scholarly journals Predicting of the Quality Attributes of Orange Fruit Using Hyperspec-tral Images

2019 ◽  
Author(s):  
V. Aredo ◽  
L. Velásquez ◽  
J. Carranza-Cabrera ◽  
R. Siche
Keyword(s):  
Hyperspectral Image ◽  
Quality Attributes ◽  
Soluble Solids ◽  
Coefficient Of Determination ◽  
Internal Quality ◽  
Least Squares Regression ◽  
Hyperspectral Reflectance ◽  
Simplified Models ◽  
External Quality ◽  
Orange Fruit

Background: Hyperspectral image analysis is a fast and non-destructive technique that is being used to measure quality attributes of food products. This research investigated the feasibility of predicting internal quality attributes, such as Total Soluble Solids (TSS), pH, Titratable Acidity (TA), and maturity index (TSS/TA); and external quality attributes such as color components (L*, a*, b*) as well as Color Index (CI) of Valencia orange fruit using hyperspectral reflectance imaging in the range of 400-1000 nm. Methods: Oranges were scanned by the system in order to build full models for predicting quality attributes using partial least squares regression. Optimal wavelengths were identified using the regression coefficients from full models, which were used to build simplified models by multiple linear regression. The coefficient of determination of prediction (R2p) and the Standard Error of Prediction (SEP) were used to measure the performance of the models obtained. Results: Full models for internal quality attributes had low performance (R2p<0.3, SEP>50%). Full models for external quality attributes presented a high performance for L* (R2p=0.898, SEP=19%), a* (R2p=0.952, SEP=13%), b* (R2p=0.922, SEP=20%), and CI (R2p=0.972, SEP=12%). The simplified models presented similar performance to those obtained for external quality attributes. Conclusion: Hyperspectral reflectance imaging has potential for predicting color of oranges in an objective and noncontact way.

scholarly journals Prediction of water content and soluble solids content of ‘manalagi’ apples using near infrared spectroscopy

2021 ◽  
Vol 922 (1) ◽  
pp. 012062
Author(s):  
K Kusumiyati ◽  
Y Hadiwijaya ◽  
D Suhandy ◽  
A A Munawar
Keyword(s):  
Infrared Spectroscopy ◽  
Water Content ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Quality Attributes ◽  
Soluble Solids ◽  
Coefficient Of Determination ◽  
Soluble Solids Content ◽  
Orthogonal Signal Correction ◽  
Solids Content

Abstract The purpose of the research was to predict quality attributes of ‘manalagi’ apples using near infrared spectroscopy (NIRS). The desired quality attributes were water content and soluble solids content. Spectra data collection was performed at wavelength of 702 to 1065 nm using a Nirvana AG410 spectrometer. The original spectra were enhanced using orthogonal signal correction (OSC). The regression approaches used in the study were partial least squares regression (PLSR) and principal component regression (PCR). The results showed that water content prediction acquired coefficient of determination in calibration set (R2cal) of 0.81, coefficient of determination in prediction set (R2pred) of 0.61, root mean squares error of calibration set (RMSEC) of 0.009, root mean squares of prediction set (RMSEP) of 0.020, and ratio performance to deviation (RPD) of 1.62, while soluble solids content prediction displayed R2cal, R2pred, RMSEC, RMSEP, and RPD of 0.79, 0.85, 0.474, 0.420, and 2.69, respectively. These findings indicated that near infrared spectroscopy could be used as an alternative technique to predict water content and soluble solids content of ‘manalagi’ apples.

scholarly journals Time-of-flight Near-infrared Spectroscopy for Nondestructive Measurement of Internal Quality in Grapefruit

2013 ◽  
Vol 138 (3) ◽  
pp. 225-228 ◽  
Author(s):  
Yohei Kurata ◽  
Tomoe Tsuchida ◽  
Satoru Tsuchikawa
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Prediction Accuracy ◽  
Near Infrared ◽  
Time Of Flight ◽  
Soluble Solids ◽  
Internal Quality ◽  
Citrus Paradisi ◽  
Least Squares Regression ◽  
Time Resolved

We proposed a technique combining time-of-flight (TOF) and near-infrared spectroscopy (NIRS), termed TOF-NIRS, capable of measuring the time-resolved profiles of near-infrared (NIR) light with nanosecond resolution. Analysis of the variation in time-resolved profiles was used to estimate soluble solids concentration (SSC) and acidity in grapefruit (Citrus paradisi), and the prediction accuracy was compared with the conventional NIR measurement device. In data processing, the cross-correlation function, which evaluated the similarity between the reference and transmitted beams, was introduced as an explanatory variable for partial least squares regression. TOF-NIRS predicted both SSC and acidity in grapefruit with higher precision than the conventional NIR measurement with respective r values of 0.72 and 0.85. Specifically, the superiority of TOF-NIRS was attributed to measurement time and prediction accuracy in determining acidity.

scholarly journals Hyperspectral Imaging for Evaluating Impact Damage to Mango According to Changes in Quality Attributes

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3920 ◽  
Author(s):  
Duohua Xu ◽  
Huaiwen Wang ◽  
Hongwei Ji ◽  
Xiaochuan Zhang ◽  
Yanan Wang ◽  
...  
Keyword(s):  
Hyperspectral Imaging ◽  
Prediction Models ◽  
Impact Damage ◽  
Mangifera Indica ◽  
Titratable Acidity ◽  
Strong Relationship ◽  
Quality Attributes ◽  
Soluble Solids ◽  
Coefficient Of Determination ◽  
Mean Square Errors

Evaluation of impact damage to mango (Mangifera indica Linn) as a result of dropping from three different heights, namely, 0.5, 1.0 and 1.5 m, was conducted by hyperspectral imaging (HSI). Reflectance spectra in the 900–1700 nm region were used to develop prediction models for pulp firmness (PF), total soluble solids (TSS), titratable acidity (TA) and chroma (∆b*) by a partial least squares (PLS) regression algorithm. The results showed that the changes in the mangoes’ quality attributes, which were also reflected in the spectra, had a strong relationship with dropping height. The best predictive performance measured by coefficient of determination (R2) and root mean square errors of prediction (RMSEP) values were: 0.84 and 31.6 g for PF, 0.9 and 0.49 oBrix for TSS, 0.65 and 0.1% for TA, 0.94 and 0.96 for chroma, respectively. Classification of the degree of impact damage to mango achieved an accuracy of more than 77.8% according to ripening index (RPI). The results show the potential of HSI to evaluate impact damage to mango by combining with changes in quality attributes.

scholarly journals Comparing Objective Quality Attributes of Grapefruit Imported Into Europe

1994 ◽  
Vol 4 (4) ◽  
pp. 398-401
Author(s):  
L.A. Risse ◽  
A.J. Bongers
Keyword(s):  
The Netherlands ◽  
Fruit Size ◽  
Quality Attributes ◽  
Quality Characteristics ◽  
Soluble Solids ◽  
Internal Quality ◽  
Citrus Paradisi ◽  
Total Acid ◽  
Total Soluble Solids ◽  
Objective Quality

Grapefruit (Citrus paradisi Macf.) were sampled biweekly from importers in Rotterdam, the Netherlands, from Oct. 1992 through Sept. 1993. For each sample, fruit size, weight, peel thickness, internal pulp color, juice weight, total soluble solids (TSS), and total acid (TA) were measured. Three grapefruit cultivars—`Marsh' white, `Ruby Red', and `Star Ruby'—were sampled from 12 countries of origin. Florida fruit weighed more, had the thinnest peel, the most juice, the lowest TA, and the highest TSS/TA ratio for all three cultivars compared to all other origins, except for `Ruby Red' grapefruit from California, which had a lower TA and a higher TSS/TA ratio. Turkish `Ruby Red' and Spanish `Star Ruby' fruit weighed the least and had the least amount of juice compared to fruit from other origins. Turkish fruit had the highest TA and the lowest TSS/TA ratio for all three cultivars from all origins. Israeli `Marsh' white and `Star Ruby' had the highest TSS. Overall, the internal quality characteristics of Florida fruit was high compared to fruit from other origins.

Evaluation of soluble solids of curry soup containing coconut milk by near infrared spectroscopy

2017 ◽  
Vol 25 (3) ◽  
pp. 203-210 ◽  
Author(s):  
Panmanas Sirisomboon ◽  
Jutarat Nawayon
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Total Sample ◽  
Coconut Milk ◽  
Soluble Solids ◽  
Coefficient Of Determination ◽  
Least Squares Regression ◽  
Robust Model ◽  
Processing Line

The aim of this research was to do a feasibility study of near infrared spectroscopy to evaluate soluble solids of curry soup containing coconut milk. The soup samples were collected from mixing tanks, water adjusting tanks, an ultra-high temperature process line and laminated cartons. There were also soluble solids adjusted samples by adding or reducing coconut sugar where the curry was made from the same recipe as in the processing line but increasing 30, 60 and 90% coconut sugar and reducing 30, 60 and 90% coconut sugar from normal. There were 119 samples in total. Sample was scanned with an FT-NIR spectrometer. A prediction model for soluble solids was established using near infrared spectral data in conjunction with partial least squares regression. When validated using a set of test samples, the model developed using spectra pretreated by min-max normalization in the range 9403.8–6094.3 cm−1, provided a coefficient of determination (r2), root mean square error of prediction, bias and ratio of performance to interquartile of 0.92, 1.0°Brix, 0.1°Brix and 2.4, respectively. It showed the potential of using near infrared spectroscopy to evaluate soluble solids in curry soup. With further development using more natural samples, a more robust model could be achieved to evaluate soluble solids in curry soup in a processing factory.

Impact of Clone Refactoring on External Quality Attributes of Open Source Softwares

2018 ◽  
pp. 86-94
Author(s):  
Himanshi Vashisht ◽  
Sanjay Bharadwaj ◽  
Sushma Sharma
Keyword(s):  
Open Source ◽  
Internal Structure ◽  
Software Quality ◽  
Source Code ◽  
Quality Attributes ◽  
Software Component ◽  
External Quality ◽  
Code Refactoring ◽  
Observable Behaviour

Code refactoring is a “Process of restructuring an existing source code.”. It also helps in improving the internal structure of the code without really affecting its external behaviour”. It changes a source code in such a way that it does not alter the external behaviour yet still it improves its internal structure. It is a way to clean up code that minimizes the chances of introducing bugs. Refactoring is a change made to the internal structure of a software component to make it easier to understand and cheaper to modify, without changing the observable behaviour of that software component. Bad smells indicate that there is something wrong in the code that have to refactor. There are different tools that are available to identify and emove these bad smells. A software has two types of quality attributes- Internal and external. In this paper we will study the effect of clone refactoring on software quality attributes.

FRAUD CONFIRMATION, CLIENT SATISFACTION AND CLIENT LOYALTY

2019 ◽  
Vol 1 (1) ◽  
pp. 39
Author(s):  
Ngurah Pandji Mertha Agung Durya
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Client Satisfaction ◽  
Audit Quality ◽  
Hypothesis Test ◽  
Linear Regression Analysis ◽  
Quality Attributes ◽  
Path Model ◽  
Coefficient Of Determination ◽  
The Government

<p>This study aims to find evidence, the influence of Audit Quality Attributes, Client Satisfaction and Client Loyalty, which are moderated by Fraud Confirmation. The research was conducted at the BKM, a community-based organization, formed by the Government, through the <em>Kotaku</em> Program. The research used Regression statistical analysis and conducted a hypothesis test. Regression analysis used includes Simple Linear Regression Analysis, Multiple Regression Analysis, and MRA Regression Analysis, and Path Model Linear Regression Analysis. This study also pays attention to the calculation of the coefficient of determination to give an idea of the ability of the model in explaining the phenomenon of Client Satisfaction and Client Loyalty. The result that both partially and simultaneously, Audit Quality Attributes, Fraud Confirmation affected Client Satisfaction and Loyalty. The research also succeeded in proving that Client Satisfaction mediates the effect of Audit Quality Attributes on Client Loyalty, but failed to provide empirical evidence, that the Fraud Confirmation moderated the effect of Audit Quality Attributes on Client Satisfaction and Loyalty. Contribution to audit practices, where it is important to realize Client Satisfaction through Audit Quality Attributes and Fraud Confirmation, especially in situations where Fraud acts are suspected.</p>

Nondestructive Quality Evaluation of Tomatoes

HortScience ◽  
1998 ◽  
Vol 33 (3) ◽  
pp. 544c-544
Author(s):  
A. Hakim ◽  
A. Purvis ◽  
E. Pehu ◽  
I. Voipio ◽  
E. Kaukovirta
Keyword(s):  
Quality Evaluation ◽  
Tomato Fruit ◽  
Quality Attributes ◽  
Internal Quality ◽  
Attractive Alternative ◽  
Fluorescence Techniques ◽  
Nondestructive Quality ◽  
Alternative Techniques ◽  
Evaluation Techniques

Both external and internal quality of fruits such as tomatoes can be evaluated by different methods, but all most all of the methods are destructive. For this reason, there is a need to reassess some of the alternative techniques. Nondestructive quality evaluation is an attractive alternative. The principles of different nondestructive quality evaluation techniques such as optical, physical, and fluorescence techniques applied to tomato fruit is explained. Successful application of these techniques that could be used for evaluation of different quality attributes are illustrated. The advantages of nondestructive quality evaluation techniques are that they are very fast, easy, labor- and time-intensive, and inexpensive. These techniques could also be useful to evaluate the quality of other vegetables.

scholarly journals Portable near Infrared Spectroscopy as a Tool for Fresh Tomato Quality Control Analysis in the Field

2021 ◽  
Vol 11 (7) ◽  
pp. 3209
Author(s):  
Karla R. Borba ◽  
Didem P. Aykas ◽  
Maria I. Milani ◽  
Luiz A. Colnago ◽  
Marcos D. Ferreira ◽  
...  
Keyword(s):  
Citric Acid ◽  
Near Infrared ◽  
Prediction Models ◽  
Quality Attributes ◽  
Internal Quality ◽  
Control Analysis ◽  
Tomato Quality ◽  
Wide Range ◽  
Different Types ◽  
Fresh Tomato

Portable spectrometers are promising tools that can be an alternative way, for various purposes, of analyzing food quality, such as monitoring in a few seconds the internal quality during fruit ripening in the field. A portable/handheld (palm-sized) near-infrared (NIR) spectrometer (Neospectra, Si-ware) with spectral range of 1295–2611 nm, equipped with a micro-electro-mechanical system (MEMs), was used to develop prediction models to evaluate tomato quality attributes non-destructively. Soluble solid content (SSC), fructose, glucose, titratable acidity (TA), ascorbic, and citric acid contents of different types of fresh tomatoes were analyzed with standard methods, and those values were correlated to spectral data by partial least squares regression (PLSR). Fresh tomato samples were obtained in 2018 and 2019 crops in commercial production, and four fruit types were evaluated: Roma, round, grape, and cherry tomatoes. The large variation in tomato types and having the fruits from distinct years resulted in a wide range in quality parameters enabling robust PLSR models. Results showed accurate prediction and good correlation (Rpred) for SSC = 0.87, glucose = 0.83, fructose = 0.87, ascorbic acid = 0.81, and citric acid = 0.86. Our results support the assertion that a handheld NIR spectrometer has a high potential to simultaneously determine several quality attributes of different types of tomatoes in a practical and fast way.

Investigating the effect of oxalic acid and salicylic acid treatments on the post-harvest life of temperate grown apricot varieties (Prunus armeniaca) during controlled atmosphere storage

2021 ◽  
pp. 108201322110320
Author(s):  
Mariya Batool ◽  
Omar Bashir ◽  
Tawheed Amin ◽  
Sajad Mohd Wani ◽  
FA Masoodi ◽  
...  
Keyword(s):  
Salicylic Acid ◽  
Oxalic Acid ◽  
Chilling Injury ◽  
Quality Attributes ◽  
Prunus Armeniaca ◽  
Soluble Solids ◽  
Carotenoid Content ◽  
Total Phenolic ◽  
Controlled Atmosphere ◽  
Injury Index

This study aimed at investigating the influence of different postharvest treatments with oxalic acid (OA) and salicylic acid (SA) on quality attributes and postharvest shelf life of temperate grown apricot varieties stored under controlled atmosphere (CA) storage conditions. After each treatment was given, the samples were stored in CA store maintained at a temperature of 0 °C, 90 ± 5% relative humidity, 5% oxygen and 15% carbon dioxide for 30 days. Results indicated that both OA and SA treatments significantly (p ≤ 0.05) retained total soluble solids, titratable acidity, color profile, ascorbic acid content and total phenolic content of apricot varieties and had a positive effect on antioxidant activity and texture of samples compared to control. However, carotenoid content was found to be higher in control. Both the treatments reduced chilling injury index, weight loss and decay percentage of samples. Moreover, it was found that SA treatment was the most effective treatment in maintaining visual color of apricots while OA maintained fruit firmness and effectively decreased the decay percentage and chilling injury index of apricot varieties. In conclusion, it was found that both OA and SA have the potential to extend storage life of apricots and maintain quality attributes of the crop during CA storage.

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