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Hd Grid Soil Sampling and Analysis for Advancing Tender - 71126996

The OLDS COLLEGE has issued a Tender notice for the procurement of a Hd Grid Soil Sampling and Analysis for Advancing Agronomy through Hyperlayer Data Collection and Analytics in the Canada. This Tender notice was published on 02 Sep 2022 and is scheduled to close on 16 Sep 2022, with an estimated Tender value of Refer Document. Interested bidders can access detailed Tender information, eligibility criteria, and complete bidding documents by referencing TOT Ref No. 71126996, while the tender notice number is 132-2022 and Registering on the platform.

Procurement Summary

Country: Canada

Summary: Hd Grid Soil Sampling and Analysis for Advancing Agronomy through Hyperlayer Data Collection and Analytics

Deadline: 16 Sep 2022

Posting Date: 02 Sep 2022

Other Information

Notice Type: Tender

TOT Ref.No.: 71126996

Document Ref. No.: 132-2022

Competition: ICB

Financier: Self Financed

Purchaser Ownership: Public

Tender Value: Refer Document

Purchaser's Detail

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Tender Details

Description: N6630n: Soil Testing Kitsb102a: Soil Studiesk107ce: Soil Analysis Services Response Submission: [email protected] - 50Th Streetolds, Alberta Canadat4h 1R6 Response Contact: Patel, Rajpurchasing Specialist4500 - 50Th Streetolds, Alberta T4h 1R6tel: 403-556-4788Email: [email protected] Opportunity Description: the Overarching Goal of this Project is to Develop Predictive Algorithms Based on Machine Learning (Ml) for Estimating the Concentrations of Plant Available Nutrients in the Soil, Instant Identification of Yield Limiting Factors, Calculating Best Achievable Yield Goals, and Automated Calculation of Site-Specific Fertilizer Prescriptions. Multiple Layers of Geospatial Data, such as Multi- and Hyperspectral Imagery, Thermal Imagery, Microwave Soil Moisture Measurements, Ground Penetrating Radar Data, High Density Soil Tests, Soil Compaction, Elevation Data and Field Surface Analysis, Gamma-Ray Soil Spectrometry Analysis, Soil Electrical Conductivity, and Yield Monitoring Data, will be Used to Build New Ml Predictive Algorithms, which will Allow for Automated Analysis of Various Agronomic Field Characteristics Including Plant Available Soil Nutrients and Water, Instant Identification of Yield-Limiting Factors, Automated Calculation of Optimal Fertilizer Rates, and Site-Specific Estimation of Best Achievable Yield Potential. Olds College
Posted: 09.01.2022
Expires Date: 09.16.2022
Category: Services

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