Interpretation of commercial production information: A case study of lulo (Solanum quitoense), an under-researched Andean fruit

Jiménez, Daniel; Cock, James H.; Jarvis, Andy; García, Jorge Alberto Osuna; Satizábal, Héctor F.; Damme, Patrick Van; Pérez-Uribe, Andrés; Barreto-Sanz, Miguel Arturo

doi:10.1016/j.agsy.2010.10.004

Cited by 21 publications

(13 citation statements)

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“…Expert opinion on its own is appropriate for defining HEs in those crops which have been well researched, but in the case of less well researched crops their performance over a range of conditions can guide the delimitation of HEs [ 3 , 27 , 28 ]. In sugarcane, ( Saccharum officinarum ) and coffee ( Coffea arabica) , a wealth of knowledge about the crops, generated through formal experiments and informal experiences, equipped researchers and growers with information to define the NCFs (e.g., climate), CFs (e.g., specific management approaches), likely to influence production [ 3 , 42 , 70 ].…”

Section: Discussionmentioning

confidence: 99%

“…For Andean blackberry ( Rubus glaucus ) and lulo ( Solanum quitoense ) there was less formal knowledge regarding the likely influence of specific environmental conditions on crop responses, nor was there as much detailed knowledge regarding the functional relationships between processes that may be linked to crop performance. In those crops, with limited formal knowledge of the relevance of the variables that describe non-controllable factors, a mix of expert guidance and automated processing appear to be an effective approach that takes advantages of the synergies between expert knowledge and standardized statistical procedures [ 28 ].…”

Section: Discussionmentioning

confidence: 99%

“…Previous studies suggested that the most effective means of analyzing data obtained from multiple sources, including field observations, is as follows: first, clustering production within homologous groups for NCFs, and secondly, looking for yield variation within each cluster [ 3 , 26 , 28 , 42 ]. The homologous groups, denoted as Homologous Events (HEs), occur, in both space and time.…”

Section: Methodsmentioning

confidence: 99%

“…Mixed models combined with Generalized Least Squares (GLS) were chosen given their ability to: (a) provide a quantitative estimate of the effects of CFs on yield within a hierarchical framework of clusters of HE; (b) estimate the dependencies between the independent and dependent variables; (c) keep the initial units of the dependent variable, which in our case is fruit yield; and (d) handle datasets with both continuous and categorical variables. These techniques were chosen and used on the same pragmatic basis followed by several researchers [ 26 , 28 , 63 – 66 ]. The method has been be used to compare the performance of varieties grown under a range of conditions in commercial fields with all varieties not being grown at all sites [ 63 , 64 , 67 ].…”

Section: Methodsmentioning

confidence: 99%

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From Observation to Information: Data-Driven Understanding of on Farm Yield Variation

et al. 2016

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Agriculture research uses “recommendation domains” to develop and transfer crop management practices adapted to specific contexts. The scale of recommendation domains is large when compared to individual production sites and often encompasses less environmental variation than farmers manage. Farmers constantly observe crop response to management practices at a field scale. These observations are of little use for other farms if the site and the weather are not described. The value of information obtained from farmers’ experiences and controlled experiments is enhanced when the circumstances under which it was generated are characterized within the conceptual framework of a recommendation domain, this latter defined by Non-Controllable Factors (NCFs). Controllable Factors (CFs) refer to those which farmers manage. Using a combination of expert guidance and a multi-stage analytic process, we evaluated the interplay of CFs and NCFs on plantain productivity in farmers’ fields. Data were obtained from multiple sources, including farmers. Experts identified candidate variables likely to influence yields. The influence of the candidate variables on yields was tested through conditional forests analysis. Factor analysis then clustered harvests produced under similar NCFs, into Homologous Events (HEs). The relationship between NCFs, CFs and productivity in intercropped plantain were analyzed with mixed models. Inclusion of HEs increased the explanatory power of models. Low median yields in monocropping coupled with the occasional high yields within most HEs indicated that most of these farmers were not using practices that exploited the yield potential of those HEs. Varieties grown by farmers were associated with particular HEs. This indicates that farmers do adapt their management to the particular conditions of their HEs. Our observations confirm that the definition of HEs as recommendation domains at a small-scale is valid, and that the effectiveness of distinct management practices for specific micro-recommendation domains can be identified with the methodologies developed.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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From Observation to Information: Data-Driven Understanding of on Farm Yield Variation

et al. 2016

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“…Este se cultiva exclusivamente en zonas tropicales donde se produce normalmente durante todo el año, con una gran variabilidad en el rendimiento en el espacio y el tiempo. Para el caso de colombiano, el cultivo es en condiciones muy heterogéneas (Jiménez et al, 2011). El fruto es de color verde, cuando está viche y varia de amarillo a rojo opaco cuando alcanza la madurez fisiológica, su epidermis es fina, suave y contiene cuatro celdas llenas de semillas envueltas en un mucílago claro, con un número promedio de 800 semillas por fruto, ésta tiene un pH acido entre 3,5 a 4,5, y puede llegar a 8 cm de diámetro y de 4 a 6 cm de largo, con un peso promedio de 180 a 320 gramos (Arrázola, 1997).…”

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Evaluación fisicoquímica y microbiológica del aperitivo vínico de lulo (Solanum quitoense L.)

et al. 2013

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ResumenSe ha estudiado una formulación que incluye pulpa de lulo con el fin de aprovechar este fruto para la obtención de aperitivos vínicos. Se utilizó la siguiente formulación: Pulpa de lulo (1%), agua (80,5%), azúcar (18%), ácido cítrico (0,03%), fosfato diamónico (0,03%) y levadura (0,42%). Los análisis microbiológicos realizados estuvieron dentro de los rangos permitidos. La fermentación se detuvo a los diez días, y luego se determinaron análisis fisicoquímicos. Posteriormente se clarificó durante cinco días. La acidez titulable fue de 0,06%, la acidez volátil de 0,11% y el pH de 3,24. Se obtuvo una bebida con un contenido alcohólico de 11,3 grados (°GL), lo cual es suficiente para ser considerada como un aperitivo vínico de calidad comparable con la de los productos existentes en el mercado. El rendimiento para la pulpa fue de 66,7%. Palabras clave: aperitivo vínico, pulpa de lulo, fermentación, grados de alcohol Physicochemical and microbiological evaluation vinous of pineapple appetizer (Solanum quitoense L.)Abstract A formulation including lulo pulp aiming to use this fruit to produce vinous snacks was studied. The following formulation was employed: Lulo pulp (1%), water (80.5%), sugar (18%), citric acid (0.03%), diammonium phosphate (0.03%) and yeast (0.42%). Microbiological analyzes were performed and were found within allowable ranges. The fermentation was stopped after ten days, and then physicochemical analyses were done. After that the product was clarified during five days. Titratable acidity was 0.06%, volatile acidity was 0.11% and pH 3.24. A beverage with an alcohol content of 11,3 percent alcohol (°GL) was obtained. This alcoholic level is enough to be considered as a vinous appetizer of quality comparable to existing products. The yield for the pulp was 66.7%.

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Response of Perennial Horticultural Crops to Climate Change

Glenn

Kim

Ramírez-Villegas

et al. 2013

Horticultural Reviews Volume 41

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Interpretation of commercial production information: A case study of lulo (Solanum quitoense), an under-researched Andean fruit

Cited by 21 publications

References 49 publications

From Observation to Information: Data-Driven Understanding of on Farm Yield Variation

From Observation to Information: Data-Driven Understanding of on Farm Yield Variation

Evaluación fisicoquímica y microbiológica del aperitivo vínico de lulo (Solanum quitoense L.)

Response of Perennial Horticultural Crops to Climate Change

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