Article

Development of freshness index of eggplant

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Abstract

Surface gloss, stiffness, and density were considered prime contributors to the freshness of eggplant fruit (Solanum melongena L.). An index to measure freshness was defined as the ratio of product of relative spectral reflectance (surface gloss) and stiffness ratios to the density ratio. Surface gloss was measured in terms of relative spectral reflectance using a computerized spectral radiometer system. Stiffness was determined as an initial slope of force deformation curve obtained by uniaxial compression tests. Weight and volume for computing eggplant density were determined by standard methods. These parameters were changed to consumers' acceptable limit by storing the eggplants for different periods at 25±2 °C temperature and 90±5% relative humidity. Experiments were replicated five to eight times, and the average values were used to compute dimensionless ratios (values at any time divided by initial value) that were later used to determine a freshness index. Various forms of equations were tested for best fitting the data to establish the best relationship with price variation in local market. The freshness index of eggplant fruit decreased exponentially with storage period while it varied in form of power equation of weight and density ratios. It attained the lowest value (5.6%) at acceptable limit of weight ratio of about 0.87. Freshness index correlated linearly with stiffness ratio and quadratically with surface gloss (correlation coefficient 0.99). Price of eggplant varied linearly with the freshness index with good correlation coefficient (0.98), which indicated that the developed freshness index might be useful in estimating the price of eggplants.

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... Medlicott (1990) reports that when eggplant has an opaque and shabby peel, and a darkened calyx, it means that the fruit has suffered from excessive water loss and aging. These swift changes to the quality of eggplant may cause a high variation in its price (Jha and Matsuoka, 2002a), but determining quality can be a difficult task. ...
... It was demonstrated previously (Mayorga Martínez, 2014) that both surface stiffness and peel gloss of eggplant declined during postharvest storage and eggplant density increased significantly over time at all storage conditions. The freshness index was therefore defined based on these factors as presented by Jha and Matsuoka (2002a): ...
... Although the respiration rate of eggplant is considered to be between low and moderate, the symptoms of deterioration in the fruit start to show when its water loss is of about 3% (Gull, 1981). In this study, like in the one carried out by Jha and Matsuoka (2002a), it is shown that I f of this crop does not only depend on the moisture loss of the fruit itself, but it is also dependent upon the early water losses from the fruit (Figure 1). When moisture loss from eggplant is excessive, its pulp becomes soft, it shrivels, its peel loses its gloss and the calyx turns brown due to dehydration (Díaz-Pérez, 1998a, 1998b. ...
... Medlicott (1990) reports that when eggplant has an opaque and shabby peel, and a darkened calyx, it means that the fruit has suffered from excessive water loss and aging. These swift changes to the quality of eggplant may cause a high variation in its price (Jha and Matsuoka, 2002a), but determining quality can be a difficult task. ...
... It was demonstrated previously (Mayorga Martínez, 2014) that both surface stiffness and peel gloss of eggplant declined during postharvest storage and eggplant density increased significantly over time at all storage conditions. The freshness index was therefore defined based on these factors as presented by Jha and Matsuoka (2002a): ...
... Although the respiration rate of eggplant is considered to be between low and moderate, the symptoms of deterioration in the fruit start to show when its water loss is of about 3% (Gull, 1981). In this study, like in the one carried out by Jha and Matsuoka (2002a), it is shown that I f of this crop does not only depend on the moisture loss of the fruit itself, but it is also dependent upon the early water losses from the fruit (Figure 1). When moisture loss from eggplant is excessive, its pulp becomes soft, it shrivels, its peel loses its gloss and the calyx turns brown due to dehydration (Díaz-Pérez, 1998a, 1998b. ...
Article
The objective of this work was to develop a non-subjective freshness index (If) for a Mediterranean variety of eggplant (Solanum melongena L. cv. Traviata). Eggplants were obtained from local agricultural sources and stored under controlled environment conditions. Storage temperature was und to have an effect on If, while the agricultural source and the degree of exposure to light did not affect If. Nonlinear functions modelled If against weight loss (WL), peel gloss loss (GL), surface stiffness loss (SL), density ratio minus one (DRMO), and storage period (in h). The best model for predicting If of eggplant was a function of SL (R2adj =0.98). Stepwise regression identified hyperspectral wavelengths that will predict If at 10°C (R2adj =0.46) and 27°C (R2adj =0.78). If can be used to estimate eggplant quality, therefore future work will develop freshness indices for other eggplant varieties stored under a range of temperature conditions.
... Of late, nondestructive techniques for quality evaluation have gained popularity. Determination of various quality characteristics of fruits and vegetables using nondestructive techniques have been reported (Lesage and Destain 1996;Kato 1997;Nussinovitch et al. 1996;Jha et al. 2005Jha et al. , 2006Jha et al. , 2007, but each of them predicts only a single or in some cases double parameters such as acid to Brix ratio (Jha and Matsuoka 2004). A few reports on determination of maturity index (Sirinnapa et al. 2004;Lakshmi et al. 2006;Jha et al. 2007), freshness index (Jha and Matsuoka 2002;McGlone et al. 2002) and physical appearances using machine vision systems (Blasco et al. 2003) are also available. These techniques determine single quality parameter using relatively costlier techniques and needed to employ as many times as the number of parameters required to be estimated. ...
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Physico-chemical quality parameters of apple were measured during storage using standard techniques and fitted to model expressions for developing an overall quality index (Iq). Predicted Iq was validated with the trends of sensory scores. Total Soluble Solids (TSS) and acidity varied from 13.2 to 12.3 ºBrix and 0.161 to 0.079%, respectively whereas, Hunter colour values L, a, b and yellowness index were 48.7-56.1, 11.0-19.4, 18.8-20.2 and 84.6-98.2, respectively. The gloss at 45 and 60º incidence angles, density and Iq varied from 7.5 to 4.3 and 6.7 to 2.6 GU, 1.01 to 0.96 kg m(-3) and 0.26 to 1.02, respectively. The variation in sensory overall quality scores with storage period was found to be in line with computed overall quality index. The Iq thus, could be defined as the ratio of product of acidity and TSS to the mode of product of a and b Hunter colour values. The polynomial regression equations for Iq with TSS, acidity, a, b, and storage period yielded the correlation coefficients of 0.8443, 0.9838, 0.7130, 0.7183 and 0.9665, respectively; which indicated that overall quality index could be predicted nondestructively using any one of these parameters during storage.
... Different combinations based on previous experiences (Jha et al., 2007Jha and Matsuoka, 2002) were used to formulate empirical expressions for I m . The I m values were computed putting the measured values of physico-chemical parameters in the developed expressions ( Table 1). ...
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This study proposes a formula for prediction of maturity index (Im) using physico-chemical characteristics and overall acceptability (OA) of a sensory panel for mangoes from orchards of nine Indian states. Computed Im values were found to be in agreement with both OA scores and the perceptions of experienced farmers. NIR spectra of 1180 mangoes were acquired. Multiple-linear regression (MLR) and partial least square (PLS) models were developed in the wavelength range of 1200–2200 nm to predict Im. The best prediction was achieved using PLS model after MSC data treatment in the wavelength range of 1600–1800 nm. Multiple correlation coefficients (R) for calibration and validation of PLS model were 0.74 and 0.68, respectively. Lower difference in standard errors of calibration (0.305) and prediction (0.335), indicated the potential of NIRS in prediction of the maturity non-destructive.
... Usually eggplants are egg-shaped or globular and have a bright green calix and firm texture (Gross et al., 2014;Jha et al., 2002). At the international level, the dark purple eggplant is the most commercially consumed fruit among other eggplant varieties (Zaro et al., 2014a). ...
Thesis
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One-third of global food produced for human consumption, which amounts to about 1.3 billion tons is lost or wasted annually. Measuring postharvest losses is an essential operational strategy to enhance postharvest management and to curtail quality loss of fresh horticultural commodity. The goal of this study was to develop and test different methods that characterize and quantify postharvest losses of cucumber and eggplant in St. Kitts-Nevis and Guyana. The study also allowed investigating the influence of temperature and light on quality changes during handling practices of freshly harvested crops. Three approaches were deployed in the study. The first approach consisted of field-based activities in St. Kitts-Nevis and Guyana using producer household surveys (PHS) and modified count and weight (MCW) method. Results from PHS baseline surveys revealed that farmers sell most of their harvested crops to local markets, keeping the remaining crops for household consumption. In Guyana, the majority of farmers (97%) reported selling their crops at harvest, while in St. Kitts-Nevis, 61% of farmers stored them before selling. While farmers in St. Kitts-Nevis reported 30% postharvest losses of crops due to spoilage, those in Guyana reported considerably less. Results from modified count and weight method revealed that small producers experienced greater postharvest loss compared to large ones due to spoilage and lack of market access. As the produce travelled throughout the supply chain, it started to lose significantly (P < 0.05) its freshness and its marketable value as well. This loss was due to inappropriate handling and exposure to undesirable environmental conditions. The second approach entailed laboratory-based work to simulate the environmental conditions during postharvest handling process in the studied countries. This approach was associated with activities investigating the effect of constant and fluctuating environmental factors including temperature and light on quality changes of eggplant and cucumber such as color, texture, weight loss, quality index and phytochemical content. Under isothermal conditions, four storage combinations of temperatures and light were studied for 10 day-period as follows: SC1=10oC/with light, SC2=30oC/with light, SC3=10oC/without light, and SC4=30oC/without light. Under non-isothermal conditions, another four combinations of temperatures and light were conducted (S1=25°C/2 hours without light, S2=25°C/3 hours with light, S3=30°C/12 hours with light and 20°C/12 hours without light for a total of 72 hours, and S4=10°C/144 hours without light). This scenario represented all steps of the supply chain of fresh produce starting at the producer level, followed by the distributor, the retailer and end up at the consumer level. Major postharvest losses occurred after 10 days of storage at 30oC in the presence of light. Under these conditions, the firmness of eggplant samples decreased from 5.31 N to 0.77 N (85.5% loss), the weight loss increased up to 21%, significant (P < 0.05) color difference was observed, and the crops became unmarketable after 8 days of storage. However, when the crops were wrapped using food grade polyethylene film, quality losses were reduced significantly (P < 0.05) with the exception of color attribute. Under non-isothermal conditions, the majority of losses happened after 77-hour period of storage (S3) due to the effect of fluctuating temperature and light every 12-hour period. Crude extracts of freeze-dried produce were used to determine the total phenolic contents (TPC) using the Folin-Ciocalteu method. Exposing vegetables to high temperature (30oC) and direct light was found to significantly degrade their phenolic content. However, a rise in TPC was observed (P < 0.05) when the crops were maintained at 10oC in complete darkness. In addition, storage at fluctuating environmental conditions was found to be the main driver to worsen the phenolic degradation in fresh eggplant (49.7% loss) and cucumber (83.8% loss). Kinetic models were used to provide a structural framework for quantitatively describing and predicting those losses. In the third approach, the Taguchi method was used to quantify postharvest quality loss of both cucumber and eggplant and to optimize environmental conditions during the handling process. The Taguchi method has been widely and successfully used in various subject areas, but no application of this method to postharvest quality management has been reported until the present time. The experimental design included the 4 three-level factors and an L-9 orthogonal array. Traditionally, the Taguchi approach was used to express loss in monetary terms. For the purpose of the study, the word “loss” means the loss of quality and is expressed in unit scale. The results revealed that fresh cucumber lost some of its quality attributes immediately after harvest. At firmness of 15.68 N, the loss was equivalent to 13.68 units. However, at 7.68 N firmness, the loss value was increased by almost 4 times (56.98 units). In terms of quality index (QI), it was noticed that even when the score was high (QI = 9 points), the produce had lost 8.74 units of its quality. In theory, the only time when the loss is equal to zero is when the cucumber fruit is still attached to its mother plant. When the quality index dropped to 1.67 points, the loss was increased by almost 30 times more (loss = 254.91 units). The results showed how large the extent of loss could be when fresh cucumber is stored under undesirable conditions. The Taguchi approach was successfully used to quantify and to predict postharvest quality losses in response to different combinations of environmental factors and their levels. In addition, this approach enabled the identification of optimum conditions of temperature, light and relative humidity, for the storage of fresh produce.
... Therefore, nowadays, non-destructive methods have gained more popularity. Several studies [14,15,16,17,18] have reported the quality parameters of various fruits and vegetables like strawberry, blueberry, apple, tomato, and chili pepper by using various non-destructive methods such as computer vision system, hyperspectral imaging, acoustic impulse resonance frequency sensor, etc.; but each of them anticipates either a single, or double quality attribute such as shape and color, firmness or acid to Brix ratio [19,20]. Furthermore, some authors have also determined the freshness index and maturity index by using machine vision systems [21,22,23]. ...
Article
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In this study, the physical and chemical quality attributes of apples were measured experimentally during the storage after harvesting, using well-defined procedures and techniques. Overall quality index (OQi) models were formulated in terms of measured quality attributes. Firmness (F) and total soluble solids (TSS) varied from 11.88 ± 0.25 to 7.68 ± 0.24 N and 14.1 ± 0.1 to 12.7 ± 0.1% Brix, respectively, whereas acidity and density varied from 0.163 ± 0.003 to 0.081 ± 0.001 % and 0.995 ± 0.003 to 0.951 ± 0.004 gm/cm3 , respectively. The gloss values at 45˚ and 60˚ angles of incidence were found to be in the range of 7.9 ± 0.2 to 4.1 ± 0.3 and 6.8 ± 0.1 to 2.5 ± 0.3, respectively whereas, the Hunter color values L, a, b were found to be in the range of 51.75 ± 1.33 to 57.01 ± 0.98, 24.20 ± 0.86 to 30.12 ± 1.13, and 19.53 ± 1.61 to 22.96 ± 1.12, respectively. Formulated models were validated with the sensory scores. OQi predicted by the Model ML2 was found to be in consonance with the variation in the sensory overall quality scores. The OQi, as per the model ML2, was estimated as the ratio of the product of the constant C (265.5), acidity (A), and firmness (F) to the mod of the product of Hunter color values a and b. Finally, the predicted values of OQi were correlated with the measured quality parameters to check the possibility of predicting OQi non-destructively by using any one of those measured attributes during the storage.
... All the 516 other remaining features such as Saturation and Vital 517 components of the HSV colourmap and Red and Blue 518 components of the RGB colourmap yield more than 83% 519 classifier accuracy with the three freshness class model; 520 which is again appreciable. 521 Freshness analysis has been carried out by researchers 522 for fruits like apple [35][36][37], banana [38], amla [39] and 523 mangoes [40] and vegetables like eggplant [41]. The 524 findings of the present work is in agreement with the pre-525 vious reported results. ...
Article
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A supervised learning-based simple three class freshness detection algorithm is presented in this paper for prediction of freshness of Amla samples. Six major features from the red–green–blue (RGB) and hue–saturation–vital component (HSV) colourspace and ten other minor features have been studied here with the proposed artificial neural network (ANN) model. The proposed freshness classifier is computationally light due to the use of only ANN as the major classifying tool. More importantly, the analysis is based on images captured on smart phone only, which enables portability and hence, wide acceptability of the scheme. Accuracy of classification higher than 96.5% is achieved using the hue histogram of the image, followed by green layer histogram and others. All the major features were able to produce more than 83% efficiency in freshness class determination; whereas, minor features could achieve a highest classification accuracy of about 77%; clearly suggesting advantage of the major set of features. High efficient freshness categorization, combined with ease of computation, simple feature analysis and use of smart phones for image acquisition ensures its high possibility of real life implementation, especially incorporating within mobile application-based software development.
... Physical methods usually considered physical parameters, such as density, suspended insoluble solids (SIS) and turbidity (TU), texture, colour and solubility. [11,12] Nowadays, various accurate and reliable methods, such as chromatography and mass spectroscopy, which are based on chemical properties of the samples, have shown great potential in food identification and adulteration detection. [13,14] Continuous monitoring of food quality and safety quality in a supply chain is currently compulsory in the EU and some other countries, but increasing the complexity of adulteration implies that continuous improvement of quantitative chemical analytical methods requires to ensure effective identification of fraudulent practices. ...
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Fingerprinting has become a powerful device in food authentication activities. Food products can be verified based on their chemical composition, geographical origin, specified botanical sources or possible adulterations by fingerprinting gas chromatographic chemical analysis and a subsequent multivariate data analysis. Although fingerprinting approaches have already been used successfully in many research projects, feasibility and employment in routine daily tests and food composition monitoring are not still widespread. Within this review, food fingerprinting studies in gas chromatographic methods for different food product categories were selected by a systematic search method. The studies were examined for chemometrics techniques, identification of effective variables, method validation and quality assurance parameters. In this way, the research activities could be considered as an effective starting point to establish fingerprinting techniques for food authentication in wide industrial scale in the future.
... In other studies, different non-destructive methods were applied also for quality and freshness prediction of eggplants. Jha and Matsuoka (2002) used relative spectral reflectance and computerized spectral radiometer system to correlate surface gloss, stiffness, and density for the evaluation of freshness the in eggplant fruit. Freshness index correlated with stiffness ratio and with surface gloss (correlation coefficient 0.99), but the measurement of these quality indices was making the evaluation more time consuming. ...
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Gorgon nuts are processed for their kernels in expanded form and this is known as makhana in India. Operations involved in the traditional method of processing make it laborious, time consuming and costly. This paper reports an investigation into the effect of five combinations of operations on recovery of makhana, viz., (1) roasting and popping; (2) drying, roasting and popping; (3) drying, tempering, roasting and popping; (4) first roasting, tempering, second roasting and popping; and (5) drying, first roasting, tempering, second roasting and popping. The design of the experiments was based on response surface methodology and they were conducted using thin-layer drying and a manual roasting method.The best combination of operations,based on the recovery of grade 1 makhana, was found to be number 5 above, that is, drying, first roasting, tempering, second roasting and popping. The data was analysed to find the optimum processing conditions, to give 97% grade 1 makhana. These were found to be a combination of first roasting of dried nut (moisture content 33% d.b.) at 335°C for 3·9 min, tempering for 23 h and second roasting at 335°C for 2·8 min. These conditions reduced the processing time to less than one-half as compared with the traditional method.