Analysis of Andean blackberry (Rubus glaucus) production models obtained by means of artificial neural networks exploiting information collected by small-scale growers in Colombia and publicly available meteorological data

The Andean blackberry (Rubus glaucus) is an important source of income in hillside regions of Colombia. However, growers have little reliable information on the factors that affect the development and yield of the crop, and therefore there is a dearth of information onhowto effectively manage the crop. Site specific information recorded by small-scale producers of the Andean blackberry on their production systems and soils coupled with publicly available meteorological data was used to develop models of such production systems. Multilayer perceptrons and Self-Organizing Maps were used as computational models in the identification and visualization of the most important variables for modeling the production of Andean blackberry. Artificial neural networks were trained with information from 20 sites in Colombia where the Andean blackberry is cultivated. Multilayer perceptrons predicted with a reasonable degree of accuracy the production response of the crop. The soil depth, the average temperature, external drainage, and the accumulated precipitation of the first month before harvest were critical determinants of productivity. A proxy variable of location was used to describe overall differences in management between farmers groups. The use of this proxy indicated that, even under essentially similar environmental conditions, large differences in production could be assigned to management effects. The information obtained can be used to determine sites that are suitable for Andean blackberry production, and to transfer ofmanagement practices from sites of high productivity to sites with similar environmental conditions which currently have lower levels of productivity.

Saved in:
Bibliographic Details
Main Authors: Jiménez, D., Cock, James H., Satizábal, H.F., Barreto Sáenz, MA, Pérez Uribe, A., Jarvis, Andy, Damme, Patrick van
Format: Journal Article biblioteca
Language:English
Published: 2009
Subjects:mulberries, rubus, hillsides, meteorology, cultivation, production, small farms, computer applications, mora, meteorología, laderas, cultivo, producción, explotación en pequeña escala, aplicaciones del ordenador,
Online Access:https://hdl.handle.net/10568/43181
http://ciat-library.ciat.cgiar.org/Articulos_Ciat/RF_Andy_Jarvis_James%20Cock_2009.pdf
Tags: Add Tag
No Tags, Be the first to tag this record!
id dig-cgspace-10568-43181
record_format koha
spelling dig-cgspace-10568-431812023-03-14T19:22:10Z Analysis of Andean blackberry (Rubus glaucus) production models obtained by means of artificial neural networks exploiting information collected by small-scale growers in Colombia and publicly available meteorological data Jiménez, D. Cock, James H. Satizábal, H.F. Barreto Sáenz, MA Pérez Uribe, A. Jarvis, Andy Damme, Patrick van mulberries rubus hillsides meteorology cultivation production small farms computer applications mora meteorología laderas cultivo producción explotación en pequeña escala aplicaciones del ordenador The Andean blackberry (Rubus glaucus) is an important source of income in hillside regions of Colombia. However, growers have little reliable information on the factors that affect the development and yield of the crop, and therefore there is a dearth of information onhowto effectively manage the crop. Site specific information recorded by small-scale producers of the Andean blackberry on their production systems and soils coupled with publicly available meteorological data was used to develop models of such production systems. Multilayer perceptrons and Self-Organizing Maps were used as computational models in the identification and visualization of the most important variables for modeling the production of Andean blackberry. Artificial neural networks were trained with information from 20 sites in Colombia where the Andean blackberry is cultivated. Multilayer perceptrons predicted with a reasonable degree of accuracy the production response of the crop. The soil depth, the average temperature, external drainage, and the accumulated precipitation of the first month before harvest were critical determinants of productivity. A proxy variable of location was used to describe overall differences in management between farmers groups. The use of this proxy indicated that, even under essentially similar environmental conditions, large differences in production could be assigned to management effects. The information obtained can be used to determine sites that are suitable for Andean blackberry production, and to transfer ofmanagement practices from sites of high productivity to sites with similar environmental conditions which currently have lower levels of productivity. 2009 2014-09-24T08:41:44Z 2014-09-24T08:41:44Z Journal Article 0168-1699 https://hdl.handle.net/10568/43181 http://ciat-library.ciat.cgiar.org/Articulos_Ciat/RF_Andy_Jarvis_James%20Cock_2009.pdf en Open Access application/pdf Computers and Electronics in Agriculture
institution CGIAR
collection DSpace
country Francia
countrycode FR
component Bibliográfico
access En linea
databasecode dig-cgspace
tag biblioteca
region Europa del Oeste
libraryname Biblioteca del CGIAR
language English
topic mulberries
rubus
hillsides
meteorology
cultivation
production
small farms
computer applications
mora
meteorología
laderas
cultivo
producción
explotación en pequeña escala
aplicaciones del ordenador
mulberries
rubus
hillsides
meteorology
cultivation
production
small farms
computer applications
mora
meteorología
laderas
cultivo
producción
explotación en pequeña escala
aplicaciones del ordenador
spellingShingle mulberries
rubus
hillsides
meteorology
cultivation
production
small farms
computer applications
mora
meteorología
laderas
cultivo
producción
explotación en pequeña escala
aplicaciones del ordenador
mulberries
rubus
hillsides
meteorology
cultivation
production
small farms
computer applications
mora
meteorología
laderas
cultivo
producción
explotación en pequeña escala
aplicaciones del ordenador
Jiménez, D.
Cock, James H.
Satizábal, H.F.
Barreto Sáenz, MA
Pérez Uribe, A.
Jarvis, Andy
Damme, Patrick van
Analysis of Andean blackberry (Rubus glaucus) production models obtained by means of artificial neural networks exploiting information collected by small-scale growers in Colombia and publicly available meteorological data
description The Andean blackberry (Rubus glaucus) is an important source of income in hillside regions of Colombia. However, growers have little reliable information on the factors that affect the development and yield of the crop, and therefore there is a dearth of information onhowto effectively manage the crop. Site specific information recorded by small-scale producers of the Andean blackberry on their production systems and soils coupled with publicly available meteorological data was used to develop models of such production systems. Multilayer perceptrons and Self-Organizing Maps were used as computational models in the identification and visualization of the most important variables for modeling the production of Andean blackberry. Artificial neural networks were trained with information from 20 sites in Colombia where the Andean blackberry is cultivated. Multilayer perceptrons predicted with a reasonable degree of accuracy the production response of the crop. The soil depth, the average temperature, external drainage, and the accumulated precipitation of the first month before harvest were critical determinants of productivity. A proxy variable of location was used to describe overall differences in management between farmers groups. The use of this proxy indicated that, even under essentially similar environmental conditions, large differences in production could be assigned to management effects. The information obtained can be used to determine sites that are suitable for Andean blackberry production, and to transfer ofmanagement practices from sites of high productivity to sites with similar environmental conditions which currently have lower levels of productivity.
format Journal Article
topic_facet mulberries
rubus
hillsides
meteorology
cultivation
production
small farms
computer applications
mora
meteorología
laderas
cultivo
producción
explotación en pequeña escala
aplicaciones del ordenador
author Jiménez, D.
Cock, James H.
Satizábal, H.F.
Barreto Sáenz, MA
Pérez Uribe, A.
Jarvis, Andy
Damme, Patrick van
author_facet Jiménez, D.
Cock, James H.
Satizábal, H.F.
Barreto Sáenz, MA
Pérez Uribe, A.
Jarvis, Andy
Damme, Patrick van
author_sort Jiménez, D.
title Analysis of Andean blackberry (Rubus glaucus) production models obtained by means of artificial neural networks exploiting information collected by small-scale growers in Colombia and publicly available meteorological data
title_short Analysis of Andean blackberry (Rubus glaucus) production models obtained by means of artificial neural networks exploiting information collected by small-scale growers in Colombia and publicly available meteorological data
title_full Analysis of Andean blackberry (Rubus glaucus) production models obtained by means of artificial neural networks exploiting information collected by small-scale growers in Colombia and publicly available meteorological data
title_fullStr Analysis of Andean blackberry (Rubus glaucus) production models obtained by means of artificial neural networks exploiting information collected by small-scale growers in Colombia and publicly available meteorological data
title_full_unstemmed Analysis of Andean blackberry (Rubus glaucus) production models obtained by means of artificial neural networks exploiting information collected by small-scale growers in Colombia and publicly available meteorological data
title_sort analysis of andean blackberry (rubus glaucus) production models obtained by means of artificial neural networks exploiting information collected by small-scale growers in colombia and publicly available meteorological data
publishDate 2009
url https://hdl.handle.net/10568/43181
http://ciat-library.ciat.cgiar.org/Articulos_Ciat/RF_Andy_Jarvis_James%20Cock_2009.pdf
work_keys_str_mv AT jimenezd analysisofandeanblackberryrubusglaucusproductionmodelsobtainedbymeansofartificialneuralnetworksexploitinginformationcollectedbysmallscalegrowersincolombiaandpubliclyavailablemeteorologicaldata
AT cockjamesh analysisofandeanblackberryrubusglaucusproductionmodelsobtainedbymeansofartificialneuralnetworksexploitinginformationcollectedbysmallscalegrowersincolombiaandpubliclyavailablemeteorologicaldata
AT satizabalhf analysisofandeanblackberryrubusglaucusproductionmodelsobtainedbymeansofartificialneuralnetworksexploitinginformationcollectedbysmallscalegrowersincolombiaandpubliclyavailablemeteorologicaldata
AT barretosaenzma analysisofandeanblackberryrubusglaucusproductionmodelsobtainedbymeansofartificialneuralnetworksexploitinginformationcollectedbysmallscalegrowersincolombiaandpubliclyavailablemeteorologicaldata
AT perezuribea analysisofandeanblackberryrubusglaucusproductionmodelsobtainedbymeansofartificialneuralnetworksexploitinginformationcollectedbysmallscalegrowersincolombiaandpubliclyavailablemeteorologicaldata
AT jarvisandy analysisofandeanblackberryrubusglaucusproductionmodelsobtainedbymeansofartificialneuralnetworksexploitinginformationcollectedbysmallscalegrowersincolombiaandpubliclyavailablemeteorologicaldata
AT dammepatrickvan analysisofandeanblackberryrubusglaucusproductionmodelsobtainedbymeansofartificialneuralnetworksexploitinginformationcollectedbysmallscalegrowersincolombiaandpubliclyavailablemeteorologicaldata
_version_ 1779064962689269760