Quantification of Mold in Hay by near Infrared Reflectance Spectroscopy

Roberts, Craig; Moore, Kate; Graffis, Don W.; Kirby, H. W.; Walgenbach, R. P.

doi:10.3168/jds.s0022-0302(87)80324-7

Cited by 15 publications

(3 citation statements)

References 12 publications

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“…Preliminary studies on screening tomato puree for excessive mould content by NIR spectroscopy were reported by Davies and co-workers. 4 Roberts and coworkers reported results about chemical and spectral quantification of mould in hay 5 and in contaminated barley 6 by NIR spectroscopy. Aramaki and coworkers 7 estimated mycelial weight in rice koji by NIR.…”

Section: Introductionmentioning

confidence: 96%

Attempts to Determine Mouldiness of Paprika Powder by near Infrared Spectroscopy

Kiskó

1998

Journal of Near Infrared Spectroscopy

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The task of our investigation was to develop a rapid method to detect both viable and dead mould biomasses in spice paprika powder. We tried to explore the relationship between the mould content of the paprika samples and their near infrared (NIR) spectra. Different methods are available for detecting moulds in food. Most of the current methods have disadvantages. In this work the ergosterol assay was chosen as reference method for determining the mould content in the samples because the ergosterol is a mould specific component and it can be satisfactorily determined. Both quantitative and qualitative methods were used for this purpose. For quantitative investigation MLR was used for creating models for determining the mouldiness of a sample (SEC = 6,11, r = 0.89). For qualitative investigation the PQS (Polar Qualification System) was used described by Kaffka and Gyarmati (1991) and the "quality points" of the samples were determined using different spectral ranges. The location of the quality points in the "quality plane" clearly shows the shift of the quality points in the function of the mould content. The NIR technique proved to be very promising as rapid, non-destructive, reagentless method to detect the mould biomass content in paprika powder and there is simple means for monitoring the mycological quality assurance of paprika powder products.

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Section: Introductionmentioning

confidence: 96%

Attempts to Determine Mouldiness of Paprika Powder by near Infrared Spectroscopy

Kiskó

1998

Journal of Near Infrared Spectroscopy

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“…Hirano, Okawara, and Narazaki (1998) developed NIR base method for sorting internally mouldy nuts by comparing the near infra red transmittance ratio of 700-1100 nm and concluded that there is decrease in the transmittance ratio on mould infection due to hydrolysis of triglycerides in nuts. In another study near-infrared reflectance spectroscopy was used to quantify mould by spectrally predicting chitin, a fungal cell wall polymer of glucosamine from moludy alfalfa (Medicago sativa L.) hay samples in the range of 75-710 lg/g (Roberts, Moore, Graffis, Kirby, & Walgenbach, 1987). NIR was also used for analyzing maize samples for fungi infection, ergosterol, and fumonisin B 1 content.…”

Section: Introductionmentioning

confidence: 99%

A rapid FT-NIR method for estimation of aflatoxin B1 in red chili powder

2009

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“…Reports that are more recent show that this technology can estimate nonchemical characteristics as well, particularly in alfalfa. Such nonchemical characteristics have included leaf:stem ratio (Hill et al, 1988), mold content (Roberts et al, 1987), and legume proportion in grass‐legume mixtures (Moore et al, 1990).…”

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confidence: 99%

Estimation of Fall Dormancy in Alfalfa by Near Infrared Reflectance Spectroscopy

et al. 2001

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Estimating fall dormancy (FD) in alfalfa (Medicago sativa L.) is time‐consuming and expensive. The objective of this study was to estimate the FD class of alfalfa using near infrared reflectance (NIR) spectroscopy. Eleven alfalfa cultivars ranging in FD from 1 to 11 were grown as spaced plants at four diverse locations. In early autumn, 55 to 65 plants were randomly selected at each location and FD determined for each plant. For each sample, NIR spectra were collected and FD values regressed against first and second derivative transformations of spectra by modified partial least squares regression. The optimum equation had a calibration R2 of 0.90 and a mean and standard error of 7.93 ± 1.14. Blind validation samples showed that this equation could accurately predict the FD class of individual plants (r2 = 0.85) as well as entire cultivars (r2 = 0.94). We concluded NIR spectroscopy has the potential to estimate FD classes of alfalfa.

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Quantification of Mold in Hay by near Infrared Reflectance Spectroscopy

Cited by 15 publications

References 12 publications

Attempts to Determine Mouldiness of Paprika Powder by near Infrared Spectroscopy

Attempts to Determine Mouldiness of Paprika Powder by near Infrared Spectroscopy

A rapid FT-NIR method for estimation of aflatoxin B1 in red chili powder

Estimation of Fall Dormancy in Alfalfa by Near Infrared Reflectance Spectroscopy

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