2018
DOI: 10.1590/1807-1929/agriambi.v22n5p315-319
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Prediction of ‘Gigante’ cactus pear yield by morphological characters and artificial neural networks

Abstract: Estimating cactus pear yield is important for the planning of small and medium rural producers, especially in environments with adverse climatic conditions, such as the Brazilian semi-arid region. The objective of this study was to evaluate the potential of artificial neural networks (ANN) for predicting yield of ‘Gigante’ cactus pear, and determine the most important morphological characters for this prediction. The experiment was conducted in the Instituto Federal Baiano, Guanambi campus, Bahia, Brazil, in 2… Show more

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Cited by 16 publications
(26 citation statements)
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References 13 publications
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“…Lucena et al (2018b) observed that, independent of the cladode order, the area of Elephant-Mexican clone (O. stricta) presented a positive correlation (r) with the product of length by width with a magnitude of 0.90. Guimarães, Donato, Azevedo, Aspiazú, and Silva Jr. (2018) also verified a positive correlation of weight with the cladode area of 0.86 in O. ficus-indica. Evaluating the relationship between the RCA and LW of the primary cladodes verified that the linear regression model presented an explanatory power (R²) of 98.55%, while the power model had an R 2 of 99.97%, and the gamma model had an explanatory power of 99.52% (Table 4) (Table 4).…”
Section: Resultssupporting
confidence: 61%
“…Lucena et al (2018b) observed that, independent of the cladode order, the area of Elephant-Mexican clone (O. stricta) presented a positive correlation (r) with the product of length by width with a magnitude of 0.90. Guimarães, Donato, Azevedo, Aspiazú, and Silva Jr. (2018) also verified a positive correlation of weight with the cladode area of 0.86 in O. ficus-indica. Evaluating the relationship between the RCA and LW of the primary cladodes verified that the linear regression model presented an explanatory power (R²) of 98.55%, while the power model had an R 2 of 99.97%, and the gamma model had an explanatory power of 99.52% (Table 4) (Table 4).…”
Section: Resultssupporting
confidence: 61%
“…Correlations between morphometric characteristics of forage cactus cladodes are known to be positively correlated, a fact that can be found in the reports of Cunha et al (2012) Little Sweet clone, Lucena et al (2019a) in N. cochenillifera Giant Sweet clone (r > 0.95), Lucena et al (2018a) in Opuntia stricta ( = 0.90), Reis, Gazarini, Fonseca, and Ribeiro (2018), ( = 0.95) in Opuntia ficus-indica correlating real cladode area with product of length by width and Guimarães, Donato, Azevedo, Aspiazú, and Silva Junior (2018) in Opuntia ficus-indica verified a positive correlation of weight with the cladode area of 0.86. Fisher's discriminant function was defined by Equation 8:…”
Section: Resultsmentioning
confidence: 68%
“…The development of high-efficiency models obtained from the original field conditions favors safety when predicting 'Gigante' cactus pear yield (Guimarães et al, 2018), which contributes to the success of rural planning, especially as a support to the producer who needs to define in advance the quantity of animals to be fed with the produced biomass or even the volume to be marketed (Marques et al, 2017). models predictive models with superior performance compared to validated conventional tools (Arruda et al, 2013;Leal et al, 2015;Kaytez et al, 2015).…”
Section: Resultsmentioning
confidence: 99%
“…For Amania et al (2019), this productive potential is associated with several mechanisms of adaptation of the crop to the adverse conditions in which the species is normally conducted. construct predictive models that minimize the effects of the productive uncertainties or the risk associated with the activity in the field (Guimarães et al, 2018).…”
Section: Introductionmentioning
confidence: 99%