Near‐infrared spectroscopy on combine harvesters to measure maize grain dry matter content and quality parameters

Abstract

Dry matter (DM) content and quality parameters of maize grain are important traits in breeding of maize hybrids. New developments in near-infrared spectroscopy (NIRS) allow to determine DM content and product quality parameters directly on plot combine harvesters. The main objective of our study was to examine the potential of NIRS on combine harvester (NOCH) for determination of DM, crude protein (CP) and starch (ST) contents in maize grain. Plot combine harvesters equipped with spectrometers were used. Eleven locations were harvested in Europe during 2003 and 2004. The NOCH calibration models were developed with standard error of prediction (SEP) and coefficient of determination for validation (R 2 V ) of 1.2% and 0.95 for DM, 0.3% and 0.88 for CP, and 1.0% and 0.79 for ST, respectively. NOCH is a promising technology for determination of DM, CP and ST contents of maize grain for breeding purposes, because it automates the assessment of each harvested plot, and the information for making selection decision is rapidly available to plan the next generation.Maize is one of the three major cereals grown in the world. In development of maize hybrids, primary breeding goals have been grain yield, standability and resistance to biotic and abiotic stresses (Duvick et al. 2004). Improving the nutritional quality of maize grain for human and animal nutrition has received much less attention because it requires expensive, laborious and time-consuming analyses. In recent years, greater emphasis has been given to value-added traits, such as higher contents of protein and oil, which resulted in a more valuable product for livestock and poultry feeding. In addition, new industrial uses of maize grain have been pursued, such as the conversion of starch (ST) to ethanol for producing maize-based fuels. The current diversifying market demands suitable products, thus forcing plant breeders to find efficient tools to screen the breeding material for the traits of interest.In central Europe, the growing season for maize is limited by the length of the frost-free period. Maturity classification of breeding materials and varieties is commonly based on dry matter (DM) content of the grain at harvest. In a typical commercial maize breeding programme, the conventional procedure for determination of DM content and quality traits involves drawing a small grain sample from each harvested plot, weighing immediately after gathering in the field, sample transportation and weighing again after drying in an oven at the station. For determination of quality traits, each sample must be additionally ground for chemical or physical analyses. This whole process is expensive, laborious and time-consuming. Another major drawback for breeding purposes is that the results are commonly available several weeks after harvest, when the selection decision for planting the next generation has already been made. Hence, application of new technologies that increase the efficiency in measuring traits of interest and provide the relevant information for making sel...

Protein concentration inheritance and selection in durum wheat

“…However, the improvement in precision must be weighed against the increased cost of measuring protein on all plots rather than only on those meeting selection criteria for agronomic and disease traits, and whether the increase in precision is sufficient to warrant this cost. Use of near infrared instruments on plot combines (Montes et al 2006(Montes et al , 2007 has the potential to overcome some of the cost limitations to measuring grain protein concentration on all plots, which would permit trend adjustment on a routine basis. Neither the Papadakis method nor the moving mean improved correlations enough to explain all of the variation, which indicates that other factors also affect protein concentration.…”

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

“…The calibration models between NIR spectra and quality parameters were developed by PLS algorithm and validated through cross-validation, with standard error of cross-validation (SECV) of 0.57% and 0.31% for protein and moisture content, respectively. Thereafter, with similar equipment, Montes et al (2006) examined the potential of NIR on combine harvest for determination of dry matter, crude protein, and starch content in maize grain. NIR spectra were collected over a range of 960-1690 nm with the interval of 6 nm, The instrumentation was calibrated by using modified partial least squares (MPLS).…”

Near-Infrared Reflectance Spectroscopy (NIRs) for Determination of Tryptophan Content in Quality Protein Maize (QPM)

“…In addition, we determined the ratio between the SD and the SEP because the quality and robustness of a NIRS calibration can also be judged by the SEP and SD/ SEP; a SD/SEP less than 2 indicates an unsuitable calibration [1].…”

“…However, in the past few years, attempts have been made in biofortification programs to increase the nutritional quality of maize for human and animal consumption [1]. Quality protein maize (QPM) is a type of maize with pronounced amounts of two essential amino acids, lysine (Lys) and tryptophan (Trp), and provides increased nutritional value for protein-deficient populations who depend upon maize as a staple food [2].…”