Does Sunflower Respond to an Increased Seeding Rate?

I conducted the experiment with Ivan Humenyuk, Director of Innovation at one of the farms in central Ukraine. The farm where Ivan works covers an area of approximately 6,000 hectares. Its main crops are sunflowers, corn, and wheat.

We laid out this experiment in two neighboring sunflower fields. Both have heterogeneous reliefs and yields.

Primary. I assumed that the high-productivity areas would provide nutrients to a larger number of plants. So I increased the planting rate in these areas and decreased it in low-productivity ones. I applied this logic to the whole field.

Alternative. I proposed this hypothesis counter to the primary one. I assumed that field plants would compete for sunlight rather than nutrients and moisture. As such, I lowered the seeding rate in high-productivity areas and increased it in low-productivity ones. To test the alternative hypothesis, I placed one test strip in the field.

The field covered an area of 110 hectares. The field’s relief is not homogenous, featuring a 35-meter difference in elevation.

Limiting factor. I analyzed the relief and compared it to the productivity map. It turned out that the productivity zones closely align with the slope map. In my experience, the bigger the slope, the higher the probability of soil erosion is in these areas. Erosion, therefore, leads to decreased soil fertility. It means that the relief in this field is limiting yield.

Yield map analysis. The harvest was gathered in August, then I exported the yield map from the combine harvester's onboard computer. It seems that yields didn't change in zones with different sunflower seed rate per hectare.

Analyzing the yield in these plots helps to make a more precise assessment of the experiment findings. I manually select noiseless data, compare the average yield in the delimited plots in each productivity zone, and put them in a spreadsheet.

The table shows that seeding rates didn't affect the yield, resulting in 4.15 t/ha with seeding rates of 50,000 and 70,000 seeds per hectare in the high-productivity zone. The sunflower yield neither increased nor decreased. It turns out that if I had known the results in advance, I wouldn't have spent a fortune on seeds.

Let’s name the second field as Lambda

I conducted the experiment in the same way in this field. The only difference is that, in Lambda Field, I looked at sunflower density to see the dependency between the number of plants in the blooming period and seeding rates.

Lambda Field covered an area of 111 hectares. The field’s relief isn’t homogenous due to its drainage hollows with a 15-meter difference in elevation.

Similar to the first field, I analyzed Lambda’s productivity zones and relief. I compared them to understand what is limiting productivity in the field. In this case, the drainage hollows where water usually gathers, and the high slope affected the yield.

Assessing the plant population in the blooming period. We first need to create an orthophoto to count the number of plants in each zone with different seeding rates. This is a photo of the field with a high spatial resolution (in our case, less than 1 cm). Using it makes it easy to manually count plants and find the precise number for each zone. Ivan made the orthophoto using a drone.

I then manually counted how many sunflower heads there were. I had the data on the actual seeding rate for 10×10-meter plots, so I used these squares to count.

The average germination rate in the high-productivity area with a seeding rate of 70,000 per hectare was 78.3%, 79.1% for a seeding rate of 65,000 per hectare, and for a seeding rate of 50,000 per hectare, it was 84.5%.

What does it mean? It means I could save money on seeds. When increasing the seeding rates in high-productivity areas, I noticed a consistent trend of decreased plant density. There was a 6% difference in the germination rate between seeding rates of 50,000/ha and 70,000/ha.

I noticed the same tendency in moderate- and low-productivity areas. There was about a 5−6% difference in the germination rate with high and low seeding rates.

After the field was harvested, I analyzed the yield map and calculated average yield values.

The conclusion for Lambda is the same as for Beta: the sunflower seeding rates didn't affect the yield.

I failed to increase yield. I drew three conclusions from the experiment.

The first is that the variable-rate seeding wasn’t needed in this case. The yield didn’t increase when the seeding rate was changed; on the contrary, the germination rate fell.

The second is that sunflowers are a very flexible crop that can adapt to variable-rate seeding. This year, I plan to continue conducting experiments in sunflower fields to gather enough data to confirm this hypothesis.