Characteristic wavelengths optimization improved the predictive performance of near-infrared spectroscopy models for determination of aflatoxin B1 in maize

Deng, Jihong; Jiang, Hui; Chen, Quansheng

doi:10.1016/j.jcs.2022.103474

Cited by 20 publications

(6 citation statements)

References 27 publications

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“…The parameter setting of CSO algorithm can also reflect that the algorithm has a certain degree of portability (Deng et al 2022). Set the CSO parameters RN and CN to 0, and the CSO algorithm can be transformed into the DE algorithm.…”

Section: Algorithm Parameter Settingmentioning

confidence: 99%

A comprehensive survey on the chicken swarm optimization algorithm and its applications: state-of-the-art and research challenges

Chen,

Cao,

Chen

et al. 2024

Artif Intell Rev

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The application of optimization theory and the algorithms that are generated from it has increased along with science and technology's continued advancement. Numerous issues in daily life can be categorized as combinatorial optimization issues. Swarm intelligence optimization algorithms have been successful in machine learning, process control, and engineering prediction throughout the years and have been shown to be efficient in handling combinatorial optimization issues. An intelligent optimization system called the chicken swarm optimization algorithm (CSO) mimics the organic behavior of flocks of chickens. In the benchmark problem's optimization process as the objective function, it outperforms several popular intelligent optimization methods like PSO. The concept and advancement of the flock optimization algorithm, the comparison with other meta-heuristic algorithms, and the development trend are reviewed in order to further enhance the search performance of the algorithm and quicken the research and application process of the algorithm. The fundamental algorithm model is first described, and the enhanced chicken swarm optimization algorithm based on algorithm parameters, chaos and quantum optimization, learning strategy, and population diversity is then categorized and summarized using both domestic and international literature. The use of group optimization algorithms in the areas of feature extraction, image processing, robotic engineering, wireless sensor networks, and power. Second, it is evaluated in terms of benefits, drawbacks, and application in comparison to other meta-heuristic algorithms. Finally, the direction of flock optimization algorithm research and development is anticipated.

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Section: Algorithm Parameter Settingmentioning

confidence: 99%

A comprehensive survey on the chicken swarm optimization algorithm and its applications: state-of-the-art and research challenges

Chen,

Cao,

Chen

et al. 2024

Artif Intell Rev

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“…Quantitative assay of Aflatoxin B1 in maize was proposed by Deng et al Their NIR system was realized and employed to characterize maize samples with different mildew degrees ( Deng et al, 2022 ). High-quality production of tobacco leaves needs identification of deep green infection.…”

Section: Applications To Agriculturementioning

confidence: 99%

Portable NIR spectroscopy: the route to green analytical chemistry

Gullifa,

Barone,

Papa

et al. 2023

Front. Chem.

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There is a growing interest for cost-effective and nondestructive analytical techniques in both research and application fields. The growing approach by near-infrared spectroscopy (NIRs) pushes to develop handheld devices devoted to be easily applied for in situ determinations. Consequently, portable NIR spectrometers actually result definitively recognized as powerful instruments, able to perform nondestructive, online, or in situ analyses, and useful tools characterized by increasingly smaller size, lower cost, higher robustness, easy-to-use by operator, portable and with ergonomic profile. Chemometrics play a fundamental role to obtain useful and meaningful results from NIR spectra. In this review, portable NIRs applications, published in the period 2019–2022, have been selected to indicate starting references. These publications have been chosen among the many examples of the most recent applications to demonstrate the potential of this analytical approach which, not having the need for extraction processes or any other pre-treatment of the sample under examination, can be considered the “true green analytical chemistry” which allows the analysis where the sample to be characterized is located. In the case of industrial processes or plant or animal samples, it is even possible to follow the variation or evolution of fundamental parameters over time. Publications of specific applications in this field continuously appear in the literature, often in unfamiliar journal or in dedicated special issues. This review aims to give starting references, sometimes not easy to be found.

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“…FB1 and FB2 concentrations in maize meal were first analyzed for mycotoxins using FT-IR as a quick way to distinguish contaminated meals [ 136 ]. Based on an optimized feature model for NIR spectroscopy, a quantitative assay for AFB1 in maize has been suggested.…”

Section: Instrumental Analysismentioning

confidence: 99%

“…After the screening, the wavelength variables were utilized to create a support vector machine (SVM) and a partial least squares (PLS) test model, respectively, to measure AFB1 in maize. As a result, by using a nonlinear SVM detection model, the characteristics of NIR spectra are beneficial for the rapid and accurate testing of the AFB1 in maize [ 136 ].…”

Section: Instrumental Analysismentioning

confidence: 99%

Recent Advances in Mycotoxin Determination in Fish Feed Ingredients

et al. 2023

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Low-cost plant-based sources used in aquaculture diets are prone to the occurrence of animal feed contaminants, which may in certain conditions affect the quality and safety of aquafeeds. Mycotoxins, a toxic group of small organic molecules produced by fungi, comprise a frequently occurring plant-based feed contaminant in aquafeeds. Mycotoxin contamination can potentially cause significant mortality, reduced productivity, and higher disease susceptibility; thus, its timely detection is crucial to the aquaculture industry. The present review summarizes the methodological advances, developed mainly during the past decade, related to mycotoxin detection in aquafeed ingredients, namely analytical, chromatographic, and immunological methodologies, as well as the use of biosensors and spectroscopic methods which are becoming more prevalent. Rapid and accurate mycotoxin detection is and will continue to be crucial to the food industry, animal production, and the environment, resulting in further improvements and developments in mycotoxin detection techniques.

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Characteristic wavelengths optimization improved the predictive performance of near-infrared spectroscopy models for determination of aflatoxin B1 in maize

Cited by 20 publications

References 27 publications

A comprehensive survey on the chicken swarm optimization algorithm and its applications: state-of-the-art and research challenges

A comprehensive survey on the chicken swarm optimization algorithm and its applications: state-of-the-art and research challenges

Portable NIR spectroscopy: the route to green analytical chemistry

Recent Advances in Mycotoxin Determination in Fish Feed Ingredients

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