Grain moisture content is an important factor for the management of harvesting and postharvest operations and for capacity planning in grain harvest, storage and preservation, and a basis for pricing in grain trade. The advantage of rapid and non-destructive on combine moisture content determination is set against the disadvantage of lower measurement accuracy. The objectives of this study are to determine the agreement of on combine grain moisture measurement with laboratory measurement methods, and to assess the suitability of on-combine grain moisture measurement. The appropriateness of on-combine measurement of grain moisture content for the management of harvesting and postharvest operations and capacity planning by maintaining a defined acceptable level of disagreement was also investigated. On-combine moisture measurement (OMC) was compared with two dry-oven methods and two capacitive moisture sensors used in laboratories, in each case for unground and ground grain. Field trials with on-combine moisture measurements and manual sampling were carried out on two farms in Germany in 2014. A total area of 514 ha with 201 manual samples was used for the investigations. The assessment of on-combine moisture measurement indicated that the on combine approach is suitable for quantifying the variability of grain moisture content. The deviation between indirect laboratory methods and on-combine moisture meters was sufficient to determine the allowable total error that agreed with the defined relative error of two percentage points moisture content. In combination with fuzzy classification of grain moisture measurements, the on-combine moisture meters are suitable for process control and capacity planning for grain harvest and preservation. (C) 2017 IAgrE. Published by Elsevier Ltd. All rights reserved.

Grain harvesting is one of the most weather-dependent processes in agriculture. Grain moisture contents decide on machinery use and costs and determine the necessary grain harvesting and preservation capacities of farms. The objective of this work is to investigate whether and how recent climate changes in the German state of Brandenburg affect the available field time and the required combine harvester capacity. Weather data, the beginning of harvesting, available hours with defined grain moisture contents and total required harvesting capacity are analyzed for the years 1961-2013 for winter wheat, winter rye, winter barley and spring barley. The trends found differ for the four cereal crops. Compared with 53 years ago, today harvesting starts significantly earlier for two cereal crops (-16 days for spring barley and -11 days for winter wheat). The available harvesting hours show a clear and highly significant increase for winter wheat (up to +9%), a distinct and highly significant decrease for winter barley (up to -20%), as well as a slight and significant decrease for winter rye (up to -3%). Inter-annual variability decreases for winter wheat and increases for winter barley. The unfavorable changes for winter barley do not ultimately affect the total required machinery capacity due to the separate harvesting period and relatively small cropping area for winter barley. In contrast, the primarily favorable trends for winter wheat lead to an increase in the total required combine harvester capacity, since the earlier harvesting period overlaps with the rye harvesting period. (C) 2014 Elsevier B.V. All rights reserved.

Quality is an essential attribute of agricultural products and production processes. Wheat (Triticum aestivum L.) quality is primarily classified according to protein concentration and sub-classified depending on additional parameters, such as moisture content, sedimentation value and Hagberg falling number (HFN). Real-time sensing of grain protein concentration by means of near-infrared reflectance spectroscopy (NIRS) is an established method of assessing cereal grain quality during harvest. The objective of this study was to obtain NIRS calibration models for determining α-amylase activity of wheat and to identify changes of wheat quality. Performance characteristics were obtained during field trials in 2011 and 2012. HFN predictions correlated with reference measurements (R2 = 0.70). The standard deviation of differences between the NIR-predicted and reference values denoted as standard error of prediction was 37 s. Processed data were classified using principal component analysis, the prediction range of HFN and Hotelling T2-statistics. The average difference of NIR HFN estimation and HFN laboratory analysis was 34 s. The results obtained indicated that the use of near-infrared reflectance inline spectroscopy on combine harvesters can provide information for grain growers to optimize grain processing and marketing.

EU legislation establishing limits and sampling plans for mycotoxins has come into force recently. Thresholds for mycotoxins emphasise the necessity of food safety monitoring at the beginning of the grain processing chain. The availability of rapid detection methods of mycotoxin contamination in agricultural commodities is still limited. Thus improved methods for grain quality monitoring and processing should be established. Imaging techniques in combination with NIRS are expected to be applicable for the inline analysis of Fusarium spp. and mycotoxin contamination.

Near-infrared spectroscopy (NIRS) is a well-established and standardized method for the analysis of agricultural products.These on/in-line applications have established their control capability in food processing.The online-analysis and the segregation of grain according to specified quality parameters on-combine have been investigated in a completed research project, whereas the main focus of the following research project is on the in-line-analysis of quality parameters in combination with imaging techniques. The taxonomy of process depends on the proximity of process analyzers to the process line [1]. While in-line-sensing allows in situ measurements of grain quality, on-line sensing is characterized by the need for a mechanical transport system. In comparison to on-line measurement, the in-line analysis requires ruggedly designed equipment as well as robust calibration methodologies to fulfill the demands of realtime monitoring and processing of grain on-combine.

A production processes in particular as a result of European Commission Regulations. Moreover, sorting of grain based on protein concentration could enable growers to realise price premiums in value-added markets. The variability of soils, topography and fertility are known to influence grain yield and quality. Interdependency of these factors has also been considered as limitation for site-specific nitrogen management strategies. The aim of this collaborative research project is to monitor protein concentration variability and to segregate grain into quantities of high or low protein content on a combine harvester. Near-infrared spectrometry (NIRS) was used to determine protein concentration of winter wheat and spring barley in both diffuse reflection and diffuse transmission in field trials in Brandenburg and Thuringia. Performance characteristics were obtained during the 2008 and 2009 field trials, a total of 300 ha of wheat and 60 ha of barley were harvested. Protein predictions correlated well with reference measurements (Barley: R2 = 0.94, SEP = 0.31 %; Wheat: R2 = 0.96, SEP = 0.33 %). Deviations of NIRS analysis results beyond the calibration error were logged constantly and helped to ensure correct grain tank filling. Process data were also classified using principal component analysis (PCA), the prediction range of protein values, their standard deviation as well as the hotelling T2statistics. Segregation results are accurate and promising for implementation as a tool to improve grain marketing. The results are sufficiently promising to suggest that monitoring of grain properties and segregation of grain according to defined quality parameters are technically feasible on an operating combine harvester.

Getreidebestande zeigen in Abhangigkeit von Standortheterogenitat und Bestandesfuhrung neben quantitativen Ertragsdifferenzen oft auch ausgepragte Qualitatsschwankungen im Ernte-gut. Ziel des Forschungsprojektes, das im Folgenden vorgestellt wird, ist die Online- Bestimmung qualitatsbestimmender Inhaltsstoffe im Gutstrom von Lebensmittel-, Futter- und Energiegetreide mittels des bewahrten Verfahrens der Nah-Infrarot-Spektroskopie (NIRS). Angestrebt wird die Trennung von Getreidepartien nach defi nierten Qualitatsparametern wahrend des Mahdruschs. Damit wurde die Voraussetzung geschaffen, dass das Verfahren der qualitatsdifferenzierten Getreideernte zukunftig im Rahmen eines Qualitatssicherungssystems eingesetzt und damit den Forderungen nach einer transparenten Lebens- und Futtermittelproduktion entsprochen werden kann.

Near-infrared spectroscopy (NIRS) has experienced widespread use as an analytical tool in agriculture in the last decades. NIR applications are used for online grain quality monitoring on combine harvesters. The objective of this research project is to implement Process Analytical Technology (PAT) on a combine harvester. The term Process Analytical Technologies (PAT) is used to describe "a system for designing and controlling manufacturing through timely measurements (i.e. during processing) of critical quality and performance attributes for raw (..) materials and processes with the goal of ensuring final product quality". [1] Applied to combining, critical protein values are defined to sort grain into fractions of high and low quality on an operating combine harvester.