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Chair of Plant Nutrition Technical University of Munich Discriminating Nitrogen Status Parameters of Maize Cultivars with High-throughput Phenotyping Friederike Gndinger and Urs Schmidhalter Chair of Plant Nutrition, TUM International

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Chair of Plant Nutrition Technical University of Munich

Friederike Gnädinger and Urs Schmidhalter Chair of Plant Nutrition, TUM

Discriminating Nitrogen Status Parameters of Maize Cultivars with High-throughput Phenotyping

International Nitrogen Conference 2016 Melbourne, 5th December 2016

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Chair of Plant Nutrition Technical University of Munich

2 Friederike Gnädinger

Rising world population requires higher yield production
Climate change is a challenge for sustainable and future-oriented agriculture
Optimizing nitrogen management by decreasing N-inputs and environmental N losses
Search for better performing and more efficient maize cultivars

by developing efficient phenotyping procedures to assess

nitrogen uptake
nitrogen use efficiency

and to compare different sensor systems

Aim Needs

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Chair of Plant Nutrition Technical University of Munich

3 Friederike Gnädinger

Methods

A B

A) Unmanned aerial vehicle picture of the field experiment B) Sensors mounted on a tractor measure radiation reflection

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Chair of Plant Nutrition Technical University of Munich

8 early and late maturing cultivars

(Lapriora, Severus, Saludo, Vitallo, Cannavaro, Barros, KWS 9361, P8105 )

Three fertilizer levels at 50, 150, 250 kg N/ha
4 replicates (plot size 14 m x 4 m, 6 rows, 0.66 cm

between rows)

Three biomass samplings at flowering, kernel dough

stage and grain maturity

Plants were separated into leaves, stems and cobs
Biomass and nitrogen contents of leaves, stems and

cobs were separately determined

Friederike Gnädinger 4

Methods

Experimental and destructive phenotypic procedures

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Chair of Plant Nutrition Technical University of Munich

5 Friederike Gnädinger

Spectral assessments

Active sensors (Ntech GreenSeeker RT100,

Holland Scientific CropCircle ACS 470, TUM ALS N-Sensor)

Passive sensor (passive spectral

spectrometer): wavelengths 300 nm - 1700 nm

Recording 5 reflectance values per second

at 4 km/h tractor speed

Co-registration of spectral measurements with

GPS data; Trimble RTK-GPS

Methods

Non-destructive phenotypic measurements

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Chair of Plant Nutrition Technical University of Munich

6 Friederike Gnädinger

Methods

Non-destructive phenotypic measurements

Holland Scientific CropCircle ACS 470 (Cc) Ntech GreenSeeker RT100 TUM ALS N-Sensor Passive Sensor

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Chair of Plant Nutrition Technical University of Munich

7 Friederike Gnädinger

Methods

Holland Scientific CropCircle ACS 470 (Cc) Ntech GreenSeeker RT100 TUM ALS N-Sensor Active Sensors Light-emitting diode

656 and 774nm 670, 730 and 760nm

Xenon flashlight

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Chair of Plant Nutrition Technical University of Munich

8 Friederike Gnädinger

Methods

Calculation:

12° H=1m A=0.318 m² H=4m 12° A≤ 2.27 m²

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Chair of Plant Nutrition Technical University of Munich

9 Friederike Gnädinger

50 kg N/ha 150 kg N/ha 250 kg N/ha flowering Kernel dough stage grain maturity flowering Kernel dough stage grain maturity flowering Kernel dough stage grain maturity Biomass accumulation [t/ha] 5 10 15 20 25 30

Results

Biomass accumulation at three fertilizer levels

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Chair of Plant Nutrition Technical University of Munich

10 Friederike Gnädinger

Results

Plant biomass nitrogen uptake at three fertilizer levels

50 kg N/ha 150 kg N/ha 250 kg N/ha Total Biomass N uptake [t/ha] 0,05 0,10 0,15 0,20 0,25 0,30 0,35 flowering Kernel dough stage grain maturity flowering Kernel dough stage grain maturity flowering Kernel dough stage grain maturity

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Chair of Plant Nutrition Technical University of Munich

11 Friederike Gnädinger

Results

Temporal illustration of different parameters at 250 kg N/ha fertilizer application

Biomass accumulation [t/ha] Total Pant Nitrogen uptake [t/ha] 10 20 30 0,1 0,2 0,3 flowering flowering Kernel dough stage Kernel dough stage grain maturity grain maturity

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Chair of Plant Nutrition Technical University of Munich

12 Friederike Gnädinger

Results

Correlation between reflectance index and total biomass at flowering at 150kg N/ha and 250 kg N/ha fertilizer application

HPS 730/760

4 6 8 4 6 8 10

Total biomass [t/ha]

12 2 2 10

Better detection for 250 kg N/ha

4 6 8 10 12 2

HPS 730/760

4 6 8 2 10

Total biomass [t/ha]

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Chair of Plant Nutrition Technical University of Munich

13 Friederike Gnädinger

Results

Correlation between reflectance index and leaf biomass and total biomass at flowering at 250 kg N/ha fertilizer application

2.0 3.0 4.0 1.2 1.3 1.4 1.5 1.6

NDVI Leaf biomass [t/ha]

5.0 1.0 1.1 1.7

HPS 730/760

4 6 8 4 6 8 10

Total biomass [t/ha]

12 2 2 10

Hardly no difference between total biomass and leaf biomass correlation

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Chair of Plant Nutrition Technical University of Munich

14 Friederike Gnädinger

Leaf biomass [t/ha]

2.0 3.0 4.0 1.2 1.3 1.4 1.5 1.6

NDVI

1.0 5.0 1.1 1.7

Better detection of fully expanded leaves at kernel dough stage

Results

Correlation between reflectance index and leaf biomass at flowering and kernel dough stage with 250 kg N/ha fertilizer application

Flowering stage

R780r740

Leaf biomass [t/ha]

Kernel dough stage

2 4 6 8 10 2.0 3.0 4.0 1.0 5.0 6.0

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Chair of Plant Nutrition Technical University of Munich

15 Friederike Gnädinger

Plants better distinguished
Fully expanded leaves

Better nitrogen uptake detection

Results

Correlation between reflectance index and leaf N uptake at flowering and kernel dough stage with 250 kg N/ha fertilizer application

Leaf N uptake [t/ha]

3.0 4.0 5.0 1.15 1.20 1.25 1.30 1.35

R780r740

2.0 6.0

Flowering stage

1.15 1.20 1.25 1.30 1.05

R780r740

1.10 1.00 4.0 6.0 8.0

Leaf N uptake [t/ha]

2.0 10.0

Kernel dough stage

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Chair of Plant Nutrition Technical University of Munich

16 Friederike Gnädinger

Conclusions

Differences in biomass and nitrogen uptake of different cultivars were observed
Passive sensing outperformed active sensing
Optimized Indices were growth stage specific
Overall, spectral information was more closely related to leaf biomass and leaf nitrogen uptake at

kernel dough stage than at flowering

Discrimination of biomass and nitrogen uptake of individual cultivars seems to be possible

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Chair of Plant Nutrition Technical University of Munich

17 Friederike Gnädinger

Thank you for your attention!

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Chair of Plant Nutrition Technical University of Munich

18 Friederike Gnädinger Response: TM.Blatt..kg.ha. Df Sum Sq Mean Sq F value Pr(>F) Sorte 7 15057961 2151137 8.3685 6.659e-05 *** Wdh 3 283872 94624 0.3681 0.7768 Residuals 21 5398074 257051 $groups trt means M 1 Cannavaro 4076.085 a 2 Barros 3328.119 ab 3 Vitallo 3327.433 ab 4 KWS 9361 2954.057 abc 5 P8105 2538.058 bc 6 Saludo 2238.682 bc 7 Severus 2230.835 bc 8 Lapriora 1877.359 c $groups trt means M 1 Cannavaro 1.278743 a 2 Vitallo 1.220152 ab 3 P8105 1.203623 ab 4 Lapriora 1.181541 b 5 Barros 1.170379 b 6 Severus 1.168927 b 7 KWS 9361 1.163578 b 8 Saludo 1.145274 b Response: R780.r740 Df Sum Sq Mean Sq F value Pr(>F) Sorte 7 0.050202 0.0071717 4.6275 0.00289 ** Wdh 3 0.005575 0.0018583 1.1991 0.33440 Residuals 21 0.032546 0.0015498

Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

2 4 6 10 8

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Chair of Plant Nutrition Technical University of Munich

19 Friederike Gnädinger

1.15 1.20 1.25 1.30 1.05

R780r740

1.10 1.00 4.0 6.0 8.0

Leaf N uptake [t/ha]

2.0 10.0

Kernel dough stage

Response: Nup.Blatt Df Sum Sq Mean Sq F value Pr(>F) Sorte 7 6428.6 918.38 17.0194 2.411e-07 *** Wdh 3 225.5 75.16 1.3929 0.2726 Residuals 21 1133.2 53.96 $groups trt means M 1 Cannavaro 69.23851 a 2 Vitallo 49.86995 b 3 Barros 47.08224 bc 4 KWS 9361 32.86096 bcd 5 P8105 31.58246 cd 6 Severus 29.45820 d 7 Lapriora 26.86340 d 8 Saludo 25.64669 d $groups trt means M 1 Cannavaro 1.278743 a 2 Vitallo 1.220152 ab 3 P8105 1.203623 ab 4 Lapriora 1.181541 b 5 Barros 1.170379 b 6 Severus 1.168927 b 7 KWS 9361 1.163578 b 8 Saludo 1.145274 b Response: R780.r740 Df Sum Sq Mean Sq F value Pr(>F) Sorte 7 0.050202 0.0071717 4.6275 0.00289 ** Wdh 3 0.005575 0.0018583 1.1991 0.33440 Residuals 21 0.032546 0.0015498

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Chair of Plant Nutrition Technical University of Munich

20 Friederike Gnädinger

Results

Relationship between reflectance index and leaf biomass at flowering with 250 kg N/ha fertilizer application

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Chair of Plant Nutrition Technical University of Munich

21 Friederike Gnädinger

Backup information

Cultivars Usage Maturity Silo- /Körnerreifezahl Cannavaro Biogas Very late S:310 Lapriora Silage Early K:190 Saludo Silage, grain Early S:210, K:210 Severus Silage Early S: ca. 190, K: ca. 190 Vitallo Silage Late S: 270

Tabelle 1: Nutzungszwecke und Reifegruppen der untersuchten Maissorten

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Chair of Plant Nutrition Technical University of Munich

22 Friederike Gnädinger

Results

Correlation between reflection index of total plant biomass at flowering and kernel dough stage with 250 kg N/ha fertilizer application

HPS 730/760

4 6 8

4 6 8 10 Total biomass [t/ha] Index ist eigentlich der R760r730

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Chair of Plant Nutrition Technical University of Munich

23 Friederike Gnädinger

Backup information

flowering kernel dough stage grain maturity flowering kernel dough stage grain maturity flowering kernel dough stage grain maturity Lapriora Vitallo Lapriora Lapriora Cannavaro KWS 9361 Saludo Saludo Saludo Saludo Lapriora P8105 Saludo Vitallo Saludo Lapriora Lapriora Lapriora Severus Cannavaro Barros P8105 KWS 9361 Vitallo KWS 9361 KWS 9361 KWS 9361 Cannavaro Saludo Severus Severus Saludo P8105 P8105 P8105 Severus P8105 Barros Vitallo KWS 9361 Barros Lapriora Barros Vitallo P8105 KWS 9361 Severus Saludo Cannavaro P8105 Severus Severus Cannavaro Vitallo Vitallo P8105 KWS 9361 Vitallo Severus Barros Vitallo Severus Barros Barros KWS 9361 Cannavaro Barros Lapriora Cannavaro Cannavaro Barros Cannavaro 50 150 250

biomass

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Chair of Plant Nutrition Technical University of Munich

24 Friederike Gnädinger

Backup information

Nitrogen Uptake

50 150 250 flowering kernel dough stage grain maturity flowering kernel dough stage grain maturity flowering kernel dough stage grain maturity Vitallo Vitallo Vitallo Saludo Cannavaro KWS 9361 KWS 9361 Saludo Saludo Lapriora Cannavaro Barros Lapriora Vitallo Saludo Saludo KWS 9361 KWS 9361 Cannavaro Barros P8105 P8105 KWS 9361 Vitallo Vitallo P8105 P8105 Saludo KWS 9361 Cannavaro KWS 9361 Barros P8105 P8105 Lapriora Vitallo Severus P8105 Severus Vitallo P8105 Barros Severus Vitallo Barros Barros Severus Lapriora Severus Saludo Severus Lapriora Severus Lapriora KWS 9361 Lapriora KWS 9361 Barros Severus Cannavaro Barros Barros Severus P8105 Saludo Saludo Cannavaro Lapriora Lapriora Cannavaro Cannavaro Cannavaro

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Chair of Plant Nutrition Technical University of Munich

25 Friederike Gnädinger

Backup information

Nitrogen Nutrition Index

50 kg N/ha 150 kg N/ha 250 kg N/ha flowering kernel dough stage grain maturity flowering kernel dough stage grain maturity flowering kernel dough stage grain maturity Cannavaro Saludo Severus KWS 9361 P8105 P8105 KWS 9361 Saludo Severus Vitallo KWS 9361 P8105 P8105 KWS 9361 Saludo Saludo P8105 Saludo Barros Vitallo Vitallo Vitallo Severus Vitallo P8105 KWS 9361 Barros KWS 9361 Severus Barros Barros Saludo KWS 9361 Barros Severus P8105 Saludo P8105 Cannavaro Cannavaro Barros Severus Lapriora Lapriora KWS 9361 P8105 Barros KWS 9361 Saludo Cannavaro Barros Vitallo Barros Lapriora Lapriora Cannavaro Lapriora Severus Vitallo Lapriora Severus Vitallo Vitallo Severus Lapriora Saludo Lapriora Lapriora Cannavaro Cannavaro Cannavaro Cannavaro

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Chair of Plant Nutrition Technical University of Munich

Flowering Kernel dough stage

Sensor LDW BDW LNU BNU NNI LDW BDW LNU BNU NNI Cc730_670 0.13 0.09 0.03 0.03 0.00 0.06 0.11 0.04 0.10 0.01 Cc760_670 0.04 0.02 0.00 0.00 0.04 0.12 0.22 0.39 0.33 0.36 Cc760_730 0.15 0.13 0.09 0.09 0.03 0.00 0.02 0.23 0.10 0.45 HPS NDVI 0.29 0.31 0.21 0.17 0.05 0.51 0.04 0.51 0.20 0.52 HPS 730_670 0.30 0.27 0.28 0.22 0.07 0.55 0.00 0.37 0.06 0.32 HPS 760_670 0.25 0.32 0.17 0.13 0.01 0.53 0.03 0.53 0.18 0.52 HPS 760_730 0.18 0.37 0.44 0.41 0.48 0.21 0.11 0.66 0.40 0.53 HPS 780_740 0.16 0.18 0.45 0.41 0.50 0.08 0.08 0.62 0.37 0.53 HPS 742_764 0.18 0.19 0.46 0.42 0.50 0.10 0.11 0.67 0.41 0.63 HPS REIP 0.13 0.14 0.42 0.39 0.09 0.11 0.10 0.63 0.39 0.60

Correlations between non-destructively and destructively assessed parameters leaf and biomass dry weight (LDW and BDW), leaf and biomass nitrogen uptake at flowering and kernel dough stage (LNU and BNU)