Resumo O objetivo deste trabalho foi o aprimoramento da classificação de aspargos verdes em uma empresa agroexportadora, mediante um Sistema de Visão Computacional (SVC). Para isso, um aplicativo de análise de imagens foi desenvolvido no MATLAB®, para a classificação de aspargos verdes, segundo a ausência de machas brancas e a largura do produto. O desempenho do SVC foi comparado com a classificação manual usando o erro na classificação como indicador de qualidade. O rendimento da matéria-prima (%), a produtividade da linha (kg/h), o valor presente líquido (USD) e a taxa interna de retorno (%) foram utilizados como indicadores econômicos. O SVC classificou o aspargo verde com 2% de erro, incrementou o rendimento da matéria-prima de 43% para 45% e a produtividade da linha de 5 para 10 kg/h, bem como aumentou o valor presente líquido em 102.609,00 USD, rendendo uma taxa interna de retorno de 156,3%, muito superior ao custo de oportunidade do capital (8,6%). Assim, a classificação de aspargos verdes mediante um CVS é uma alternativa eficiente e rentável quando comparada à classificação manual.

Abstract The aim of this work was to improve the classification of green asparagus in an agro-export company by way of a Computer Vision System (CVS). Thus, an image analysis application was developed in the MATLAB® environment to classify green asparagus according to the absence of white spots and the width of the product. The CVS performance was compared with a manual classification using the error in the classification as the quality indicator; the yield from the raw material (%) and line productivity (kg/h) as the production indicators; and the net present value (USD) and internal rate of return (%) as the economic indicators. The CVS classified the green asparagus with 2% error; improved the yield from the raw material from 43% to 45%, and line productivity from 5 to 10 kg/h; and increased the net present value by 102,609.00 USD, yielding an Internal Rate of Return of 156.3%, much higher than the Opportunity Cost of the Capital (8.6%). Hence the classification of green asparagus by a CVS is an efficient and profitable alternative to manual classification.

The aim of this study was to build a model to predict the beef marbling using HSI and Partial Least Squares Regression (PLSR). Totally 58 samples of longissmus dorsi muscle were scanned by a HSI system (400 - 1000 nm) in reflectance mode, using 44 samples to build the PLSR model and 14 samples to model validation. The Japanese Beef Marbling Standard (BMS) was used as reference by 15 middle-trained judges for the samples evaluation. The scores were assigned as continuous values and varied from 1.2 to 5.3 BMS. The PLSR model showed a high correlation coefficient in the prediction (r = 0.95), a low Standard Error of Calibration (SEC) of 0.2 BMS score, and a low Standard Error of Prediction (SEP) of 0.3 BMS score

Abstract: The aim of this study was to optimize the sensory acceptability (SA) of an andean sweet bread made with different percentages of wheat flour (WF), quinoa flour (QF) and sugar (S) was optimized through Simplex-Centroid Design (SCD) and Desirability Function (DF). Ten treatments were performed, in which the mixture of different percentages of WF (28% - 52.5%), QF (0% - 24.5%) and S (17.5% - 42%) accounted for 70% of the dough formula. The evaluation of the SA was conducted in triplicate with 20 consumer panelists of sweet bread, applying an unstructured scale from 0 to 10. Statistical analysis of SCD reported that a cubic model successfully explained the effect of WF, QF and S on SA (p = 0.0529 ≈ 0.05 and R2 = 94.49%), analyzing the response surface was observed that the ranges of the percentage that optimize the SA were: 35.35% - 41.97% of WF, 7.11% - 11.03% QF and 20.44% - 24.61% of S. By DF was determined that the percentages that optimize the SA were: 40.25% of WF, 9.05% QF and 20.70% of S.

Resumen: El objetivo de este trabajo fue optimizar la aceptabilidad sensorial (AS) de pan dulce (bizcocho andino) elaborado con diferentes porcentajes de harina de trigo (HT), harina de quinua (HQ) y azúcar (A) mediante Diseño Simplex-Centroide (DSC) y Función de Deseabilidad (FD). Se realizaron 10 tratamientos, en los cuales la mezcla de diferentes porcentajes de HT (28% - 52.5%), HQ (0% - 24.5%) y A (17.5% - 42%) representaron el 70% de la formulación. La evaluación de la AS fue realizada por triplicado con 20 panelistas consumidores aplicando una escala no estructurada (0 a 10). El análisis estadístico del DSC reportó que un modelo cúbico explicó satisfactoriamente el efecto de HT, HQ y A en la AS (p = 0.0529 ≈ 0.05 y R2 = 94.49%), en la superficie de respuesta se observó que los rangos porcentuales que optimizaron la AS fueron: 35.35% - 41.97% de HT, 7.11% - 11.03% de HQ y 20.44% - 24.61% de A. Mediante FD se determinó que los porcentajes que optimizaron la AS fueron: 40.25% de HT, 9.05% de HQ y 20.70% de A.

Two types of skimmed (fat 3%) goat’s milk fruit yogurt with mango (YM) and banana (YB) were stored at temperatures of 5 °C, 15 °C and 25 °C for 72 hours. Every 24 hours the pH, titratable acidity, total solids, fat and protein were analyzed. Sensory acceptability was also evaluated with 75 yogurt frequent consumers, who responded with "yes" or "no" to the question ¿would you consume this product? At the beginning pH, acidity, total solids, fat and protein were 4.35 and 4.36; 0.76% and 0.75%; 12.71% and 13.23%; 3.2% and 3.3%; 4.4% and 4.5%, for the YM and YB respectively, meeting known standards for cow's milk yogurt: range of acidity 0.5%-1.6%, fat maximum value 15% and protein minimum value 2.7%. The sensory acceptability of the YM and the YB was high, with 88.9% and 94.7%, respectively. During storage under accelerated conditions, pH decreased to 3.88 and 3.92; titrable acidity increased to 1.1% and 0.93%; total solids, fat and protein decreased to 9.37% and 9.7%; 2.4% and 2.0%; 2.5% and 2.6%, for the YM and YB respectively, while remaining within the limits of the standards consulted. The sensory acceptability decreased to 4% and 5.33% for YM and YB respectively. Therefore the shelf life of the sensory acceptability was estimated (S.S.A) at 4°C in a rejection percentage of 25% and 50%, 69 and 49 h; 193 and 111 h, for the YM and YB respectively.

Dos tipos de yogur de leche descremada de cabra (3% de grasa) frutado con mango (YM) y plátano (YP) fueron almacenados a temperaturas de 5 °C, 15 °C y 25 °C durante 72 horas. Cada 24 horas se analizó el pH, acidez titulable, sólidos totales, grasa y proteína. Asimismo se evaluó la aceptabilidad sensorial con 75 consumidores habituales de yogur, que respondieron con “sí” o “no” a la pregunta ¿consumiría este producto?. Al inicio, el pH, acidez, sólidos totales, grasa y proteína fue 4,35 y 4,36; 0,76% y 0,75%; 12,71% y 13,23%; 3,2% y 3,3%; 4,4% y 4,5%, respectivamente para el YM y el YP, cumpliendo con normas conocidas para yogur de leche de vaca: rango de acidez 0,5%-1,6%, grasa valor máximo 15% y proteína valor mínimo 2,7%. La aceptabilidad sensorial del YM y el YP fue alta, con 88,9% y 94,7%, respectivamente. Durante el almacenamiento en condiciones aceleradas, el pH disminuyó hasta 3,88 y 3,92; la acidez titulable aumentó hasta 1,1% y 0,93%; los sólidos totales, grasa y proteína disminuyeron hasta 9,37% y 9,7%; 2,4% y 2,0%; 2,5% y 2,6%, respectivamente para el YM y el YP, permaneciendo dentro de los límites de las normas consultadas. La aceptabilidad sensorial disminuyó hasta 4% y 5,33% para el YM y el YP respectivamente. Estimando así la vida útil de la aceptabilidad sensorial (V.U.A.S.) a 4ºC en 69 y 49 h (para un porcentaje de rechazo de 25%), 193 y 111 h (para un porcentaje de rechazo de 50%) para el YM y el YP respectivamente.