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- Title
La espectroscopía de infrarrojo cercano (NIRS) en el seguimiento de la madurez del cultivo de la caña de azúcar (Saccharum spp.).
- Authors
López Hernández, Oscar; Salgado García, Sergio; Hernández Nataren, Edith; Lagunes Espinoza, Luz del Carmen; Contreras Oliva, Adriana; Córdova Sanchez, Samuel; Romero, Eduardo R.; Zossi, Silvia
- Abstract
Objective: To determine the viability of the near infrared spectroscopy methodology to estimate the maturity of sugarcane (Saccharum spp.). Design/methodology/approximation: The management of the parameters to evaluate the maturity were the total soluble solids (°Brix) and Pol (%). This work was carried out at the Obispo Colombres Agroindustrial Experimental Station in Tucumán, Argentina, where 1265 juice samples were collected from sugar cane in the laboratory, where the total soluble solids (°Brix) and Pol (%) were examined with the usual methods and to obtain the spectra of the juice samples, the near infrared spectrophotometer FOSS NIR Systems model 6500 for liquids was used. And the prediction model for °Brix and Pol (%) in juices, was generated from the mathematical treatment SNV and Detrend and arrangements 1,4,4,1 and 2,4,4,1 (derived, GAP and smoothed, respectively). Results: The prediction models generated for °Brix and Pol (%) have standard calibration error values (SEC) of 0.126 and 0.296; standard prediction error (SEP) of 0.181 and 0.327; and calibration correlation coefficient (R2) of 0.997 and 0.991, respectively. Limitations/implications: The study was carried out at the Obispo Colombres Agroindustrial Experimental Station in Tucumán, Argentina, for reasons of logistics between Public and Private Institutions in Mexico. Findings/Conclusions: These results indicate that the models developed for °Brix and Pol (%) can be used as a cheaper alternative to conventional procedures in the determination of maturity since it improves the speed in the determinations, does not use chemical reagents and requires less workforce.
- Subjects
MEXICO; NEAR infrared spectroscopy; CHEMICAL reagents; SUGAR; PREDICTION models; STATISTICAL correlation; SUGARCANE
- Publication
Agro Productividad, 2019, Vol 12, Issue 7, p107
- ISSN
2448-7546
- Publication type
Article
- DOI
10.32854/agrop.v0i0.1477