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Agronomía Mesoamericana
versão On-line ISSN 2215-3608versão impressa ISSN 1659-1321
Resumo
MORALES-HERRERA, Ileana; LOPEZ-VARGAS, Elena; FALLAS-RODRIGUEZ, Pilar e PEREZ, Ana M.. Survival or traditional statistics? Shelf life estimation of purple corn (Zea mays L.) premix. Agron. Mesoam [online]. 2024, vol.35, n.spe1, 60261. ISSN 2215-3608. http://dx.doi.org/10.15517/am.2024.60261.
Introduction.
Since the product development process is incomplete without determining its shelf life, the creation of a novel product, such as pancake premix based on purple corn flour, raised the need to determine it. Objective. To estimate the shelf life of a pancake premix made from pujagua corn flour (Zea mays L.), using linear regression analysis and survival statistics to compare both methodologies. Materials and methods. The study was conducted at the Centro Nacional de Ciencia y Tecnología de Alimentos (CITA) of the Universidad de Costa Rica, from 2018 to 2023. The pancake premix storage study was carried out with three repetitions, in a chamber at 25 °C, with control samples stored at -18 °C for 7.5 months, and nine sampling times at intervals of 26 days. Sensory variables analyzed from the pancakes were chewiness and off-flavor, while off-odor was selected for the premix. A consumers acceptance test (n=100) was conducted. Based on these results and data from a panel of judges (n=11), two shelf life values were calculated, one using the cut-off point method and the other using survival statistics. Results. The sensory variable limiting the shelf life of the premix was chewiness. The cut-off point method estimated a shelf life of 124 days, while the survival statistics method estimated 265 days at 25 °C. The cut-off point method was more conservative and sensitive to the selected critical variables, whereas the survival statistics method proved more practical. Conclusions. This study estimated the shelf life of the premix using both methodologies, demonstrating the benefits of each approach.
Palavras-chave : food storage; prediction techniques; statistical models; sensory evaluation; corn flour.












