Food analysis by portable NIR spectrometer

Folli, Gabriely S.; Santos, Layla P.; Santos, Francine D.; Cunha, Pedro Henrique Pereira da; Schaffel, Izabela F.; Borghi, Flávia T.; Barros, Iago H.A.S.; Pires, André Assis; Ribeiro, Araceli Verónica Flores Nardy; Romão, Wanderson; Filgueiras, Paulo R.

doi:10.1016/j.focha.2022.100074

Cited by 20 publications

(8 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…These methods do not require chemicals as well as a multi stages process. Non-destructive measurement allows for on-site analysis, has a low maintenance cost, requires only small sample volumes, and does not cause destruction of the sample [ 51 , 52 ].…”

Section: Resultsmentioning

confidence: 99%

Comparison of color spectrophotometer and Vis/NIR spectroscopy on assessing natural pigments of cucumber applied with different ethephon concentrations

Kusumiyati,

Putri

2023

Heliyon

View full text Add to dashboard Cite

Section: Resultsmentioning

confidence: 99%

Comparison of color spectrophotometer and Vis/NIR spectroscopy on assessing natural pigments of cucumber applied with different ethephon concentrations

Kusumiyati,

Putri

2023

Heliyon

View full text Add to dashboard Cite

“…Real‐time applications for determining various quality characteristics from a small number of essential spectra or even from a single spectrum have a significant advantage over existing techniques, especially the development of affordable handheld devices. Recent technological improvements have reduced the size of spectroscopic instruments, enabling the development of handheld gadgets and portable sensing systems that enable in situ, real‐time monitoring of crops, food, and egg quality (Brasil et al., 2022; Cruz‐Tirado et al., 2021; Folli et al., 2022; Freitag et al., 2022; Xu et al., 2022). Therefore, the use of intelligent optical sensors has become more popular.…”

Section: Challenges and Future Trendsmentioning

confidence: 99%

Non‐destructive optical sensing technologies for advancing the egg industry toward Industry 4.0: A review

Ahmed,

Hossainy,

Khaliduzzaman

et al. 2023

Comp Rev Food Sci Food Safe

View full text Add to dashboard Cite

The egg is considered one of the best sources of dietary protein, and has an important role in human growth and development. With the increase in the world's population, per capita egg consumption is also increasing. Ground‐breaking technological developments have led to numerous inventions like the Internet of Things (IoT), various optical sensors, robotics, artificial intelligence (AI), big data, and cloud computing, transforming the conventional industry into a smart and sustainable egg industry, also known as Egg Industry 4.0 (EI 4.0). The EI 4.0 concept has the potential to improve automation, enhance biosecurity, promote the safeguarding of animal welfare, increase intelligent grading and quality inspection, and increase efficiency. For a sustainable Industry 4.0 transformation, it is important to analyze available technologies, the latest research, existing limitations, and prospects. This review examines the existing non‐destructive optical sensing technologies for the egg industry. It provides information and insights on the different components of EI 4.0, including emerging EI 4.0 technologies for egg production, quality inspection, and grading. Furthermore, drawbacks of current EI 4.0 technologies, potential workarounds, and future trends were critically analyzed. This review can help policymakers, industrialists, and academicians to better understand the integration of non‐destructive technologies and automation. This integration has the potential to increase productivity, improve quality control, and optimize resource management toward sustainable development of the egg industry.

show abstract

“…Near-infrared (NIR) spectroscopy coupled with multivariate processing techniques has been extensively analyzed in recent years. This technology has been significantly applied in several industries, like the agricultural product industry [12,13], the pharmaceutical factory [14] and the petrochemical industry [15,16]. NIR has become a pivotal assessment 2 of 12 method for milk quality [17,18] because it is an undamaged, green and rapid method.…”

Section: Introductionmentioning

confidence: 99%

Application of Near-Infrared Spectroscopy and Fuzzy Improved Null Linear Discriminant Analysis for Rapid Discrimination of Milk Brands

Wu,

Fang,

et al. 2023

Foods

View full text Add to dashboard Cite

The quality of milk is tightly linked to its brand. A famous brand of milk always has good quality. Therefore, this study seeks to design a new fuzzy feature extraction method, called fuzzy improved null linear discriminant analysis (FiNLDA), to cluster the spectra of collected milk for identifying milk brands. To elevate the classification accuracy, FiNLDA was applied to process the near-infrared (NIR) spectra of milk acquired by the portable near-infrared spectrometer. The principal component analysis and Savitzky–Golay (SG) filtering algorithm were employed to lower dimensionality and eliminate noise in this system, respectively. Thereafter, improved null linear discriminant analysis (iNLDA) and FiNLDA were applied to attain the discriminant information of the NIR spectra. At last, the K-nearest neighbor classifier was utilized for assessing the performance of the identification system. The results indicated that the maximum classification accuracies of LDA, iNLDA and FiNLDA were 74.7%, 88% and 94.67%, respectively. Accordingly, the portable NIR spectrometer in combination with FiNLDA can classify milk brands correctly and effectively.

show abstract

Food analysis by portable NIR spectrometer

Cited by 20 publications

References 38 publications

Comparison of color spectrophotometer and Vis/NIR spectroscopy on assessing natural pigments of cucumber applied with different ethephon concentrations

Comparison of color spectrophotometer and Vis/NIR spectroscopy on assessing natural pigments of cucumber applied with different ethephon concentrations

Non‐destructive optical sensing technologies for advancing the egg industry toward Industry 4.0: A review

Application of Near-Infrared Spectroscopy and Fuzzy Improved Null Linear Discriminant Analysis for Rapid Discrimination of Milk Brands

Contact Info

Product

Resources

About