Nondestructive measurement of pectin polysaccharides using hyperspectral imaging in mulberry fruit

Yang, Liang; Gao, Huaqi; Meng, Liuwei; Fu, Xiaping; Du, Xiaoqiang; Wu, Di; Huang, Lingxia

doi:10.1016/j.foodchem.2020.127614

Cited by 45 publications

(27 citation statements)

References 37 publications

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“…The Daqu reflectivity curve of spectral set I was quite smooth with no obvious absorption peaks, which may be because the major substances in Daqu are not sensitive to the visible spectrum. In addition, the visible light spectrum mainly reflects the chromatic number feature of the sample when detecting fruit pectin content (Yang et al, 2021; Zhu, Huang, Wu, Chen, & He, 2017). Three absorption peaks at 980 nm, 1,200 nm and 1,470 nm can be observed in spectral set II, which were associated with the overtones and combinations of the fundamental vibrations of OH, CH, and NH functional groups, respectively (Lin & Ying, 2009; Wang, Wang, et al, 2020).…”

Section: Results and Analysismentioning

confidence: 99%

Detecting total acid content quickly and accurately by combining hyperspectral imaging and an optimized algorithm method

Jiang

Huang

et al. 2021

J Food Process Engineering

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The total acid content of Daqu during fermentation directly influences the quality of the Daqu. Hyperspectral imaging (HSI) was used to rapidly and accurately detect the total acid content of Daqu. The performances of two spectral ranges obtained by two hyperspectral cameras for Daqu total acid content were compared. Different pretreatment methods were used to build the partial least squares regression (PLSR) model, and the optimal pretreatment for the corresponding spectra was determined. A combination of principal component analysis (PCA) and successive projection algorithm (SPA) was used to select the feature wavelengths. The PCA algorithm optimized by SPA was more accurate than the PCA algorithm alone when extracting the feature wavelengths. PLSR, backpropagation neural network (BP), and the backpropagation‐genetic algorithm (BP‐GA) model were developed to predict the total acid content of the Daqu samples by using the full wavelengths and feature wavelengths, respectively. The predictive performance of each model was compared and analyzed. The optimal model was the MSC + PCA‐SPA+BP‐GA model (Rc2 = 0.8832, RMSEC = 0.1163, Rp20.25em = 0.9724, RMSEP = 0.0593, RPD = 4.2860, AB_RMSE = 0.0570). In addition, the distribution of total acid content within the region of interest (ROI) of Daqu samples was visualized at different fermentation stages using the optimized model. These results show that HSI technology can rapidly and precisely detect the total acid content of Daqu and visualize the content distribution, which provides important technical support for upgrading and transforming the liquor. Practical Applications Daqu is the saccharifying agent, leavening agent, and aroma‐generating agent of liquor brewing. During the fermentation process, the total acid content is an important indicator for the quality evaluation of Daqu. Therefore, it is highly significant to detect the total acid content in Daqu quickly and accurately. The HSI technique is widely used to detect the contents of various substances in food. In this study, the HSI technique combining the PCA‐SPA and BP‐GA algorithms was established to detect the total acid content of Daqu, and a satisfactory result was obtained, showing that HSI technology combined with an optimized algorithm could be used to realize rapid and accurate detection of the total acid content of Daqu. In addition, the predictive model proposed in this study is not only applicable for detecting other food substances but also this method has great potential for real‐time indicators detection in winery for future work.

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Section: Results and Analysismentioning

confidence: 99%

Detecting total acid content quickly and accurately by combining hyperspectral imaging and an optimized algorithm method

Jiang

Huang

et al. 2021

J Food Process Engineering

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“…Another remote-controlled field robot, RobHortic, equipped with color, multispectral, and hyperspectral (400-1000 nm) cameras and specific software, has been developed and tested under field conditions for the detection of infected plants (symptomatic and asymptomatic) with "Candidatus Liberibacter solanacearum", across carrot fields, with an accuracy of about 60 %, based on several machine learningbased models [68]. Other common applications of Vis-NIRS MHS imaging comprise the sorting of horticultural products by assessing their external (EQA) and internal quality attributes (IQA) in the postharvest, with portable, benchtop devices and in automated grading lines [1,31,35,36,66,[69][70][71][72][73], commercialized by several vendors (e.g., Aweeta, Maf-Roda, Greefa, Compaq, Unitec). The majority of these commercial devices, particularly those installed on inline grading systems, seldom provide their actual proven assessment capacity due to industrial secrecy.…”

Section: Elastic Spectroscopymentioning

confidence: 99%

“…It is worth mentioning the development of a hyperspectral insect damage detection algorithm in coffee, which can automatically detect insect-damaged beans using only a few bands and one spectral signature [70]. The demonstration of the feasibility of using these imaging techniques to rapidly measure pectin polysaccharides in intact mulberry fruits is also of significance [72]. Furthermore, their utility for high-throughput phenotyping of plant chemical traits was also established for maize and soybean plants in a greenhouse exposed to varying levels of either water deficit and nutritional stress [7].…”

Section: Elastic Spectroscopymentioning

confidence: 99%

“…This is of the utmost importance when considering the assessment of fruit ripening on-tree across different plots of an orchard or in different orchards and essential to depart from the "proof of concept" approach and embrace the real-life conditions. Secondly, there is the effect of the rind in the assessment of the pulp quality attributes in thick rind fruit, since the NIR radiation hardly reaches the fruit pulp and both biochemical and optical properties have a major role to play in the spectral data acquired [1,[59][60][61]70,72]. Thirdly, in spite of the different spectral ranges, levels of accuracy and cost-effective portable devices, only a few have been effectively used on-tree to assess fruit quality and ripening, for there are many conditions such as light and temperature that diminish the devices performance and deteriorate the calibration models predictions, as observed for citrus [10,11,66,[82][83][84][85].…”

Section: Elastic Spectroscopymentioning

confidence: 99%

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Making Sense of Light: The Use of Optical Spectroscopy Techniques in Plant Sciences and Agriculture

et al. 2022

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As a result of the development of non-invasive optical spectroscopy, the number of prospective technologies of plant monitoring is growing. Being implemented in devices with different functions and hardware, these technologies are increasingly using the most advanced data processing algorithms, including machine learning and more available computing power each time. Optical spectroscopy is widely used to evaluate plant tissues, diagnose crops, and study the response of plants to biotic and abiotic stress. Spectral methods can also assist in remote and non-invasive assessment of the physiology of photosynthetic biofilms and the impact of plant species on biodiversity and ecosystem stability. The emergence of high-throughput technologies for plant phenotyping and the accompanying need for methods for rapid and non-contact assessment of plant productivity has generated renewed interest in the application of optical spectroscopy in fundamental plant sciences and agriculture. In this perspective paper, starting with a brief overview of the scientific and technological backgrounds of optical spectroscopy and current mainstream techniques and applications, we foresee the future development of this family of optical spectroscopic methodologies.

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“…Pectin is an acidic heteropolysaccharide formed by D-galacturonic acid units connected through α-1,4 glycosidic bonds and can be found mainly in the primary cell wall and intercellular regions of higher plants. For this reason, it can be extracted from food processing waste and used as a natural additive in the food industry itself (YANG et al, 2021). In addition, due to its physical properties such as gelling, selective permeability to gases, among others, as well as its characteristics such as biodegradability, biocompatibility, edibility and chemical versatility, pectin can be used as a polymer matrix in the preparation of edible packaging with bioactive properties (OLIVEIRA et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Use of fruit epicarps to formulate pectin-based bioactive films / Utilização de epicarpos de frutos para formulação de filmes bioativos à base de pectinas

Júnior¹,

Santos²,

Aguiar³

et al. 2021

Braz. Ap. Sci. Rev.

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The functional properties of biofilms can vary according to the biopolymer used as the raw material; thus, in the search for alternative sources for preparation of biodegradable films, fruits and vegetables have been used to extract compounds of interest with applications in the food industry. The objective of this work was to obtain and characterize bioactive films based on pectin extracted from the epicarps (skin) of the fruit. The genipap (Genipa americana), red pitaya (Hylocereus polyrhizus) and star fruit (Averrhoa carambola) were collected, washed, pulped and dried at 50 °C for 24 h, and their epicarps were ground and subjected to pectin extraction using the casting method. The films were characterized as to their visual appearance, moisture, pH, water solubility and antioxidant activity. The pectin-based films of G. americana and H. polyrhizus showed a yellowish color, while A. carambola was dark brown. The highest pectin yield (29%) and moisture content (13.9%) were obtained from the H. polyrhizus film, while A. carambola showed the highest solubility in water (98.6%) and had the highest pH (3.9). Additionally, the film based on A. carambola showed greater antioxidant potential against ABTS (30.5%) and DPPH (34%), as well as greater reducing power (0.262 absorbance at 750 nm) and content of total phenolic compounds (553 mg GAE/100 g), whereas H. polyrhizus had a higher percentage of chelating ability (27%). The physicochemical characteristics and bioactive properties exhibited make the film formulation a viable alternative for the food industry.

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Nondestructive measurement of pectin polysaccharides using hyperspectral imaging in mulberry fruit

Cited by 45 publications

References 37 publications

Detecting total acid content quickly and accurately by combining hyperspectral imaging and an optimized algorithm method

Detecting total acid content quickly and accurately by combining hyperspectral imaging and an optimized algorithm method

Making Sense of Light: The Use of Optical Spectroscopy Techniques in Plant Sciences and Agriculture

Use of fruit epicarps to formulate pectin-based bioactive films / Utilização de epicarpos de frutos para formulação de filmes bioativos à base de pectinas

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