Cotton plant height collected by hand versus plant height measured using a sonar device.  Ninety three percent of the variation in plant height could be explained using this indirect method of measurement.

Table 2. Grain Yield for Wheat OFIT 2006 across sites, OK.              

Table 3. Profit earned for Wheat OFIT 2006 across sites, OK.

Preplant N fertilizer price lb^-1: $ 0.40
Topdress N fertilizer price lb^-1: $0.40
Wheat grain price bu^-1: $4.50

3 Point Trials 2006
Profit maximized in 2 of 3 trials using 0-N preplant and the variable N rate applicator (treatment 3). 

Table 1. Nitrogen use efficiency and N fertilizer applied for 2006 Wheat 3 PT Trial at Efaw, Hennessey and Chickasha, OK.

* UAN – 28% N

Table 2. Nitrogen fertilizer, grain yield and profit for 2006 Wheat 3 PT trial at Efaw, Hennessey and Chickasha, OK.

Preplant N price lb^-1: $ 0.40
Topdress N price lb^-1: $ 0.40
Wheat grain price bu^-1: $4.50

February 22, 2006

The Sensor Based Nitrogen Calculator now has 15 functional algorithms for corn, wheat, canola, sorghum and bermudagrass.

Can corn "catch up" when N fertilization is delayed until V6, V10, or VT growth stages?  If no N is applied preplant, it is unlikely that you can produce near maximum yields when N is delayed until V10 growth stages or later.  Ideally, a minimum amount of N is required preplant, with added N applied at or before V10.  The highest NUE's were in general observed from mid-season N applications.  When N fertilization was delayed until VT, grain yields were significantly reduced.

Table 1.  Treatment, Grain Yield, Grain N uptake, and NUE, for Efaw, Oklahoma, 2005.

Table 2. Treatment, Grain Yield, Grain N uptake, and NUE, for Lack Carl Blackwell, Oklahoma, 2005.

Table 3. Treatment, Grain Yield, Grain N uptake, and NUE, for Haskell, Oklahoma, 2005.

The same relationship observed between yield level and NUE was also observed for RI and NUE.  Thus, altering NUE as a function of predicted RI, or predicted yield level will be a next step toward improving the mid-season SBNRC.

Figure 6.  Grain yield prediction equation using the EFAW, LCB, and Hennessey sites from 2004 with the index
developed from the plant competition factor, linear distance, and INSEY (Equation 5).
 

Improving nitrogen use efficiency (NUE) with remote sensing devices is an emerging technology. This study characterized grain yield and biomass yield of corn (Zea mays L.) and evaluated the spatial variability of corn growth in terms of normalized difference vegetative index (NDVI). Four rows, 30 m in length from two locations over two years were randomly selected for this study. A GreenSeeker™ Handheld sensor was used to collect NDVI readings at all possible growth stages during the life cycle of corn. NDVI increased with progression of vegetative growth stages until V10, where a plateau was encountered, followed by a decline in NDVI after the VT growth stage. Coefficient of variation (CV) data from the NDVI readings of each row revealed two dominant peaks during the life cycle of corn, one between the V6 and V8 growth stages and the second during the late reproductive growth stages. The CV data illustrated that the greatest variation expressed by corn during the vegetative growth stages was between the V6 and V8 growth stages. The highest correlation of NDVI with corn grain yield was found at the V7 to V9 growth stages, while CV and plant spacing had the highest correlation from the V7 to V9 growth stages. The CV also had a high correlation with grain and biomass yields at all growth stages. As remote sensing technology progresses, results indicate that the V8 growth stage will be vitally important as a physiological stage to best recognize spatial variability for nutrient application in corn.

Coefficient of variation from NDVI readings determined from 4 separate rows, over growth stages ranging from V3 to VT, EFAW Experiment Station, 2003.

Click on Questions Below to See Video

Jerrel Powell, Farmer near Council Hill, OK
Question: How have you used GreenSeeker Technology?
Question: Why is Nitrogen Important?
Question: What would you like to tell producers in OK about GreenSeeker Technology?

March 10, 2005

It is very difficult to establish relationships between NDVI values and corn grain yield unless readings can be taken by plant.  This is because the large differences in yield, are found at the by-plant resolution.  When NDVI readings were collected by plant, at the V8 growth stage, and then plotted with grain yield (determined 3 months later), you can see the definite trend in NDVI and yield over 16 m of row where each plant was sensed individually, and harvested by plant. This was from a corn field near Ames, IA, where the average over both transects exceed the 2003 state average.  

Consequently, the upper boundary of regression curves fitted for the data reported must approach zero at the genetic yield potential. Similarly, both the range and standard deviation of yield should be small near zero-yield to satisfy results reported by Taylor et al., (1999), and Dobermann et al., (2003).

Seed suppliers do not normally publish genetic yield potential data. However, the National Corn Growers Association Corn Yield Contest results (www.NCGA.com) can serve as a surrogate for these data. In order to achieve maximum yields, contest participants attempt to manage all factors under their control to minimize reduction in corn yield from the cultivars genetic yield potential. First place yields for all classes from 2002, 2003, and 2004 ranged from 19,000 to 22,000kg ha-1. One can infer that these yields approached the genetic yield potential of the corn cultivars, and where by-plant variability would be low.

The standard deviation curve peaked near 13000 kg ha-1 and declined at higher yields. However, most of that decline occurred at yields greater than 15000 kg ha-1. Average field scale corn yields in all areas reported in this paper were much less than 15000 kg ha-1. Clearly, by-plant corn yield variability is large within the yield ranges achieved by producers, and that was delineated to in the by-state and country averages.

(See complete article on this topic)

Figure 1. Relationship between the CV of NDVI readings and winter wheat plant population (7 locations, 2003-2004, multiple seeding rates and 6 varieties).

The observation that CV reached a peak at Feekes 5 to 6 suggests that current timing of application may have to be changed in order to maximize the efficiency of the technology. As to application direction, it was beneficial to see that it does not matter what direction the sensors are traveling across the seed row and that the NDVI values will remain the same. This is extremely important in that the applicators do not have the need to follow any rigid guidelines for the equipment to perform properly.

Figure 2. Change in CV, from NDVI readings collected from three N treatments in winter wheat, over time at the EFAW Research Farm, Stillwater OK (2004).

Is "plant to plant" variability the same whether fixed distances are used between plants or using actual measured distances? Turns out that the expressed variability is actually greater when using fixed distances that do not accurately reflect computed yields based on the area occupied.
 

Experiments documenting by-plant differences in corn grain yield show that variability increases as yield levels increase. This work shows that regardless of yield level, the average hybrid corn grain yield difference from one plant to the next exceeds 2740 kg/ha or 44 bu/ac in producer fields.