Non-destructive prediction of total soluble solids, titratable acidity and maturity index of limes by near infrared hyperspectral imaging
暂无分享,去创建一个
[1] R. Poppi,et al. Quality evaluation of frozen guava and yellow passion fruit pulps by NIR spectroscopy and chemometrics. , 2016, Food research international.
[2] Anupun Terdwongworakul,et al. Quantitative prediction of nitrate level in intact pineapple using Vis–NIRS , 2015 .
[3] D. Bulanon,et al. Spectral reflectance characteristics of citrus canker and other peel conditions of grapefruit. , 2009 .
[4] Da-Wen Sun,et al. Recent developments and applications of image features for food quality evaluation and inspection – a review , 2006 .
[5] Jerome J. Workman,et al. Practical Guide and Spectral Atlas for Interpretive Near , 2012 .
[6] Dolores Pérez-Marín,et al. Developing universal models for the prediction of physical quality in citrus fruits analysed on-tree using portable NIRS sensors , 2017 .
[7] Kerry B. Walsh,et al. Non-invasive assessment of pineapple and mango fruit quality using near infra-red spectroscopy , 1997 .
[8] Lembe S. Magwaza,et al. Application of Vis/NIR spectroscopy for predicting sweetness and flavour parameters of ‘Valencia’ orange (Citrus sinensis) and ‘Star Ruby’ grapefruit (Citrus x paradisi Macfad) , 2017 .
[9] Byoung-Kwan Cho,et al. Determination of origin and sugars of citrus fruits using genetic algorithm, correspondence analysis and partial least square combined with fiber optic NIR spectroscopy. , 2008, Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy.
[10] Wouter Saeys,et al. NIR Spectroscopy Applications for Internal and External Quality Analysis of Citrus Fruit—A Review , 2012, Food and Bioprocess Technology.
[11] Yud-Ren Chen,et al. Machine vision technology for agricultural applications , 2002 .
[12] J. Blasco,et al. Recent Advances and Applications of Hyperspectral Imaging for Fruit and Vegetable Quality Assessment , 2012, Food and Bioprocess Technology.
[13] José Blasco,et al. VIS/NIR hyperspectral imaging and N-way PLS-DA models for detection of decay lesions in citrus fruits , 2016 .
[14] Desire L. Massart,et al. Estimation of partial least squares regression prediction uncertainty when the reference values carry a sizeable measurement error , 2003 .
[15] José Blasco,et al. Visible–NIR reflectance spectroscopy and manifold learning methods applied to the detection of fungal infections on citrus fruit , 2015 .
[16] Shigeki Nakauchi,et al. Image analysis operations applied to hyperspectral images for non-invasive sensing of food quality – A comprehensive review , 2016 .
[17] P. Geladi,et al. Hyperspectral NIR imaging for calibration and prediction: a comparison between image and spectrometer data for studying organic and biological samples. , 2006, The Analyst.
[18] Zhang Jianqiang,et al. Detection of Thrips Defect on Green-Peel Citrus Using Hyperspectral Imaging Technology Combining PCA and B-Spline Lighting Correction Method , 2014 .
[19] C. Greensill,et al. Sorting of Fruit Using near Infrared Spectroscopy: Application to a Range of Fruit and Vegetables for Soluble Solids and Dry Matter Content , 2004 .
[20] Chunjiang Zhao,et al. Fast detection and visualization of early decay in citrus using Vis-NIR hyperspectral imaging , 2016, Comput. Electron. Agric..
[21] L. Smith. Pineapple specific gravity as an index of eating quality , 1984 .