Crop NIR Calibration Using At-Line Sampling Feedback
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Solution Overview
Problem
Existing agricultural technologies fail to effectively link at-line and online measurement data for harvested crops, leading to inaccuracies in chemical analysis due to imperfect NIR device calibration and external factors, which complicates the analysis of crop constituents.
Innovation Solution
An agricultural harvesting machine equipped with an automatic sampling device collects laboratory samples for at-line analysis, linking at-line measurement data with online NIR data to improve calibration and correct NIR measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If online NIR measurement is used for continuous monitoring of crop constituents, then measurement speed and productivity are improved, but measurement precision and reliability deteriorate due to imperfect calibration and external factors
Solution Approach 1:
The system uses at-line measurement results as feedback to continuously calibrate and correct the online NIR measurement data. The control unit compares online NIR measurements with at-line reference measurements and adjusts calibration parameters accordingly, creating a closed-loop system that maintains high measurement speed while improving accuracy through continuous feedback correction.
Solution Approach 2:
At-line measurements serve as an intermediary reference standard to bridge the gap between quick but inaccurate online NIR measurements and accurate but slow laboratory analysis. The at-line measurements mediate by providing periodically updated reference data that corrects the online NIR data without requiring continuous laboratory analysis.
2Measurement precision
If at-line analysis is performed on laboratory samples to ensure accuracy, then measurement precision is improved, but productivity and measurement frequency worsen due to time-decoupled intervals
Solution Approach 1:
The system merges the advantages of both at-line and online measurement approaches by combining periodic at-line reference measurements with continuous online NIR measurements. The control unit integrates data from both sources, using at-line results to calibrate online measurements, thereby achieving both high precision and high frequency measurements simultaneously.
Solution Approach 2:
The system performs preliminary calibration using at-line measurements before and during the harvesting process. By establishing reference calibration curves from at-line analysis of representative samples, the system prepares correction factors that are then applied to subsequent online NIR measurements, enabling fast measurements to be both frequent and accurate.
3Measurement precision
If calibration of NIR measuring device is performed to improve accuracy, then measurement precision is improved, but device complexity and calibration requirements worsen
Solution Approach 1:
The system enables self-calibration by automatically comparing online NIR measurements with at-line reference measurements and adjusting calibration parameters without requiring manual intervention. The control unit autonomously performs calibration corrections based on the difference between measurement types, reducing the complexity of manual calibration procedures while maintaining high accuracy.
4Measurement precision
If automatic sampling device is added to collect laboratory samples for at-line analysis, then measurement precision is improved through representative sampling, but device complexity and cost increase
Solution Approach 1:
The automatic sampling device extracts a small representative portion of the crop stream for at-line analysis while leaving the main crop flow uninterrupted. This extraction approach enables precise reference measurements to be taken from the actual harvest material without significantly complicating the overall harvesting system or requiring major modifications to the crop transport path.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enhances the accuracy and efficiency of NIR measurement calibration by using representative laboratory samples to correct and refine NIR data, allowing for precise analysis of crop constituents across multiple harvesting processes.
Implementation Method 1
an NIR measuring device (25) arranged on the crop transport path (8) for measuring the NIR measurement data of the harvested crop (6)
Data Source
Figure 1
Figure 2a~2b
Figure 3a~3b
AI summary
The invention relates to a method for combining at-line measurement data and on-line NIR measurement data for the analysis of harvested crop (6), wherein an agricultural harvesting machine (3) is provided with at least one working unit (4) for taking up a harvested crop (5) as harvested crop (6) and/or for processing the harvested crop (6), wherein the harvested crop (6) is transported in a crop stream (7) along a crop transport path (8) through the agricultural harvesting machine (3) during operation, wherein the agricultural harvesting machine (3) has an NIR measuring device (25) arranged on the crop transport path (8) by measuring the NIR measurement data of the harvested crop (6),wherein the agricultural harvesting machine (3) has an automatic sampling device (9) arranged on the harvested crop transport path (8) for taking laboratory samples (1) from the harvested crop stream (7) and takes a laboratory sample (1) with the sampling device (9), wherein an at-line analysis device (26) is provided, wherein the laboratory sample (1) is analyzed at-line by measuring the at-line measurement data using the at-line analysis device (26), and wherein the at-line measurement data and the on-line NIR measurement data are linked together in a linking routine for analyzing the NIR measurement data.