An Automated Near‐Infrared System for Selecting Individual Kernels Based on Specific Quality Characteristics

Dowell, Floyd E.; Maghirang, Elizabeth B.; Graybosch, Robert A.; Baenziger, P. S.; Baltensperger, David D.; Hansen, L. E.

doi:10.1094/cc-83-0537

Cited by 49 publications

(43 citation statements)

References 20 publications

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“…Both means were higher than those observed in durum wheat (Dowell et al 2006;Crosbie et al 2007;Tahir 2008), but they were similar to those detected by Sissons and Hare (2002) in khorassan wheat. These high values could be connected with long life cycles of these materials.…”

supporting

confidence: 72%

Association between the HMW-glutenin subunits and gluten strength characteristics in khorassan wheat lines - Short Communications

Carmona¹,

Caballero²,

Álvarez³

2009

CZECH J GENET PLANT

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Khorassan wheat (Triticum turgidum ssp. turanicum Jakubz em. A. Löve & D. Löve) is an ancient tetraploid wheat that was grown in the Mediterranean region and Near East. Sixteen lines differing in the composition of high-molecular-weight glutenin subunits (HMWGs) were evaluated for SDS-sedimentation volume and quality index (QI). The data suggested that the two subunit combinations detected in the examined materials at the Glu-b1 locus showed differences in both characteristics (relatively higher levels at the presence of the subunit combination 7+15 compared to 6+8). Weak gluten is in general characteristic of this wheat species. It could be used in a better way for other baking applications than for the pasta industry.

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supporting

confidence: 72%

Association between the HMW-glutenin subunits and gluten strength characteristics in khorassan wheat lines - Short Communications

Carmona¹,

Caballero²,

Álvarez³

2009

CZECH J GENET PLANT

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“…A number of applications have been reported using SKNIR in wheat and maize for quality and fungal infection [4][5][6][7][8]14,21,22,25 , as well as for protein 4,26 and hardness 4,17 in wheat. In barley, there have been a number of recent reports on SK measurements for grain hardness 2,13,[15][16][17]19 .…”

Section: Introductionmentioning

confidence: 99%

Development of a Single Kernel NIR Barley Protein Calibration and Assessment of Variation in Protein on Grain Quality

Fox¹,

Kelly²,

Sweeney³

et al. 2011

Journal of the Institute of Brewing

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In this paper, we describe results from a preliminary experiment on the development of a near infrared reflectance (NIR) calibration for single kernel (SK) % protein content in barley. The SKNIR calibration was developed using kernels from breeding lines and commercial barley varieties with a range in protein content of 7.3% to 16.6% "as is" . The calibration model produced an R 2 = 0.903, while the validation set had a R 2 = 0.837 with a standard error of cross validation and a standard error of prediction of 0.8% for both the calibration and validation sets respectively. The calibration was then used to estimate the variation in % protein of 4,000 single kernels from a commercial variety (Gairdner at 9.3% protein) by segregating kernels into six sub-groups (<7.8%, 7.9-8.3%, 8.4-9.0%, 9.1-9.7%, 9.8-10.4%, >10.5% "as is" ). These sub-groups then had additional grain quality tests carried out including grain size, thousand kernel weight and NIR estimates of % protein, starch, hardness and barley hot water extract (HWE). The results showed an increase in grain size, and a decrease in HWE from the low to high % protein sub-groups. While only a single variety was used in the SKNIR protein segregation study, the results suggested SKNIR could be used to screen for the variation in grain quality traits based on variation in protein content.

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“…The prediction of constituent concentrations using NIR spectroscopy on intact single seeds has been most successful for plants with small seeds and those with a relatively uniform distribution of seed constituents, such as rapeseed, wheat, sunflower achenes or soybean seeds [36][37][38][39][40]. The potential of NIR spectroscopy for non-destructive determination of quality parameters, including oil and protein contents in shell-intact cottonseed, was also reported [41].…”

Section: Determining Grain Composition At Harvestmentioning

confidence: 99%

An Overview on the Use of Infrared Sensors for in Field, Proximal and at Harvest Monitoring of Cereal Crops

2015

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Farmers are increasingly demanding rapid, cost-effective, easy-to-use and non-destructive methods for monitoring changes in the physical and chemical characteristics of crops and plants from the early stages of crop development until harvest. Remote and proximal sensor tools have been used recently to monitor different aspects of cereal production (e.g., fertilization, crop diseases). Most of these tools are characterized as non-destructive, non-invasive and easy-to-use, and most of them are based in near-infrared (NIR) spectroscopy. This article reviews recent and potential applications for the use of proximal sensors based on NIR spectroscopy to monitor dry matter (DM), yield, nitrogen and diseases in different cereal crops.

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An Automated Near‐Infrared System for Selecting Individual Kernels Based on Specific Quality Characteristics

Cited by 49 publications

References 20 publications

Association between the HMW-glutenin subunits and gluten strength characteristics in khorassan wheat lines - Short Communications

Association between the HMW-glutenin subunits and gluten strength characteristics in khorassan wheat lines - Short Communications

Development of a Single Kernel NIR Barley Protein Calibration and Assessment of Variation in Protein on Grain Quality

An Overview on the Use of Infrared Sensors for in Field, Proximal and at Harvest Monitoring of Cereal Crops

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