dry matter (DM) yield and precipitation use efficiency (PUE, i.e. the quotient between forage DM yield and precipitation). The aims of this study were to analyze the impact (i) of year-by-year precipitation variability on DM yield and PUE of oats-maize (Avena sativa L. - Zea mays L.) double-crop and alfalfa (Medicago sativa L.) and (ii) of cumulative precipitation during the critical period of maize on DM yield and PUE of oatsmaize double-crop. We used a modelling approach to estimate DM yield and PUE of oats-maize (sequence) and alfalfa in five locations of the Argentinean Pampas, which differed in annual precipitation (AP) and variability of it. Coefficient of variation (CV) was used as the main statistical variable to compare the variability of AP (CVAP), DM yield (CVDM), and PUE (CVPUE). Mean DM yield of both landcovers was higher in locations with high AP (> 800 mm) than with low AP (< 800 mm). Although alfalfa had lower mean DM yield than sequence in all locations, it showed a lower CVDM than sequence. In contrast, sequence showed lower and higher CVDM than CVAP, depending on location. Moreover, changes in DM yield due to variations of AP were higher in sequence than in alfalfa. On the other hand, mean PUE was higher for sequence (2.2 g DM m−2mm−1) than that of alfalfa (1.6 g DM m−2mm−1). The CVPUE between locations, i.e. an index that reflects the spatial variability, ranged from 20 for the sequence to 68% for alfalfa, whereas CVPUE between years, i.e. an index that reflects the temporal variability, ranged from 16 to 31 % for both landcovers. Precipitation use efficiency tended to be similar across locations in years with low AP (< 800 mm) compared to years with high AP (> 800 mm). Our results provided valuable knowledge for decision making in livestock systems of this region through the development of spatial and temporal models between DM yield and AP. In a broader sense, they also showed that shifts from perennial to seasonal forage covers increased yields but also its inter-annual variability, posing a risk for farmers.
format info:ar-repo/semantics/artículo
topic_facet Pastizal Permanente
Plantas Forrajeras
Modelos de Simulación
Maíz
Medicago Sativa
Zea Mays
Periodicidad
Periodicity
Maize
Dry Matter
Simulation Models
Feed Crops
Permanent Pastures
APSIM
Temporal Patterns
Materia Seca
Alfalfa
Región Pampena
author Ojeda, Jonathan Jesus
Caviglia, Octavio
Irisarri, Jorge Gonzalo Nicolás
Agnusdei, Monica Graciela
author_facet Ojeda, Jonathan Jesus
Caviglia, Octavio
Irisarri, Jorge Gonzalo Nicolás
Agnusdei, Monica Graciela
author_sort Ojeda, Jonathan Jesus
title Modelling inter-annual variation in dry matter yield and precipitation use efficiency of perennial pastures and annual forage crops sequences
title_short Modelling inter-annual variation in dry matter yield and precipitation use efficiency of perennial pastures and annual forage crops sequences
title_full Modelling inter-annual variation in dry matter yield and precipitation use efficiency of perennial pastures and annual forage crops sequences
title_fullStr Modelling inter-annual variation in dry matter yield and precipitation use efficiency of perennial pastures and annual forage crops sequences
title_full_unstemmed Modelling inter-annual variation in dry matter yield and precipitation use efficiency of perennial pastures and annual forage crops sequences
title_sort modelling inter-annual variation in dry matter yield and precipitation use efficiency of perennial pastures and annual forage crops sequences
publishDate 2018
url http://hdl.handle.net/20.500.12123/2839
https://www.sciencedirect.com/science/article/pii/S0168192318301369?via%3Dihub
https://doi.org/10.1016/j.agrformet.2018.04.014
work_keys_str_mv AT ojedajonathanjesus modellinginterannualvariationindrymatteryieldandprecipitationuseefficiencyofperennialpasturesandannualforagecropssequences
AT cavigliaoctavio modellinginterannualvariationindrymatteryieldandprecipitationuseefficiencyofperennialpasturesandannualforagecropssequences
AT irisarrijorgegonzalonicolas modellinginterannualvariationindrymatteryieldandprecipitationuseefficiencyofperennialpasturesandannualforagecropssequences
AT agnusdeimonicagraciela modellinginterannualvariationindrymatteryieldandprecipitationuseefficiencyofperennialpasturesandannualforagecropssequences
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spelling oai:localhost:20.500.12123-28392018-07-20T14:30:42Z Modelling inter-annual variation in dry matter yield and precipitation use efficiency of perennial pastures and annual forage crops sequences Ojeda, Jonathan Jesus Caviglia, Octavio Irisarri, Jorge Gonzalo Nicolás Agnusdei, Monica Graciela Pastizal Permanente Plantas Forrajeras Modelos de Simulación Maíz Medicago Sativa Zea Mays Periodicidad Periodicity Maize Dry Matter Simulation Models Feed Crops Permanent Pastures APSIM Temporal Patterns Materia Seca Alfalfa Región Pampena In livestock systems of the Argentinean Pampas, its forage production stability relies on the integration of two landcovers, annual forage crop sequences and perennial pastures. Despite the key role that these forage cropping systems have on current milk and beef production, it is unclear how year-by-year variability of precipitation affect forage dry matter (DM) yield and precipitation use efficiency (PUE, i.e. the quotient between forage DM yield and precipitation). The aims of this study were to analyze the impact (i) of year-by-year precipitation variability on DM yield and PUE of oats-maize (Avena sativa L. - Zea mays L.) double-crop and alfalfa (Medicago sativa L.) and (ii) of cumulative precipitation during the critical period of maize on DM yield and PUE of oatsmaize double-crop. We used a modelling approach to estimate DM yield and PUE of oats-maize (sequence) and alfalfa in five locations of the Argentinean Pampas, which differed in annual precipitation (AP) and variability of it. Coefficient of variation (CV) was used as the main statistical variable to compare the variability of AP (CVAP), DM yield (CVDM), and PUE (CVPUE). Mean DM yield of both landcovers was higher in locations with high AP (> 800 mm) than with low AP (< 800 mm). Although alfalfa had lower mean DM yield than sequence in all locations, it showed a lower CVDM than sequence. In contrast, sequence showed lower and higher CVDM than CVAP, depending on location. Moreover, changes in DM yield due to variations of AP were higher in sequence than in alfalfa. On the other hand, mean PUE was higher for sequence (2.2 g DM m−2mm−1) than that of alfalfa (1.6 g DM m−2mm−1). The CVPUE between locations, i.e. an index that reflects the spatial variability, ranged from 20 for the sequence to 68% for alfalfa, whereas CVPUE between years, i.e. an index that reflects the temporal variability, ranged from 16 to 31 % for both landcovers. Precipitation use efficiency tended to be similar across locations in years with low AP (< 800 mm) compared to years with high AP (> 800 mm). Our results provided valuable knowledge for decision making in livestock systems of this region through the development of spatial and temporal models between DM yield and AP. In a broader sense, they also showed that shifts from perennial to seasonal forage covers increased yields but also its inter-annual variability, posing a risk for farmers. EEA Paraná Fil: Ojeda, Jonathan Jesus. University of Tasmania. Tasmanian Institute of Agriculture; Australia. Universidad Nacional de Entre Ríos. Facultad de Ciencias Agropecuarias; Argentina Fil: Caviglia, Octavio. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Paraná. Grupo Ecología Forestal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Entre Ríos. Facultad de Ciencias Agropecuarias; Argentina Fil: Irisarri, Jorge Gonzalo Nicolás. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; Argentina Fil: Agnusdei, Monica Graciela. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; Argentina 2018-07-20T14:06:53Z 2018-07-20T14:06:53Z 2018 info:ar-repo/semantics/artículo info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://hdl.handle.net/20.500.12123/2839 https://www.sciencedirect.com/science/article/pii/S0168192318301369?via%3Dihub 0168-1923 https://doi.org/10.1016/j.agrformet.2018.04.014 eng info:eu-repo/semantics/restrictedAccess application/pdf Agricultural and forest meteorology 259 : 1–10. (2018)