Kenneth Hood of Perthshire, Miss., is spending a lot of his time writing prescriptions. No, he hasn't gotten his medical license. The prescriptions Hood is writing are for the variable rate applications of cottonseed, nitrogen, and insecticides he applies to the crops on his Bolivar County farm.
Hood, who was recently featured as a speaker at the 2001 Beltwide Cotton Conference in Anaheim, Calif., says his deep involvement in precision agriculture is paying off with higher yields and lower production costs.
Partnering with the Stennis Space Center, the National Cotton Council, USDA's Agricultural Research Service and Mississippi State University, Hood uses his farm as a test site for much of the emerging technology being developed for agriculture.
Like most farmers, Hood says, he is trying to cut his cost of production. And, he is succeeding in reducing his expenses by using variable rate technology to write site-specific prescriptions for applications of nitrogen, insecticides and plant growth regulators.
He has also discovered substantial cost savings through the use of variable rate technology to determine seeding rates at planting time. "In the Delta, our soils change. We can have anywhere from three to five different soil types from one end of the field to the other," he says. "We're planting three, four, or five cottonseed per foot of row, depending on the soil criteria and the elevation of the soil."
Varying seeding rates within a field is reducing Hood's cottonseed expense anywhere from 31 to 66 percent, and it's optimizing his yield potential, he says. This cost savings is especially important due to the increasing price of seed. "In the past few years we've gone from paying somewhere between $12 and $16 per acre for cottonseed to more than $50 to $60 per acre for cottonseed.
Another area where Hood is using variable rate technology to reduce his crop input expenses is fertility. "We found that going and zoning your soils sometimes is not the best criteria to use to put your plant nutrients out. Instead, we're looking at topography of the soil, sand and clay content of the soil, and water-holding capacity We put all four of these things together and then write our fertilizer prescription from that information.
"We're applying the nitrogen where it is needed most for maximum yield and not applying it where it is not needed." Hood says the practice offers environmental as well as economic benefits, particularly in those areas of a field that may have drainage problems.
Hood is also saving money applying his insecticides only in those areas of a field where they are most needed.He has particularly focused his attention on plant bug control because, in his opinion, plant bugs are becoming a much more serious problem for growers in the Mid-South.
By selectively applying insecticides only areas of a field where the plant bug infestations are located, Hood has drastically cut his insecticide costs. For example, in one 238-acre field he cut his insecticide bill by 34 percent. In another field, Hood realized a 49 percent savings by prescription spraying insecticide, instead of spraying the entire field. In a larger-scale example, he says he saved $4,120 in just one insecticide application on an almost 2,000-acre block of cotton.
In addition, Hood is using weekly satellite imagery of his farm to help determine when he should terminate his cotton crop. The imagery, which enables him to better judge the maturity of his crop, is one way he is using emerging technology to increase his yield potential.
In one recent case, Hood was all set to defoliate a 420-acre field on his farm when he consulted the satellite imagery of that field. Those pictures told him what he was easily able to see - that one side of the field wasn't yet mature enough to terminate. "We waited 10 days to defoliate and, as a result, increased our yield by 150 pounds per acre.
"We, as producers, can generate vast amounts of data for our farms, but I can't tell you that we can handle all of this data in the matter that we ought to," Hood says. "We need a crop production model that would pull all of the data together and spit out what we need to help us make these decisions."