Maize starch yield calibrations with near infrared reflectance

Marvin R. Paulsen; Lester O. Pordesimo; Mukti Singh; Steven W. Mbuvi; Binying Ye

doi:10.1016/S1537-5110(03)00082-5

Maize starch yield calibrations with near infrared reflectance

Marvin R. Paulsen, Lester O. Pordesimo, Mukti Singh, Steven W. Mbuvi, Binying Ye

Agricultural and Biological Engineering

Research output: Contribution to journal › Article › peer-review

Abstract

Maize starch yield is affected by variety, environmental growing conditions, and drying conditions. One-hundred gram starch yield tests that predict actual wet milling starch yield were used as a reference method for developing an extractable starch calibration on a NIRSystems Model 6500 spectrophotometer. A maize starch yield calibration was developed from 940 samples and used to predict a validation set of 304 samples. It had a standard error of prediction (SEP) of 1-06, a coefficient of determination r² of 0.77 and a ratio of performance to deviations (rpd) of 2-1. This indicates about 95% of similar samples could have starch yield predicted by near-infrared reflectance within about ± 2.1%. The calibration should be successful in segregating maize lots for high and low starch yield percentages.

Original language	English (US)
Pages (from-to)	455-460
Number of pages	6
Journal	Biosystems Engineering
Volume	85
Issue number	4
DOIs	https://doi.org/10.1016/S1537-5110(03)00082-5
State	Published - Aug 1 2003

ASJC Scopus subject areas

Control and Systems Engineering
Food Science
Animal Science and Zoology
Agronomy and Crop Science
Soil Science

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10.1016/S1537-5110(03)00082-5

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title = "Maize starch yield calibrations with near infrared reflectance",

abstract = "Maize starch yield is affected by variety, environmental growing conditions, and drying conditions. One-hundred gram starch yield tests that predict actual wet milling starch yield were used as a reference method for developing an extractable starch calibration on a NIRSystems Model 6500 spectrophotometer. A maize starch yield calibration was developed from 940 samples and used to predict a validation set of 304 samples. It had a standard error of prediction (SEP) of 1-06, a coefficient of determination r2 of 0.77 and a ratio of performance to deviations (rpd) of 2-1. This indicates about 95% of similar samples could have starch yield predicted by near-infrared reflectance within about ± 2.1%. The calibration should be successful in segregating maize lots for high and low starch yield percentages.",

author = "Paulsen, {Marvin R.} and Pordesimo, {Lester O.} and Mukti Singh and Mbuvi, {Steven W.} and Binying Ye",

note = "Funding Information: Presented as Paper No. 98-F-065 at AgEng Oslo 98 an International Conference on Agricultural Engineering, Oslo, Norway, 24–27 August 1998. This study was a part of Project No. 95077 and 95168 of the Illinois Agricultural Experiment Station, College of Agricultural, Consumer and Environmental Sciences, University of Illinois at Urbana-Champaign. The research was funded in part by the Illinois Council on Food and Agricultural Research. ",

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doi = "10.1016/S1537-5110(03)00082-5",

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T1 - Maize starch yield calibrations with near infrared reflectance

AU - Paulsen, Marvin R.

AU - Pordesimo, Lester O.

AU - Singh, Mukti

AU - Mbuvi, Steven W.

AU - Ye, Binying

N1 - Funding Information: Presented as Paper No. 98-F-065 at AgEng Oslo 98 an International Conference on Agricultural Engineering, Oslo, Norway, 24–27 August 1998. This study was a part of Project No. 95077 and 95168 of the Illinois Agricultural Experiment Station, College of Agricultural, Consumer and Environmental Sciences, University of Illinois at Urbana-Champaign. The research was funded in part by the Illinois Council on Food and Agricultural Research.

PY - 2003/8/1

Y1 - 2003/8/1

N2 - Maize starch yield is affected by variety, environmental growing conditions, and drying conditions. One-hundred gram starch yield tests that predict actual wet milling starch yield were used as a reference method for developing an extractable starch calibration on a NIRSystems Model 6500 spectrophotometer. A maize starch yield calibration was developed from 940 samples and used to predict a validation set of 304 samples. It had a standard error of prediction (SEP) of 1-06, a coefficient of determination r2 of 0.77 and a ratio of performance to deviations (rpd) of 2-1. This indicates about 95% of similar samples could have starch yield predicted by near-infrared reflectance within about ± 2.1%. The calibration should be successful in segregating maize lots for high and low starch yield percentages.

AB - Maize starch yield is affected by variety, environmental growing conditions, and drying conditions. One-hundred gram starch yield tests that predict actual wet milling starch yield were used as a reference method for developing an extractable starch calibration on a NIRSystems Model 6500 spectrophotometer. A maize starch yield calibration was developed from 940 samples and used to predict a validation set of 304 samples. It had a standard error of prediction (SEP) of 1-06, a coefficient of determination r2 of 0.77 and a ratio of performance to deviations (rpd) of 2-1. This indicates about 95% of similar samples could have starch yield predicted by near-infrared reflectance within about ± 2.1%. The calibration should be successful in segregating maize lots for high and low starch yield percentages.

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DO - 10.1016/S1537-5110(03)00082-5

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VL - 85

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EP - 460

JO - Biosystems Engineering

JF - Biosystems Engineering

IS - 4

ER -

Maize starch yield calibrations with near infrared reflectance

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