scholarly journals Vis-NIR Hyperspectral Imaging for Online Quality Evaluation during Food Processing: A Case Study of Hot Air Drying of Purple-Speckled Cocoyam (Colocasia esculenta (L.) Schott)

Processes ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 1804
Author(s):  
John Ndisya ◽  
Ayub Gitau ◽  
Duncan Mbuge ◽  
Arman Arefi ◽  
Liliana Bădulescu ◽  
...  
Keyword(s):  
Hyperspectral Imaging ◽  
Prediction Models ◽  
Prediction Performance ◽  
Good Prediction ◽  
Hot Air Drying ◽  
Full Spectrum ◽  
Air Drying ◽  
Hot Air ◽  
Good Prediction Performance ◽  
Hue Angle

In this study, hyperspectral imaging (HSI) and chemometrics were implemented to develop prediction models for moisture, colour, chemical and structural attributes of purple-speckled cocoyam slices subjected to hot-air drying. Since HSI systems are costly and computationally demanding, the selection of a narrow band of wavelengths can enable the utilisation of simpler multispectral systems. In this study, 19 optimal wavelengths in the spectral range 400–1700 nm were selected using PLS-BETA and PLS-VIP feature selection methods. Prediction models for the studied quality attributes were developed from the 19 wavelengths. Excellent prediction performance (RMSEP < 2.0, r2P > 0.90, RPDP > 3.5) was obtained for MC, RR, VS and aw. Good prediction performance (RMSEP < 8.0, r2P = 0.70–0.90, RPDP > 2.0) was obtained for PC, BI, CIELAB b*, chroma, TFC, TAA and hue angle. Additionally, PPA and WI were also predicted successfully. An assessment of the agreement between predictions from the non-invasive hyperspectral imaging technique and experimental results from the routine laboratory methods established the potential of the HSI technique to replace or be used interchangeably with laboratory measurements. Additionally, a comparison of full-spectrum model results and the reduced models demonstrated the potential replacement of HSI with simpler imaging systems.

Detection of moisture and carotenoid content in carrot slices during hot air drying based on multispectral imaging equipment with selected wavelengths

2021 ◽  
Vol 17 (9) ◽  
pp. 727-735
Author(s):  
Jiamei Long ◽  
Jia Yang ◽  
Jing Peng ◽  
Leiqing Pan ◽  
Kang Tu
Keyword(s):  
Moisture Content ◽  
Prediction Model ◽  
Multispectral Imaging ◽  
Prediction Models ◽  
Projection Algorithm ◽  
Carotenoid Content ◽  
Support Vector ◽  
Hot Air Drying ◽  
Air Drying ◽  
Hot Air

Abstract Moisture content and carotenoid content are important indicators for evaluating the drying process of carrot slices. There are growing attention to develop non-destructive methods as effectively analytical tools in quality assurance of drying carrot slices. In this study, the characteristic wavelengths of moisture and carotenoid content in carrot slices during hot air drying were extracted based on hyperspectral imaging technology. A multispectral imaging equipment was built after that, and the wavelengths of filters were determined according to the characteristic wavelengths. Based on the successive projection algorithm (SPA), the optimal wavelengths of moisture and carotenoid content were further determined, and prediction models of both were established based on the system. There were 12 filters selected in this study. The results showed that a support vector machine (SVM) prediction model for moisture content was established based on seven optimal wavelengths with 0.991 for the coefficient of determination of prediction set (R 2 p ) and 10.318 for the residual prediction residual (RPD). Based on eight optimal wavelengths, a SVM prediction model for carotenoid content was also established with 0.968 for R 2 p and 5.337 for RPD. The prediction performance is close to or even better than that based on hyperspectral. The study confirmed the feasibility of using the multispectral imaging equipment to measure the moisture and carotenoid content of carrot slices during drying based on selected wavelengths, laying a foundation for the further preparation of a portable multispectral detector for the quality of dry products.

scholarly journals Organic apples (cv. Elstar) quality evaluation during hot-air drying using Vis/NIR hyperspectral imaging

2018 ◽  
Author(s):  
Luna Shrestha ◽  
Roberto Moscetti ◽  
Stuart Crichton ◽  
Oliver Hensel ◽  
Barbara Sturm
Keyword(s):  
Moisture Content ◽  
Hyperspectral Imaging ◽  
Regression Models ◽  
Quality Evaluation ◽  
Pls Regression ◽  
Drying Process ◽  
Hot Air Drying ◽  
Air Drying ◽  
Hot Air ◽  
Apple Slices

Organic dried apples are common snacks fulfilling functional as well as nutritional aspects. However, appearance of dried slices does not always satisfy consumer requirements, thus, improvements are needed. In this study, partial least squares (PLS) regression models were successfully developed to monitor changes in colour and moisture content in apple slices during the drying process over the Vis/NIR spectral range. The regression vector analysis results suggested that features at 580, 750 and 970 nm are better for predicting moisture content, while 580 and 680 nm allow to measure the (a*/b*) colour ratio.   Keywords: Drying; Dried apple slices; Moisture content; Colour; PLSR modelling

scholarly journals Postharvest monitoring of organic potato (cv. Anuschka) during hot-air drying using visible-NIR hyperspectral imaging

2017 ◽  
Vol 98 (7) ◽  
pp. 2507-2517 ◽  
Author(s):  
Roberto Moscetti ◽  
Barbara Sturm ◽  
Stuart OJ Crichton ◽  
Waseem Amjad ◽  
Riccardo Massantini
Keyword(s):  
Hyperspectral Imaging ◽  
Hot Air Drying ◽  
Air Drying ◽  
Hot Air ◽  
Organic Potato

scholarly journals Determining the Effect of Pre-Treatment in Rice Noodle Quality Subjected to Dehydration through Hierarchical Scoring

Processes ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 1309
Author(s):  
Muhammad Heikal Ismail ◽  
Hii Ching Lik ◽  
Winny Routray ◽  
Meng Wai Woo
Keyword(s):  
Heat Pump ◽  
Freeze Drying ◽  
Oil Content ◽  
Hot Air Drying ◽  
Air Drying ◽  
Starch Gelatinization ◽  
Hot Air ◽  
Heat Pump Drying ◽  
Pre Treatment ◽  
Noodle Quality

Fresh rice noodle was usually coated in a large amount of oil to avoid stickiness and extend the shelf life. Pre-treatment has been applied to reduce the quantity of oil in rice noodle. In this research, the pre-treatment and temperature effect on the rice noodle quality subjected to hot air drying, heat pump drying, and freeze drying was investigated. Texture, color, oil content, and starch gelatinization of the dried noodle was further evaluated. Results revealed that there were significant differences (p < 0.05%) in texture, color, oil content, and starch gelatinization in rice noodle subjected to pre-treatment. Furthermore, the texture, color, oil content, and starch gelatinization demonstrated a significant difference (p < 0.05%) in freeze drying rather than hot air drying and heat pump drying. The findings indicate that the qualitative features of the dehydrated noodle are synergistic to pretreatment and drying temperature. Despite superior quality shown by freeze drying, the hierarchical scoring has proven that rice noodle undergoing hot air drying at 30 °C to produce comparable quality attributes. The hierarchical scoring can be a useful tool in quality determination for the food industry.

Dynamics of heat transfer and moisture in beef jerky during hot air drying

Meat Science ◽  
2021 ◽  
pp. 108638
Author(s):  
Shuo Shi ◽  
Jia Feng ◽  
Geer An ◽  
Baohua Kong ◽  
Hui Wang ◽  
...  
Keyword(s):  
Heat Transfer ◽  
Hot Air Drying ◽  
Air Drying ◽  
Hot Air ◽  
Beef Jerky
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