Determination of hardness for maize kernels based on hyperspectral imaging

Qiao, Mengmeng; Yang, Xu; Xia, Guoyi; Su, Yuan; Lu, Bing; Gao, Xiaowei; Fan, Haojun

doi:10.1016/j.foodchem.2021.130559

Cited by 47 publications

(11 citation statements)

References 25 publications

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“…Moreover, there are three absorption peaks in the NIR spectral range that are located in the vicinity of 1000, 1200, and 1450 nm. The absorption peak around 1000 nm may be related to the second‐order frequency doubling of OH stretching vibration (Qiao et al, 2022). In addition, the absorption peak around 1200 nm may be related to the effect of CH stretching the first overtone (Sun et al, 2020).…”

Section: Resultsmentioning

confidence: 99%

Rapid and accurate detection of starch content in mixed sorghum by hyperspectral imaging combined with data fusion technology

Jiang

Tian

et al. 2022

J Food Process Engineering

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Sorghum is a type of brewing material. The starch content of different kinds of mixed sorghum affect the quality and yield of liquor. Therefore, an accurate and efficient detection of its starch content is of great significance to obtain high‐quality and high‐yield of liquor. Based on the data of single visible light (Vis), near‐infrared (NIR), and Vis and NIR fusion, this study develops a genetic algorithm optimization BP neural network (GA‐BPNN) model and a particle swarm optimization support vector machine model. It is deduced that the model based on the data from the Vis and NIR fusion has the highest performance in predicting the starch content of mixed sorghum. For the prediction of amylose, the GA‐BPNN model developed after using the Pearson correlation coefficient to select the characteristic wavelength for fusion, has the highest performance (RMSEP = .0298 and = .9948). For the prediction of amylopectin, the GA‐BPNN model developed after fusion of spectral features extracted by principal component analysis, has the highest performance (RMSEP = .0213 and = .9985). In conclusion, the hyperspectral imaging combined with data fusion can rapidly and accurately detect the starch content of mixed sorghum.Practical ApplicationsAs the single raw material of Maotai‐flavor liquor and the main raw material of Luzhou‐flavor liquor, the amylopectin content of sorghum directly affects the quality of liquor. Its amylose content also affects the yield of liquor. Because the different varieties of sorghum have different amylose and amylopectin content, liquor manufacturers often use several mixed varieties of sorghum as a brewing material. In order to ensure the quality and yield of liquor, it is particularly crucial to detect the amylose and amylopectin content variables of blended sorghum. The traditional sorghum starch content determination methods, such as the chemical detection methods and near infrared spectroscopy, have the disadvantages of destructiveness, low efficiency, and low detection accuracy. In the process of liquor brewing, the traditional detection methods cannot guide the timely adjustment of brewing process parameters. The hyperspectral imaging technology is widely used in food material detection, due to its fast and nondestructive advantages. The data fusion technology can fuse data from different sources of the same object to be detected, in order to obtain more comprehensive data for the development of accurate prediction models. This study uses the hyperspectral imaging combined with data fusion in order to quickly and accurately predicts the starch content (amylose, amylopectin) of mixed sorghum, which has a guiding significance for the timely adjustment of process parameters in the brewing process of liquor. In addition, it provides an accurate method for the component detection of other grains.

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Section: Resultsmentioning

confidence: 99%

Rapid and accurate detection of starch content in mixed sorghum by hyperspectral imaging combined with data fusion technology

Jiang

Tian

et al. 2022

J Food Process Engineering

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“…In quantitative analysis, PLSR is the most often used multivariate analysis method (Liu, Sun, & Ouyang, 2010; Lu et al, 2019; Qiao et al, 2022). The independent and dependent variable data matrices are concurrently deconstructed in PLSR, and the dependent variable information is included into the independent variable data decomposition process.…”

Section: Methodsmentioning

confidence: 99%

Assessment of kiwifruit firmness by using airflow and laser technique

Sun

Luo

et al. 2023

Journal of Texture Studies

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Firmness is a valid and widely acknowledged indication of fruit quality that is directly connected to physical structure and mechanical qualities. The deformation signals of kiwifruit for firmness assessment were acquired using an assessment system based on airflow and laser technology in this investigation. Using partial least squares regression (PLSR), genetic algorithm optimization of bp neural network (GA-BP), and an extreme learning machine (ELM), deformation data from kiwifruit was used to create models of Magness-Taylor penetration firmness prediction. The ELM model outperformed the PLSR model, and GA-BP model in the prediction set, with a correlation coefficient of 0.876 and a root mean squared error of 3.576 N in the prediction set. These findings showed that an assessment system based on airflow and laser techniques can be utilized to assess the firmness of kiwifruit quickly and nondestructively.

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“…In cereals crops according to the yield maize has the highest yield in the world (Ahmad et al 2021). The demand for maize increased day by day by increasing the Human population (Qiao et al 2022). Maize is produced about 1.05 million thousand tonnes/annual over the entire world (Ahmad et al 2021).…”

Section: Introductionmentioning

confidence: 99%

Foliar application of silicon-based nanoparticles improve the adaptability of maize (Zea mays L.) in cadmium contaminated soils

Ahmed

Iqbal

Ahmad

et al. 2023

Environ Sci Pollut Res

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Heavy metals (HMs) are a serious threat all over the world and show a different impact on plants and human life by contaminating the plant. Among all HMs cadmium (Cd) is one of the serious metals that are absorbed by the roots of the plant and are transported from root to leaves and fruit. Cd stunted plant growth causes the death of plants, causes, and disturbance in photosynthetic machinery and nutrient homeostasis process. Based on a serious problem a controlled experiment was conducted in the

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Determination of hardness for maize kernels based on hyperspectral imaging

Cited by 47 publications

References 25 publications

Rapid and accurate detection of starch content in mixed sorghum by hyperspectral imaging combined with data fusion technology

Rapid and accurate detection of starch content in mixed sorghum by hyperspectral imaging combined with data fusion technology

Assessment of kiwifruit firmness by using airflow and laser technique

Foliar application of silicon-based nanoparticles improve the adaptability of maize (Zea mays L.) in cadmium contaminated soils

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