Sorting of Fruit Using near Infrared Spectroscopy: Application to a Range of Fruit and Vegetables for Soluble Solids and Dry Matter Content

2004 ◽  
Vol 12 (3) ◽  
pp. 141-148 ◽  
Author(s):  
K.B. Walsh ◽  
M. Golic ◽  
C.V. Greensill
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Dry Matter ◽  
Near Infrared ◽  
Matter Content ◽  
Fruit And Vegetables ◽  
Soluble Solids ◽  
Dry Matter Content

Near-infrared spectroscopy on combine harvesters to measure maize grain dry matter content and quality parameters

2006 ◽  
Vol 125 (6) ◽  
pp. 591-595 ◽  
Author(s):  
J. M. Montes ◽  
H. F. Utz ◽  
W. Schipprack ◽  
B. Kusterer ◽  
J. Muminovic ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Dry Matter ◽  
Near Infrared ◽  
Quality Parameters ◽  
Matter Content ◽  
Dry Matter Content ◽  
Maize Grain ◽  
Combine Harvesters

Towards on-line prediction of dry matter content in whole unpeeled potatoes using near-infrared spectroscopy

Talanta ◽  
2015 ◽  
Vol 143 ◽  
pp. 138-144 ◽  
Author(s):  
Trygve Helgerud ◽  
Jens P. Wold ◽  
Morten B. Pedersen ◽  
Kristian H. Liland ◽  
Simon Ballance ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Dry Matter ◽  
Near Infrared ◽  
Matter Content ◽  
Dry Matter Content ◽  
On Line

Texture of Cooked Potatoes (Solanum tuberosum). 1. Relationships between Dry Matter Content, Sensory-Perceived Texture, and Near-Infrared Spectroscopy

2002 ◽  
Vol 50 (18) ◽  
pp. 5082-5088 ◽  
Author(s):  
Cees van Dijk ◽  
Monica Fischer ◽  
Jörgen Holm ◽  
Jan-Gerard Beekhuizen ◽  
Trinette Stolle-Smits ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Solanum Tuberosum ◽  
Near Infrared Spectroscopy ◽  
Dry Matter ◽  
Near Infrared ◽  
Matter Content ◽  
Dry Matter Content

Use of Visible-Near Infrared Diffuse Reflectance Spectroscopy to Discriminate between Kiwifruit with Properties Altered by Preharvest Treatments

1997 ◽  
Vol 5 (2) ◽  
pp. 113-122 ◽  
Author(s):  
Alistair D. Mowat ◽  
Philip R. Poole
Keyword(s):  
Dry Matter ◽  
Diffuse Reflectance ◽  
Near Infrared ◽  
Diffuse Reflectance Spectroscopy ◽  
Matter Content ◽  
Soluble Solids ◽  
Skin Colour ◽  
Canonical Variate ◽  
Dry Matter Content ◽  
Treatment Groups

Visible-near infrared (NIR) spectra of kiwifruit berries were processed by discriminant analysis techniques to differentiate berries treated during on-vine development. Treatments applied were leaf removal or shading berries with aluminium foil through crop development, or dipping the berries in ethephon two weeks prior to harvest. In order to accentuate the treatment effects, the canes used for individual treatments were cinctured to cut the phloem layer near the central cordon. Diffuse reflectance visible-NIR spectra were measured for all berries at harvest and after storing at 0°C for 16 weeks, and in sound ripened berries, for which the mass, skin colour, soluble solids and dry matter content were also determined. Principal components (PCs) were calculated for the 550–990 nm region of the visible-NIR absorption spectra for 500 berries randomly selected from all treatments. Canonical variate analyses of the PC were used to distinguish the berries from the original treatment groups. At harvest and after storage, discriminant algorithms, based on training spectra, were applied to validation spectra sets and correctly classified 99% and 87% of the berries, respectively, by their on-vine treatment. In the sound ripened berries, discrimination based on the visible-NIR data was superior to that achieved using combinations of mass, skin colour, dry matter and soluble solids.

scholarly journals Infrared Spectroscopy for the Quality Assessment of Habanero Chilli: A Proof-of-Concept Study

2021 ◽  
Vol 8 (1) ◽  
pp. 19
Author(s):  
Joel B. Johnson ◽  
Janice S. Mani ◽  
Mani Naiker
Keyword(s):  
Infrared Spectroscopy ◽  
Infrared Spectra ◽  
Total Phenolic Content ◽  
Dry Matter ◽  
Near Infrared ◽  
Phenolic Content ◽  
Matter Content ◽  
Total Phenolic ◽  
Dry Matter Content ◽  
Near Infrared Spectra

Habanero chillies (Capsicum chinense cv Habanero) are a popular species of hot chilli in Australia, with their production steadily increasing. However, there is limited research on this crop due to its relatively low levels of production at present. Rapid methods of assessing fruit quality could be greatly beneficial both for quality assurance purposes and for use in breeding programs or experimental growing trials. Consequently, this work investigated the use of infrared spectroscopy for predicting dry matter content, total phenolic content and capsaicin/dihydrocapsaicin content in 20 Australian Habanero chilli samples. Near-infrared spectra (908–1676 nm) taken from the fresh fruit showed strong potential for the estimation of dry matter content, with an R2cv of 0.65 and standard error of cross-validation (SECV) of 0.50%. A moving-window partial least squares regression model was applied to optimise the spectral window used for dry matter content prediction, with the best-performing window being between 1224 and 1422 nm. However, the near-infrared spectra could not be used to estimate the total phenolic content or capsaicin/dihydrocapsaicin content of the samples. Mid-infrared spectra (4000–400 cm−1) collected from the dried, powdered material showed slightly more promise for the prediction of total phenolics and the ratio of capsaicin-to-dihydrocapsaicin, with an R2cv of 0.45 and SECV of 0.32 for the latter. The results suggest that infrared spectroscopy may be able to determine dry matter content in Habanero chilli with acceptable accuracy, but not the capsaicinoid or total phenolic content.

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