WinField: Here’s What We’re Seeing So Far This Season

One of the most important things you can do throughout the season to help increase yield potential is to ensure your crops have adequate nutrition. You can check nutrient levels by working with your agronomist to take multiple tissue samples throughout the season (often in concert with soil samples) to determine if critical nutrients are lacking.

More than 300,000 tissue samples have been analyzed through the WinField NutriSolutions 360 system over the past six years, building a robust plant nutrition database to help farmers make fact-based planning decisions. Combining this information with traditional soil testing and other advanced technologies provides the means to identify precise plant nutrient programs that can help achieve excellent return potential.

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Here is a quick rundown of what we’re seeing currently in corn, soybean and wheat crops in our area; recommendations for optimal times to take tissue samples during the season; and what national NutriSolutions tissue sampling data is telling us about the most deficient nutrients.

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Corn

In-field snapshot: It’s been cool into May, and we’ve even had snow in some areas. As of early May, we were still waiting for corn to emerge with warmer weather. Certain areas have received large amounts of rainfall in mid- to late-May, and watching those areas for nitrogen deficiencies will be important.

Tissue sample timing: We recommend taking tissue samples at the V4 to V8 time frame, right before the corn starts taking up large amounts of nutrients with a huge growth spurt. Then again at V10 to V12 to make sure the plant has adequate nutrients. The last one would be late in the season, such as at the dent stage, to do a comparison with what was found at the beginning.

Tissue sample trends: Of the more than 41,500 NutriSolutions corn tissue samples taken in 2014, the most common nutrient deficiencies were zinc (approximately 75% of tissue samples were deficient), nitrogen (nearly 70% were deficient), and boron and potassium (both were approximately 65% deficient).

Soybeans

In-field snapshot: We began doing soybean tissue sampling in late May. In South Dakota, we consistently see zinc and manganese deficiencies in this crop. But the biggest deficiency is potassium. Potassium is vital in soybeans, because it contributes to plant health and keeps the plant metabolizing.

Tissue sample timing: Take your first tissue sample at V3 to V5 when plants are just above ankle high, to see what early-season nutrient adjustments should be made. Take the second sample between R1 and R4 — between when the plant starts to flower and when it is filling out its pods — to learn how the nutrients are fitting in the plant and make sure the pods are filling correctly.

Tissue sample trends: The nearly 10,000 NutriSolutions soybean tissue samples taken in 2014 indicated the most common deficiencies were copper (just over 60% of tissue samples were deficient), potassium (approximately 52% were deficient) and manganese (nearly 40% were deficient).

Wheat

In-field snapshot: Wheat was emerging from late-April through May, and we will be taking our first tissue samples from late-May to mid-June to look for any micronutrient deficiencies (particularly zinc and copper); and any macronutrient deficiencies (particularly nitrogen).

Tissue sample timing: The first tissue samples should be taken during tillering/early jointing, because the plant will start growing rapidly and we want to make sure we have the right nutrients in place. The second samples should be taken right around flag leaf. Boron will be especially important at this time, because it helps arrange the spikelets in the head, which will help with reproduction. We’ll also be looking for proper copper levels.

Tissue sample trends: Of the more than 2,500 NutriSolutions wheat tissue samples taken in 2014, the most common deficiencies were boron (approximately 75% of samples were deficient), magnesium (nearly 70% were deficient), copper (just over 60% were deficient) and zinc (just under 60% of samples were deficient).

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