Application of near Infrared Spectroscopy On-Combine in Corn Grain Breeding

Abstract

Improving maize (Zea mays L.) grain yield and agronomic properties are major goals for corn breeders in northern Europe. In order to facilitate fi eld grain yield determination we measured corn grain moisture content with near infrared (NIR) spectroscopy directly on a harvesting machine. NIR spectroscopy, in combination with harvesting, signifi cantly improved quality and speed of yield determination within the very narrow harvest time window. Moisture calibrations were developed with 2117 samples from the 2001 to 2003 crop seasons using six diode array spectrometers mounted on combines. These models were derived from databases containing spectra from all instruments. Spectrometer-specifi c calibrations cannot be used to predict samples measured on other instruments of the same type. Standard error of cross-validation (SECV) and coeffi cient of determination (R 2 ) were 0.56 and 0.99%, respectively. Moisture standard errors of prediction (SEPs) for the six instruments, using varying independent sample sets from the 2004 harvest, ranged between 0.59% and 0.99% with R 2 values between 0.92 to 0.98. The six instruments produced the same dry matter predictions on a common sample set as indicated by high R 2 and low biases among them, hence there was no need to apply specifi c standardisation algorithms. Moisture NIR spectroscopy determinations were signifi cantly more precise than those obtained using the reference method. Analysis of variance revealed low least signifi cant differences and high heritabilities. High precision and heritability demonstrate successful implementation of on-combine NIR spectroscopy for routine dry matter (yield) measurements.

Usefulness of portable near infrared spectroscopy in olive breeding programs

“…Significant differences for oil and moisture content were obtained between genotypes with similar grouping for both reference and NIR predicted results (Table 4). Moreover, the analysis of variance between and within genotypes provided similar distribution of sums of squares for reference and predicted data, which indicate that NIR predicted results could be efficiently used for genotype × environment and heritability studies as suggested in other crops (Welle et al, 2005;Posada et al, 2009). Models developed from samples collected in selections plots provided slightly more accurate results than the obtained in samples collected in progenies plots.…”

Near infrared spectroscopy for on/in-line monitoring of quality in foods and beverages: A review

“…In addition, calibration models for determination of dry mater, starch content, in vitro digestibility by cellulase, and soluble sugars in maize forage based on NIR measurements taken directly on the chopper during harvest were developed (Welle et al, 2003). Using a network of six diode arrays, NIR spectrometers were implemented successfully for on-line analysis of dry matter corn grain (Welle et al, 2005). With this method, calibration models were derived from the database of spectra from all six instruments; this eliminated the need to apply specific standardization algorithms when using different NIR instruments.…”

Nondestructive analysis of single plant canola (Brassica napus) seeds using near infra-red spectroscopy.

“…Therefore, DA-NIRS ensures greater accuracy and a short analysis time compared to conventional spectrometers. Although with these benefits, the scientific literature documenting the use of DA-NIRS for the compositional analysis of agricultural crops is limited Niewitetzki et al 2010;Welle et al 2005;Welle et al 2007).…”