By Diane Rowland, Plant Physiologist, UF/IFAS Agronomy Department
The PeanutFARM website (http://agronomy.ifas.ufl.edu/peanutfarm) is a tool developed by the University of Florida Agronomy Department, to assist peanut farmers, consultants, and extension agents. The program provides irrigation scheduling recommendations and monitoring of peanut maturity, on an individual field basis. PeanutFARM has 3 essential functions: 1) Irrigation scheduling management, 2) Adjusted Growing Degree Day (aGDD) calculation, 3.) Prediction of digging date by scanning of pod blast samples.
PeanutFARM provides an irrigation scheduling tool that gives a grower recommendations on when to irrigate based on soil type, crop growth stage, and rainfall. Individual fields can be monitored through a secure account and irrigation recommendations are made automatically as nearby weather station data are downloaded daily.
Adjusted Growing Degree Days (aGDD’s)
Research conducted at the USDA/ARS National Peanut Research Lab and at the University of Florida has shown that an aGDD calculation can successfully predict peanut maturity and harvest date. The aGDD calculation takes into account daily temperatures, rainfall, and irrigation a crop receives through the course of the season to give a harvest prediction and it has been shown that an accumulation of 2500 aGDDs on most cultivars signals an optimum maturity.
The PeanutFARM website automatically calculates aGDDs for every field that a grower initiates on his/her account. This information can be used to give a general prediction of maturity. For example, last year, most peanuts in the lower Southeast were not fully mature until 150 days after planting (rather than 135 days on a normal year). We were able to anticipate this by monitoring the aGDD’s of certain fields.
Pod Blast Scan
Pod blasting peanuts for a maturity profile board, also known as the hull-scrape method, has been the standard tool determining peanut maturity for many years. The tool can be effective if used properly, however, determining the hull color of peanuts can be subjective, thus profile board predictions can vary from person to person.
To help take out the subjectivity, the University of Florida developed a digital image protocol and computer model (DIM) that evaluates the color of blasted pods. The process is based on the maturity profile board, but the DIM eliminates the subjective nature of the color decision by the human eye and allows the computer to make an objective pod color classification.
Previous to this year, growers were able to email images of pods scanned on any type commercial copier/scanner to UF and a “days to dig” prediction was provided on a person to person basis. However, this season the process will become automated, allowing for a simpler, faster, and more convenient process.
Coming in July 2014
A sister page will be launched in July on the PeanutFARM webpage called Peanut Profile. This page will allow a person with a free, PeanutFARM account to upload a scanned peanut profile image to the website and receive an email within minutes, containing a “days to dig” prediction. The team at the UF/IFAS Agronomy Department has developed programming that will automatically analyze that image based on an algorithm, and send an automated email message with peanut harvest timing recommendations.
This new feature will significantly streamline the process of determining peanut maturity in an easy to use format. Farmers will now be able to use the PeanutFARM website through the season to monitor the cumulative aGDDs up to the recommended 2500 for a general prediction of peanut maturity. The next step is to upload a pod blasted sample to the Peanut Profile site, which will give a “days to dig” prediction, thus eliminating the time-consuming process of manually boarding pod samples. This process will insure the most accurate assessment of crop maturity and should expedite the overall assessment of when to harvest peanuts.
For more information and specific questions on the PeanutFarm program, contact Diane Rowland at firstname.lastname@example.org.