Predicting Potential Grain Protein Content of Spring Wheat with in-season Hand-Held Optical Sensors. orth Dakota State University orth Dakota State University
Introduction Why is Protein Important in Spring Wheat? Protein increases gluten strength which is associated with increased dough extensibility and quality Protein also increases loaf volume, water absorption, mixing requirement time, and mixing tolerance http://www.yara.com.au
Introduction Protein Premiums In the orthern Great Plains a premium or discount is often placed on Hard Red Spring Wheat (HRSW) at the 14% GPC threshold Premiums are difficult to predict but are influenced by supply, demand, and quality of previous winter wheat crop Premium/Discount (USS) Current Protein Premiums and Discounts for Hard Red Spring Wheat September 22, 2017 30 20 10 0 12.5 13 13.5 14 14.5 15 15.5-10 -20-30 -40 Grain Protein Content http://chssunprairie.com/grain/premiums-and-discounts/#springwheat
Introduction itrogen and Protein As the wheat plant reaches grain-filling, is remobilized from plant tissues to the grain kernel Plant uptake before grain filling will boost yield. Fertilizing to Boost Protein As grain filling begins, that is applied will most likely boost GPC, especially if the plant has ample to boost yield c Foliar applications of urea ammonium nitrate (UA) are often applied post anthesis.
Introduction DVI The availability and affordability of crop health sensors has drastically increased in recent years. Many of these sensors output a ormalized Difference Vegetation Index (DVI), which is a ratio of the near-infrared (IR) and red light reflected back from objects. DVI = ( RRRRRR) (RRRRRR+) DVI has been shown to be very predictive of yield, but it has been much more challenging to predict protein.
Objectives 1. Determine whether there is a predictive relationship between early season DVI and GPC. orth Dakota 2. Determine the earliest HRSW growth stage that has a predictive relationship between DVI and protein.
Experiment Locations Data were taken in 2016 and 2017 from experimental locations in the Red River Valley of orth Dakota and Minnesota. PK Testing was conducted in the fall prior to planting Trial Locations orth Dakota Minnesota
Materials & Methods Based on fall soil tests 4 rates of were applied at planting by following recommendations from the orth Dakota Wheat itrogen Calculator treatments were at realistic rates growers would apply Additional in-season applications were made, but for this experiment only treatments made before the 4-5 leaf were used. 70% recommended rate (77 lbs/acre) 100% recommended rate (110 lbs/acre) 200% recommended rate (200 lbs/acre) Check (0 lbs/acre)
Materials & Methods DVI Sensing In 2016 and 2017 DVI was measured for each plot with a hand-held optical sensor for each treatment at three growth stages: 4-5 Leaf Flag Leaf Boot
Materials & Methods Data Analysis Post-harvest grain protein content was measured using a IR protein analyzer. GPC was then compared with each of DVI values taken at each sensing date using simple linear regression. DVI was further normalized by dividing each DVI value by the DVI value of the 200% application. Total Protein Harvest Calculation To account for the total protein per acre the following calculation was used: Total Protein Harvest = GPC x Yield (lb/acre)
Results & Discussion DVI & GPC Of the three growth stages, DVI taken at the boot stage was the most predictive. Boot DVI > Flag DVI > 4-5 Leaf DVI DVI measured at the boot stage was modestly predictive of GPC at some, but not all, locations. DVI overall was more predictive of total protein (GPC x yield) orth Dakota R 2 =0.06 2016 Trial 2017 Trial R 2 =0.09 R 2 =0.59** R 2 =0.43** R 2 =0.41** R 2 =0.06 R 2 =0.18** Minnesota
Results & Discussion 15 Boot DVI ormalized by Rep vs GPC Red Lake Falls, M 2016 Grain Protein Content (g kg -1 ) 14 13 12 11 10 y = 28.017x - 15.039 R² = 0.591 9 0.9 0.92 0.94 0.96 0.98 1 1.02 1.04 1.06 Boot Stage DVI ormalized by Rep
Results & Discussion 16 DVI ormalized by Rep vs GPC Casselton, D 2017 Grain Protein Content g( kg -1 15 14 13 12 11 10 y = 7.3721x + 6.4483 R² = 0.0598 9 0.86 0.88 0.9 0.92 0.94 0.96 0.98 1 1.02 1.04 Boot Stage DVI ormalized by Rep
Results & Discussion DVI The variability in the predictive ability of DVI may be due to environmental differences Precipitation Soil Range of Total Protein (GPC x Yield) DVI Predictiveness of GPC 8.2 cm 393 2016 Trial 2017 Trial 2016 May Total Precipitation Protein Range 2017 May (kg ha Precipitation -1 ) 2017 Total Protein Range (kg ha -1 ) orth Dakota R 2 =0.06 1 R 2 =0.09 3.4 cm 2.6 cm 5.1 285 cm R 2 =0.59** 8.1 cm R 2 =0.43** R 2 =0.41** 275 1.6 R 2 =0.06 cm R 2 =0.18** 193 446 597 467 Minnesota
Conclusions DVI is most predictive of GPC when it is measured at the boot stage, DVI, at best, is moderately predictive of GPC. Whether DVI is predictive of GPC may be dependent on environmental factors. DVI is limited in distinguishing differences between medium and high protein contents (13-14%). It is much more capable at distinguishing between low and medium protein.
Further Research Unmanned aerial vehicles (UAV) may be a more effective method for measuring DVI and assessing crop health. -rich Strip Because DVI was more predictive of total protein, working to assign a dollar value to the total protein yield would enable us to give better recommendations on the economic viability of added inseason.