Researchers Seek the Best Seeding Rate for Yield Potential

Researchers Seek the Best Seeding Rate for Yield Potential

Growers who have been around long enough don’t need to be reminded just how much the cost of a bag of seed has risen in recent years.

As seed companies pack more research and genetic advancements into each seed, the costs have skyrocketed. As recently as 1996, a 10 pound bag of seed could be sold at retail for as little as $7. By 2010, the same size bag could go for as much as $70, a ten-fold increase in less than two decades. Growers and subsequently researchers across the Cotton Belt have taken notice.


“As far as plant populations, many studies have been done on this throughout the Cotton Belt,” says Dr. Ed Barnes, director of agricultural and environmental research at Cotton Incorporated.

One such study that Barnes has kept an eye on has been conducted by researcher Sam Wang, a cropping systems specialist with the University of Arizona, in conjunction with Dr. Randy Norton. Wang conducted his studies at the Maricopa Agriculture Center in Maricopa, AZ.

Wang set out to at least narrow the range of recommended planting rates for growers in his area. The commonly accepted range of 20,000 to 55,000 plants per acre left a lot of room for either over- or under-population.

“We wanted to give them a more narrow range so that they could really focus on what works best,” says Wang. “Normally, growers we talked with would plant too high or too dense when left with such a wide recommended range.”

Wang chose two very specific varieties for his research – Deltapine DP 0949 B2RF and Stoneville ST 4498B2RF. The idea was to study varieties that have notably different plant architecture.

“The DP 0949 B2RF grows tall and compact, while the ST 4498B2RF has more of a bushy shape,” says Wang. “We wanted to see how these different types of plants respond to different rates of plant population.”

Wang used four 40-inch wide rows and 40 feet long plots at varying rates of density at his fields in Maricopa. The plots were in sandy loam soils, and all were furrow irrigated. Tests were conducted at nine different plant population rates, ranging from 5,000 plants per acre to 70,000 plants per acre.

Given these conditions, Wang varied his plant density per acre with both varieties, and found a noteworthy pattern. Typically, yields rose at a stable rate as density rose from 5,000 plants per acre to 30,000 plants per acre and up to 35,000 plants per acre. Wang says that once populations rose past 35,000 plants per acre, the lint yield plateaued. The similar lint yield held as plant population increased, until the plants per acre rose past 50,000. At this point, the data reflected a clear decline in yield per acre.

In the first year of the study’s existence, Wang enlisted a local farmer at Marana, AZ, who conducted two properly replicated and randomized trials using PHY 499WRF in one field and PHY 375WRF in another, on a larger, working scale. Those results corroborated Wang’s findings that cotton at 35,000 plants per acre yielded better than 29,000 plants per acre or 42,000 plants per acre.

That data supported the long-held belief that overpopulation can strain an individual plant’s ability to yield to its full potential. This is especially true in less than ideal soil scenarios.

“For variable rate planting, a general strategy is to lower planting rates in the weaker soil types for two reasons,” says Barnes. “First, you want to lower plant to plant competition for limited water and nutrients. Secondly, there is less to risk in lower yield soils. That is, if you do not get a good stand in a soil that will only yield 0.5 bales per acre on a good day, that will not be as big a problem as getting a poor stand on a field that has a three bale per acre yield potential.”

Wang points out that a related benefit to lower plant populations is uniformity within a given field. He focused much of his study during this research on the performance of individual plants.

“It’s consistent with ecological principles of plant population, when the plant density is low, the variation among the plants is low,” says Wang. “So you have plants in a field that are all a similar size. When this happens, you have about 60 percent of the plants that are above average size, meaning the majority of the plants are contributing to lint yield.

“Conversely, in a high density plot, you get some plants with a large size, but about 60 percent of the plants are smaller than average. This means that there are a lot of plants in that field that are not being very productive. Their contributions to yield are very small,” says Wang.

Both Wang and Barnes recognize that there are other variables that may come into play when a grower is deciding how densely to populate a given field. In those instances where a cotton producer may opt for a more sparsely populated field, Barnes says growers should keep emergence rates in mind.

“The low end of that commonly accepted range of 20,000 assumes you will have 20,000 plants that emerge,” says Barnes. “So, you would want a higher seeding rate of at least 25,000 to make sure you have that many plants. Also, this low rate assumes the plants are evenly distributed. It does not apply to skippy stands.”

Another factor to consider when choosing a plant population rate is the maturity rate of a given crop. Growers in northern regions of the Cotton Belt who require a shorter-maturing variety should consider planting a higher seeding rate.

“Dense populations – usually involving 15 inch or tighter row spacings – do typically result in an earlier crop,” says Barnes.

So, while other factors will come into play when deciding how densely to populate a field, researchers like Wang and Barnes are giving growers a better idea of how to maximize their own yield potential. At the very least, Wang hopes his research has helped narrow the wide range of options growers face when contemplating plant populations.

“We want to help them save on their input costs and have better yields, for sure, but we want them to have a better idea of how density affects individual plant performance, too,” says Wang. “We wanted to narrow that range so a farmer won’t go too low or too high.”