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Institut für Pflanzenzüchtung, Saatgutforschung und Populationsgenetik

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    Application of Near-Infrared Spectroscopy in Plant Breeding Programs
    (2006) Montes, Juan Manuel; Melchinger, Albrecht E.
    The success of plant breeding programs depends on the availability of genetic variation and efficient data collection processes that allow large-scale screenings of genotypes. When genetic variation is present, the goal is to identify those genotypes that are closest to the breeding objectives. In this context, the evaluation of a large number of genotypes requires optimization of the data collection process in order to provide reliable information for making selection decisions. The process of data collection must yield an accurate and precise assessment of genotypes timely because the information is needed to plan the next generation for breeding and cultivar development. Laboratory NIRS is routinely used in the data collection process of many breeding programs, but it requires the withdrawal of field plot samples and involves manual work. Applications of the near-infrared spectroscopy on choppers (NOC) and near-infrared spectroscopy on combine harvester (NOCH) are a step forward to the automation of data collection processes, by which sampling, labor, and sources of error in the data can be reduced. The objective of this thesis research was to assess the potential of NOC and NOCH for application in breeding programs of grain maize, rapeseed, and silage maize. Plot combine harvesters and choppers were equipped with diode-array spectrometers for collection of near-infrared plot spectra, and used to harvest experimental varieties of breeding programs in Central Europe. Two alternative sample presentation designs (conveyor belt and spout) were used for the NOC systems. The NOCH systems used the conveyor belt as sample presentation design. NOCH showed a high potential for determination of dry matter (DM), crude protein (CP), and starch (ST) contents of maize grain. NOCH calibration models yielded standard errors of prediction (SEP) and coefficients of determination of validation (R2V) of 1.2% and 0.95 for DM, 0.3% and 0.88 for CP, and 1.0% and 0.79 for ST, respectively. The potential of NOCH for determination of DM, CP, oil and glucosinolate contents of rapeseed was also high. NOCH calibration models yielded standard errors of cross validation (SECV) and coefficients of determination of cross validation (R2CV) of 0.3% and 0.96 for DM, 0.6% and 0.69 for CP, 0.9% and 0.71 for oil, and 2.2 μmol/g and 0.40 for glucosinolate, respectively. The NOC systems showed high potential for the determination of DM, ST, and soluble sugars (SS) content of silage maize hybrids. The NOC system equipped with a conveyor belt design yielded calibration models with SEP and R2V of 0.9% and 0.93 for DM, and 2.1% and 0.78 for ST, respectively. For the NOC system equipped with the spout design, the SEP and R2V amounted to 1.4% and 0.84 for DM, 2.3% and 0.75 for ST, and 0.9% and 0.81 for SS. The potential of both NOC systems for determination of fiber contents (CF, ADF, and NDF), digestibility and energy-related traits was lower than for DM, ST, and SS. The precision of NOCH for the determination of DM content in maize grain was higher than by traditional drying-oven method. A higher precision of NOCH is also expected for other traits and may also be extended to the NOC systems because the sampling error associated with traditional processes of data collection is reduced drastically by NOC and NOCH. The investigation of the effects caused by the calibration technique, mathematical transformation of the near-infrared spectra, and scatter correction on the development of NOCH calibration models for the prediction of DM, CP, and ST content in maize grain revealed that calibration technique was the most important factor affecting the prediction ability, whereas the importance of mathematical transformation and scatter correction depended on the particular constituent considered. Presently, there exists high uncertainty about the optimal NOC and NOCH sample presentation designs for agricultural harvesters. The dynamic signal range, i.e., the range of spectral values on which predictions are based, and the amount of plot material measured were identified as guide parameters for optimization of sample presentation designs. In addition, calibration transferability between NOC systems with different sample presentation designs proved to be feasible after merging spectra from both NOC systems in the calibration set. In conclusion, NOC and NOCH show high potential for replacing laboratory NIRS analysis of several traits in a plant breeding context and yield a more accurate and precise evaluation of field plot characteristics. Therefore, technological applications of the electromagnetic radiation is predicted to have a high impact in plant breeding, precision farming, and agriculture.