NUE Workshop: Improving NUE using Crop Sensing, Waseca, MN Comparing Different Remote Sensing Approaches for Early Season Nitrogen Deficiency Detection in Corn Yuxin Miao1, David J. Mulla1, Gyles W. Randall2, Jeff A. Vetsch2, and Roxana Vintila3 1. Precision Agriculture Center, University of Minnesota. 2. Southern Research and Outreach Center, University of Minnesota. 3. Research Institute of Soil Science and Agrochemistry (ICPA), Romania.

Different Sensing Approaches for Precision N Management Chlorophyll Meter: SPAD 502 GreenSeeker: CropScan Multispectral Radiometer:

Different Sensing Approaches for Precision N Management Aerial or Satellite -based Remote Sensing: High spatial resolution remote sensing images are potentially cheaper, more efficient and more spatially detailed than chlorophyll meter or other ground-based hand-held sensors. Hyperspectral Remote Sensing (Image from http://www.eoc.csiro.au/hswww/Overview.htm)

Objectives Identify hyperspectral bands (wavelengths), band ratios and vegetation indices that are sensitive to early season corn plant N status; To compare the effectiveness of different sensing approaches to monitor early season corn plant N status and detect N deficiency: SPAD Meter; GreenSeeker; CropScan multispectral radiometer; Aerial hyperspectral remote sensing; and, Aerial multispectral remote sensing (simulated).

Materials and Methods – Study Sites Field 1: Corn-Soybean Rotation Field 2: Corn-Corn Rotation

Materials and Methods – N Treatments 3 x 15.2 m Field 1, Corn-Soybean Rotation

Materials and Methods – N Treatments Field 2, Corn-Corn Rotation

Materials and Methods – Data Collection N Concentration: V9: Whole plant sampling, 10 plants: N concentration, biomass; R1: Ear leaf, 10 leaves; Harvest: grain and stover. SPAD Meter: F1: V9, V11, R1, and R3; F2: V7, V9-10, V12, R1, R3 Collected 30 readings from each plot. GreenSeeker: F1: V9 and V11; F2: V8, V9-10, V11-V12 and V12. CropScan Multispectral Radiometer: V6 and V9; About 50 cm above the canopy, three samples each plot.

Materials and Methods – Data Collection Aerial Hyperspectral Remote Sensing: AISA-Eagle (AE) Hyperspectral Imager 61 bands from 392 – 982 nm, at 8.76 – 9.63nm; At 0.75 m spatial resolution; V9, R1, R2 and R4; Pixels of the central two rows in each plot were averaged; Simulated Multispectral Remote Sensing: Landsat ETM+ sensor’s four broad bands: Blue: 450-515nm; Green: 525-605nm; Red: 630-690 nm; NIR: 775-900nm.

Materials and Methods – Band Combinations Simple Ratio (SR) Ratio Definition Reference Green Index Zarco-Tejada & Miller (ZTM) PSSRa PSSRb PSSRc SPRI SR1 SR2 SR3 SR4 SR5 SR6 SR7 R554/R677 R750/R710 R800/R680 R800/R635 R800/R470 R430/R680 NIR/Red = R801/R670 NIR/Green=R800/R550 R700/R670 R740/R720 R675/(R700 x R650) R672/(R550 x R708) R860/(R550 x R708) Smith et al., 1995 Zarco-Tejada et al., 2001 Blackburn, 1998 Penuelas et al., 1994 Daughtry et al., 2000 Buschman and Nagel, 1993 McMurtrey et al., 1994 Vogelman et al., 1993 Chappelle et al., 1992 Datt, 1998

Materials and Methods – Band Combinations Difference Index (DI) and Normalized Difference Index (NDI) Index Definition Reference DI1 DVI NDVI Green NDVI PSNDb PSNDc NPCI NPQI SIPI mND705 mSR705 NDI1 NDI2 NDI3 R800-R550 R800-R680 (R800-R680)/(R800+R680) (R801-R550)/(R800+R550) (R800-R635)/(R800+R635) (R800-R470)/(R800+R470) (R680-R430)/(R680+R430) (R415-R435)/(R415+R435) (R800-R445)/(R800-R680) (R750-R705)/(R750+R705-2 x R445) (R750-R445)/(R705-R445) (R780-R710)/(R780-R680) (R850-R710)/(R850-R680) (R734-R747)/(R715+R726) Buschman and Nagel, 1993 Jordan, 1969 Lichtenthaler et al., 1996 Daughtry et al., 2000 Blackburn, 1998 Penuelas et al., 1994 Barnes et al., 1992 Penuelas et al., 1995 Sims and Gamon, 2002 Datt, 1999 Vogelman et al., 1993

Materials and Methods – Band Combinations Integrated Index (II) Index Definition Reference MCARI TCARI OSAVI TCAVI/OSAVI TVI MCARI/OSAVI RDVI MSR MSAVI MTVI [(R700-R670)-0.2x(R700-R550)](R700/R670) 3x[(R700-R670)-0.2x(R700-R550)(R700/R670)] (1+0.16)(R800-R670)/(R800+R670+0.16) 0.5x[120x(R750-R550)-200x(R670-R550)] (R800-R670)/SQRT(R800+R670) (R800/R670-1)/SQRT(R800/R670+1) 0.5x[2xR800+1-SQRT((2xR800+1)2-8x(R800-R670))] 1.2x[1.2x(R800-R550)-2.5x(R670-R550)] Daughtry et al., 2000 Haboudane et al., 2002 Rondeaux et al., 1996 Broge and Leblanc, 2000 Zarco-Tejada et al., 2004 Rougean and Breon, 1995 Chen, 1996 Qi et al., 1994 Haboudane et al., 2004 Broad Band Combinations NIR/Green; NIR/Red; Blue NDVI; Green NDVI; Red NDVI.

Materials and Methods – Analysis Correlation analysis; Multiple linear regression; Nitrogen Sufficiency Index (NSI) Yield, Plant N, SPAD, or index NSI = x 100% Reference value F1: the average of the highest two preplant N rates: 168 and 202 kg ha-1. F2: 224 kg ha-1. NSI of Plant N Concentration as standard

Results and Discussion: Plant N Variability 36.1 34 31.9 28.2 24.9 CV = 9.33% CV = 14.06% 18.7 202 kg ha-1 224 kg ha-1

Results and Discussion: Impact of N Rate on Reflectance CropScan MSR Hyperspectral RS

Results and Discussion: Sensitive Wavelengths Correlation between plant N concentration and CropScan reflectance at V9 760-1000nm 560-710nm

Results and Discussion: Sensitive Wavelengths Correlation between plant N concentration and hyperspectral reflectance at V9 742-982nm 554 and 563nm 695nm

Results and Discussion: Sensitive Indices Correlation with Plant N Concentrations at V9 Field 1 Field 2 CropScan: GNDVI: 0.51 0.72 NIR/Green: R800/R550 0.50 0.71 NDI2 0.39 0.71 Hyperspectral: NDI1 0.47 0.78 NDI2 0.41 0.79 SPAD Meter: 0.58 0.85 GreenSeeker NDVI: 0.26 0.49 Simulated Landsat ETM+: GNDVI: 0.31 0.68

Results and Discussion: Multiple Regression Correlation Coefficient Field 1 Field 2 SPAD Meter: 0.58 0.85 CropScan: 6 (F1)/5(F2) bands 0.77 0.79 5 (F1)/4(F2) Indices 0.67 0.79 Hyperspectral: 4 bands 0.73 0.89 4 (F1)/3(F2)indices 0.66 0.88 Simulated Landsat ETM+: 3 bands 0.56 0.89 2 indices 0.57 0.88

Results and Discussion: N Sufficiency Index

Results and Discussion: N Deficiency Detection Treatment Level, Field 1, Corn-Soybean Rotation CropScan Hyper Landsat ID Yield Plant N SPAD GS G TVI NIR/G 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Results and Discussion: N Deficiency Detection Treatment Level, Field 2 CropScan Hyper Landsat ID Yield Plant N SPAD GS SR7 DI1 NIR 1 2 3 4 5 6 7 8 9 10 11 12 13 14

Results and Discussion: N Deficiency Detection Plot Level, Field 1, Corn-Soybean Rotation Deficient Plots Sufficient Plots DS SD Overall Accuracy (%) Plant N Content 34 (44) 26 (16) 100 SPAD Meter 3 26 48 (35) GreenSeeker 15 17 19 9 53 (47) CropScan: MCARI 22 14 12 12 60 (60) Hyperspectral: MCARI 25 11 9 15 60 (55) Landsat ETM+: Green 17 15 17 11 53 (62)

Results and Discussion: N Deficiency Detection Plot Level, Field 2, Corn-Corn Rotation Deficient Plots Sufficient Plots DS SD Total Accuracy (%) Plant N Content 29 (46) 27 (10) 100 SPAD Meter 21 25 8 2 82 (71) GreenSeeker 10 26 19 1 64 (43) CropScan: TCARI/OSAVI 18 22 11 5 71 (59) Hyperspectral: SR7 21 22 8 5 77 (61) Landsat ETM+: NIR/Green 17 20 12 7 66 (57)

Results and Discussion: Promising Indices Normalized Difference Index 2 (NDI2) R850-R710 NDI2 = R850-R680

Results and Discussion: Promising Indices Simple Ratio 7 R860 SR7 = R550 x R708

Conclusions than in corn-soybean rotation field at V9; The sensors performed better in corn-corn rotation field than in corn-soybean rotation field at V9; The NIR region was most sensitive to N deficiency at V9; Reflectance at around 550-560 nm, 696 nm, and NIR region was highly correlated with corn plant N concentration at V9; SPAD meter readings and GreenSeeker NDVI data had the highest and lowest correlation coefficients with corn plant N concentration, respectively; Hyperspectral aerial remote sensing has a good potential to monitor spatial corn N variation, and identify N deficiency at V9, especially in corn-corn rotation fields; SR7 and NDI2 were promising indices for N deficiency identification and deserve further testing.

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