Physicochemical properties and sensory acceptability of pineapples of different varieties and stages of maturity

Rashima, R. Siti; Murad, Maizura; Hafzan, W.M. Wan Nur; Hazzeman, H.

doi:10.26656/fr.2017.3(5).060

Cited by 24 publications

(8 citation statements)

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“…Lime and pineapple contain 27 mg/100 g and 24 mg/100 g of vitamin C, respectively, whereas citric acid does not. This result is in accordance with the work of [34], which has shown that using pineapple in jam making can increase the vitamin C content.…”

Section: Vitamin Csupporting

confidence: 93%

Processing Sky Rocket Melon into Jam with Various Acidifiers and Sugar Concentrations

Aini¹,

Setyawati²,

Alyani³

et al. 2023

Advances in Biological Sciences Research

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The high production of melons in Indonesia is affected by non-optimal post-harvest handling and the accelerated loss of quality due to its abundant water content, which reduce its economic value. The Sky Rocket variety is Indonesia's most widely grown type of melon. The post-harvest handling of melon that has not been implemented is the production of jam. The correct recipe must be determined to produce melon spread, or jam, with good characteristics. This study aims to determine the effects of the sucrose and acidifier on the physicochemical and sensory characteristics of the melon spread and to find the combination of treatments that produce the melon spread with the best physicochemical and sensory characteristics. This study used experimental methods and factorial randomized block design. The observed factors were the concentration of sucrose, 40%, 50% and 60%, and the type of acidifier, citric acid, lime and pineapple. Experiments were performed three times; thus, there were 27 experimental units. The variables observed included water content, acidity (pH), total dissolved solids and vitamin C content, as well as sensory variables such as colour, spreadability, texture, melon aroma, sweet taste and preference. The use of different concentrations of sucrose affected the water content, total dissolved solids, and sensory variables of the melon spread. The type of acidifier affected the physicochemical and sensory variables of the melon spread, except for the total dissolved solids. The interaction between the sucrose and the acidifier only affected the sensory variables. The best treatment combinations were treatment with 50% sucrose and pineapple with a water content of 31.49%, pH 6.90, TPT 71.00°Bx, vitamin C of 114.40 mg/100 g, colour 3.55 (bright green), spreadability 4.05, texture 3.12, melon aroma 3.00, sweet taste 4.23 and preference 3.43.

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Section: Vitamin Csupporting

confidence: 93%

Processing Sky Rocket Melon into Jam with Various Acidifiers and Sugar Concentrations

Aini¹,

Setyawati²,

Alyani³

et al. 2023

Advances in Biological Sciences Research

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“…The CC values of pineapples had significant differences (p < 0.05) for all origins. It can be denoted that the carotenoids' synthesis determined the progression of the orange or yellow color of the pineapple flesh [30].…”

Section: Statistical Analysis Of Chemical Datamentioning

confidence: 99%

Towards a Multispectral Imaging System for Spatial Mapping of Chemical Composition in Fresh-Cut Pineapple (Ananas comosus)

Mollazade,

Hashim,

Zude-Sasse

2023

Foods

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With increasing public demand for ready-to-eat fresh-cut fruit, the postharvest industry requires the development and adaptation of monitoring technologies to provide customers with a product of consistent quality. The fresh-cut trade of pineapples (Ananas comosus) is on the rise, favored by the sensory quality of the product and mechanization of the cutting process. In this paper, a multispectral imaging-based approach is introduced to provide distribution maps of moisture content, soluble solids content, and carotenoids content in fresh-cut pineapple. A dataset containing hyperspectral images (380–1690 nm) and reference measurements in 10 regions of interest of 60 fruit (n = 600) was prepared. Ranking and uncorrelatedness (based on ReliefF algorithm) and subset selection (based on CfsSubset algorithm) approaches were applied to find the most informative wavelengths in which bandpass optical filters or light sources are commercially available. The correlation coefficient and error metrics obtained by cross-validated multilayer perceptron neural network models indicated that the superior selected wavelengths (495, 500, 505, 1215, 1240, and 1425 nm) resulted in prediction of moisture content with R = 0.56, MAPE = 1.92%, soluble solids content with R = 0.52, MAPE = 14.72%, and carotenoids content with R = 0.63, MAPE = 43.99%. Prediction of chemical composition in each pixel of the multispectral images using the calibration models yielded spatially distributed quantification of the fruit slice, spatially varying according to the maturation of single fruitlets in the whole pineapple. Calibration models provided reliable responses spatially throughout the surface of fresh-cut pineapple slices with a constant error. According to the approach to use commercially relevant wavelengths, calibration models could be applied in classifying fruit segments in the mechanized preparation of fresh-cut produce.

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“…Pineapple (Ananas comosus [L.] Merr.) is a popular tropical fruit and consumed all over the world owing to its unique flavor and odor, as well as substances beneficial to human health, including minerals, vitamins, and dietary fibers [1,2]. Global pineapple production amounted to approximately 28.65 million metric tons in 2021.…”

Section: Introductionmentioning

confidence: 99%

Nondestructive Detecting Maturity of Pineapples Based on Visible and Near-Infrared Transmittance Spectroscopy Coupled with Machine Learning Methodologies

Qiu

et al. 2023

Horticulturae

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Pineapple is mainly grown in tropical regions and consumed fresh worldwide due to its attractive flavor and health benefits. With increasing global production and trade volume, there is an urgent need for nondestructive techniques for accurate and efficient detection of the internal quality of pineapples. Therefore, this study is dedicated to developing a nondestructive method for real-time determining the internal quality of pineapples by using VIS/NIR transmittance spectroscopy technique and machine learning methodologies. The VIS/NIR transmittance spectrums ranging in 400–1100 nm of total 195 pineapples were collected from a dynamic experimental platform. The maturity grade and soluble solids content (SSC) of individual pineapples were then measured as indicators of internal quality. The qualitative model for discriminating maturity grades of pineapple achieved a high accuracy of 90.8% by the PLSDA model for unknown samples. Meanwhile, the quantitative model for determining SSC also reached a determination coefficient (RP2) of 0.7596 and a root mean square error of prediction (RMSEP) of 0.7879 °Brix by the ANN-PLS model. Overall, high model performance demonstrated that using VIS/NIR transmittance spectroscopy technique coupled with machine learning methodologies could be a feasible method for nondestructive and real-time detection of the internal quality of pineapples.

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Physicochemical properties and sensory acceptability of pineapples of different varieties and stages of maturity

Cited by 24 publications

References 0 publications

Processing Sky Rocket Melon into Jam with Various Acidifiers and Sugar Concentrations

Processing Sky Rocket Melon into Jam with Various Acidifiers and Sugar Concentrations

Towards a Multispectral Imaging System for Spatial Mapping of Chemical Composition in Fresh-Cut Pineapple (Ananas comosus)

Nondestructive Detecting Maturity of Pineapples Based on Visible and Near-Infrared Transmittance Spectroscopy Coupled with Machine Learning Methodologies

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