Automated Crop Receiving With NIR Load Tracking and Analysis
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Solution Overview
Problem
Current methods for tracking and analyzing crop loads at receiving sites are labor-intensive, time-consuming, and often require manual data entry, limiting the ability to provide real-time quality analysis and management of crop storage.
Innovation Solution
An automated system and method utilizing sensors, a spectrometer, and a programmable logic controller (PLC) to detect and analyze crop loads, including identifying truck identifiers, determining crop locations and temperatures, and performing near-infrared spectroscopy to determine crop components, thereby enabling real-time analysis and data storage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual tracking and analysis methods are used for crop loads, then personnel can record and analyze crop data, but the process becomes labor-intensive and time-consuming
Solution Approach 1:
The patent replaces manual mechanical operations with automated electronic systems. Sensors detect truck identifiers, crop locations, and temperatures automatically. A spectrometer performs optical analysis of crop samples without manual intervention. A PLC controller coordinates these systems, eliminating the need for personnel to manually record data, operate sampling equipment, or analyze crops, thereby dramatically improving productivity while reducing labor requirements
Solution Approach 2:
The system enables self-service automation where the equipment performs its own monitoring and analysis functions. The sensors automatically detect and record data as trucks pass through. The spectrometer autonomously analyzes crop samples and generates reports. The PLC controller self-coordinates the entire process flow, allowing the system to operate with minimal human intervention and maintain continuous automated crop load tracking and analysis
2Loss of information
If manual data entry and tracking are used, then personnel can record crop information, but the process requires personnel to be in close proximity to heavy equipment
Solution Approach 1:
The patent replaces manual data entry operations with automated sensing and electronic recording systems. Optical sensors and barcode readers automatically capture truck identifiers without personnel needing to approach vehicles. Weight sensors on the scale automatically record crop loads. The PLC controller electronically stores and manages all data, eliminating the need for personnel to manually record information while maintaining complete data tracking accuracy and removing personnel from hazardous proximity to heavy equipment
Solution Approach 2:
The patent introduces electronic intermediaries between personnel and the crop tracking process. Sensors act as intermediaries that detect truck identifiers, crop locations, and temperatures remotely. The spectrometer serves as an intermediary that performs optical analysis of crops without direct contact. The PLC controller acts as an intermediary that electronically manages data flow, allowing personnel to monitor crop information from a safe distance while maintaining complete data accuracy
3Measurement precision
If samples are sent to an analytical lab for content analysis, then detailed crop composition data can be obtained, but the process takes a few or several days
Solution Approach 1:
The patent replaces traditional laboratory mechanical and chemical analysis methods with optical spectroscopy. The spectrometer uses light interaction with crop samples to rapidly determine composition data including moisture, sugar content, and other components. This optical analysis method provides laboratory-quality precision without the time-consuming mechanical preparation, chemical reagents, and manual procedures required by traditional lab methods, delivering accurate results in minutes rather than days
Solution Approach 2:
The patent changes the physical parameter used for analysis from mechanical/chemical methods to optical spectroscopy. By measuring the interaction of light with crop samples at different wavelengths, the system rapidly determines compositional parameters such as moisture content, sugar concentration, and other chemical constituents. This parameter change enables rapid real-time analysis while maintaining measurement precision comparable to or exceeding traditional laboratory methods
4Quantity of substance
If only 30-40% of truck loads are sampled and tested in a lab, then some quality information is obtained, but growers have analytical information limited to a portion of their delivered loads
Solution Approach 1:
The patent implements continuous automated spectrometer analysis that operates without interruption as trucks pass through the receiving site. Unlike intermittent lab sampling, the spectrometer continuously analyzes every crop load in real-time, providing unbroken streams of quality data for 100% of deliveries. This continuous operation ensures complete crop quality information is captured for all loads while maintaining high sampling rates without the gaps and delays inherent in batch laboratory processing
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
The system significantly reduces labor and time required for crop analysis, allows for real-time reporting of crop quality, and enhances the management of crop storage by providing immediate data on crop loads and locations, thereby improving operational efficiency and safety.
Implementation Method 1
A spectrometer device is configured to determine components of the crops. The spectrometer device may include one or more of the following: a near infrared spectrometer, an infrared spectrometer, an MIR spectrometer, and a Raman spectrometer. The near infrared spectrometer may perform near infrared irradiation encompassing wavelengths such as from 800 to 2500 nm.
Implementation Method 2
a common method to track crop loads is to record the total weight of the truck and the crops on the truck along with an identifier, such as a number or alphanumeric string, or a bar code, RFID tag, or optical character recognition (OCR) code
Data Source
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AI summary
A system analyzes crops provided by a truck on a transport device. The truck enters the transport device to transport and unload the crops. The system includes sensors to detect an identifier of the truck, detect a temperature of the crops, and determine components of the crops. A programmable-logic controller sends paired information between the detected identifier of the truck and the detected location of the crops to a non-transitory storage medium for storage. The processor also sends the detected temperature of the crops and the determined components of the crops to the non-transitory storage medium for storage.