Breeding and agronomic evaluation of Virginia and Runner-type peanut cultivars for South Carolina, with evaluation and implementation of improved production and harvest systems

Institution:

Clemson University

Budget ID:

1360

Project ID:

438

Report BID:

State:

South Carolina

Region:

South Carolina

State Group:

SC-06

Project Fiscal Year:

2015

Category:

Breeding/Genetics/Biotech

Report Type:

Report Received Date:

Investigator:

Anco

Project NPB Budget:

$100,844

Tests were conducted to evaluate improvement of prototype peanut yield monitor accuracy, especially as related to moisture correction. For the John Deere cotton mass flow sensor, peanut yield prediction relative error increases as a function of moisture content. At lower moisture contents the sensor under-estimates mass flow rate and at higher moisture contents the sensor over-estimates mass flow rate. Additional data under a wider range of conditions will allow for development of a mass flow prediction algorithm which corrects for peanut moisture content. This will require implementation of a cost-effective, on-the-go peanut moisture sensor to be included as a part of the yield monitoring system. Tests were conducted using capacitive and conductive sensors for in-shell measurement of peanut moisture content. The conductive sensor tested shows promise for use on combines, demonstrating average errors of less than 2% moisture content. Analysis of calibration procedures suggested for one prototype yield monitoring system that use of six calibration loads was significantly more accurate than use of three calibration loads and that the first and last several loads of the season should not be used for calibration. Depending on the system(s) commercialized for peanut yield monitoring, the data and results from this analysis of calibration procedures may not be relevant, although the procedures developed and demonstrated can be applied once a peanut yield monitor is commercially available. 

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