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Yield Monitors and Maps BAE 4213 April 12, 2007 Randy Taylor Biosystems and Ag Engineering What Are the Tasks? Measure grain flow Mass or Volume Flow Sensor Measure ground speed Existing ground speed sensor or position sensor signal Program harvest width Programmed as a constant value or changed on-the-go Combine position GPS Position Sensor Flow Sensors Yield Monitor Errors How do we calculate yield mass mass Yield area length width Yield errors must be related to one of these 3 measurements: mass, length, width For a yield monitor Mass is determined from the flow sensor Width is a programmed constant Length is determined from speed Width When do errors occur? header not full (i.e. harvest width does not match header width) How do we fix it? Adjust on the go => bad idea How much error are we really talking about? U of Missouri research found it was 8-12% in drilled beans if they assumed constant full header How much do you have to reduce harvest width to get area (field) to be accurate? Distance Errors UNL Research harvesting up & down slope found no significant difference in mass accumulation. However they found a 42’ difference going uphill verses down on a 6% slope Though GPS was the intended speed signal, differences in end points was not observed in a GIS The greater distance measurements going uphill cause a reduction in calculated yield Mass Flow Measurement Errors Combine Dynamics Calibration Combine Dynamics Crop is cut or removed from plant Conveyed to feeder house in the header Conveyed to threshing unit (cylinder or rotor) ~80% of separation should occur during threshing ~20% of grain goes on to separation (rotor or straw walkers) Grain that falls on the cleaning shoe should pass through near the front of the shoe Grain that goes through the returns All of these affect the grain flow relative to its former location in the field Mass Flow Sensors Lag/Resonance Time Sensor Calibration Response to mass flow is non linear Diaphragm vs Triangular Can get a very good fit with linear Operating at points away from one calibration can cause errors Where do we see these? Start and stop grain flow Transitional Mass Flow What Causes Error? 20 R2 = 0.78 10 R2 = 0.61 R2 = 0.53 Error, % 0 0 -10 10 2 20 R = 0.86 30 -20 -30 -40 Average Mass Flow, lbs/s 40 50 Ranking Plots 40 Yield Monitor Rank 35 30 Project 2 Project 3 Project 4 Project 5 Project 6 Ideal 25 20 15 10 5 0 0 10 20 Actual Rank 30 40 Using YM for OFR 50% of the error between weigh wagon and yield monitor weights was due to mass flow Correlation between yield monitor and weigh wagon weights was 0.97 Regression results lead to the same conclusions regarding the treatments Challenging to rank treatments with YM data What Can a Yield Map Tell Us? Soil fertility, type, etc. Disease or insect pressure Variety differences Poorly drained areas Compacted areas Does not point out the yield limiting variable, it only indicates the response to it Using YM Data 1. 2. 3. 4. Diagnosing Crop Production Estimating Nutrient Removal On-Farm Research Establishing Yield Potential (Goals) 1. Diagnosing Crop Production Probably the most widespread use for yield maps today Print maps to keep records on Select appropriate ranges Number of ranges Spread (don’t create or exaggerate variability) Color scheme Problem Diagnoses Wire worm infestation Crop drowned Presenting Yield Maps 5 – 6 ranges or groups maximum Based on Natural Break Even Intervals Predefined Crop Standard Deviation Percent of Average Color Scheme Dryland Wheat Even Intervals 1996 1997 Dryland Wheat Predefined Crop 1996 1997 Dryland Wheat Percent of Average 1996 1997 Normalized Yield (96-97) Data Aggregation Point data Contouring Some type of interpolation Likely have minimal or confusing choices Grid Interpolated Averaged Summed Points versus Interpolation How many of the dark blue points are zero yield? Header Status Raised the mean yield about 5 bu/ac, but did it really make a difference? Irrigated Corn/Beans Normalized Yield 1996 Beans/Corn Beans Corn 1997 Corn Average of Two Years Interpreting Patterns Straight lines are manmade Parallel with travel At an angle with travel patterns Irregular patterns are generally naturally occurring Lines Areas/patches Sand Pivot (1996-97 Crops) Yield Variability Many causes of yield variability Yield monitors and maps don’t determine the cause Yield maps display the location and magnitude (area and degree) This information should lead to better decisions Yield Variability That which can be changed Fertility That which must be managed Soil physical properties 3. On-Farm Research Has the potential to expand knowledge about individual farms Comparison of varieties, tillage practices, fertility rates, etc. Not as easy as it may seem What do you want to know? Why do you want to know it? Layering Maps Yield Topsoil Population 1998 Corn - Osage County 165 Yield, bpa 160 155 150 145 22500 25500 28500 140 135 0 2 4 6 Topsoil, inches 8 10 4. Prescribing Spatial Inputs Some input recommendation models require the use of a crop yield goal Development of a nutrient recommendation map may require the use of a yield goal map How can you generate variable yield goals? Yield Stability Analysis Data were obtained with various yield monitors Converted to point yield and unrealistic values were removed Data were block averaged to 180 foot cells ‘Whisker Plots’ of YM Data 0.4 0.2 0.0 -0.2 0 20 40 60 80 100 120 140 160 180 -0.4 -0.6 -0.8 -1.0 0.0 -0.2 0 20 40 60 80 100 120 140 160 -0.4 -0.6 -0.8 Rank 0.4 Mean Relative Difference 0.2 -1.0 Rank 0.2 0.0 -0.2 Mean Relative Difference Mean Relative Difference 0.4 0 20 40 60 80 100 -0.4 -0.6 -0.8 -1.0 Rank 120 140 160 180 Points are the mean relative difference for each cell Bars are the standard deviation of yield through time. 180 Classification Maps Mean Relative Difference Standard statistical analysis offers minimal insight into spatial data Low yielding cells tend to be more variable There is a better opportunity to classify consistently low yielding areas Because like classed cells were spatially contiguous, this method showed more promise than typical methods Conclusions Yield monitor data can be used for anything that yield data are used for 1. 2. 3. 4. Diagnosing Crop Production Estimating Nutrient Removal On-Farm Research Establishing Yield Potential (Goals)