Evaluation of Biostimulants for Plant Stress Tolerance

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AgriThority ® Biostimulant Evaluation Challenges

Evaluation of Biostimulants for Plant Stress Tolerance Overcoming Challenges for an Objective Assessment in Field Trials Submitted by Ignacio Colonna, Global Director, Science and Technology

BIOSTIMULANT DEVELOPMENT

EARLY DEVELOPMENT EFFICACY TRIALS

Effective biostimulant development requires: • Careful design of early development Example: Rhizotron study designed to support

Choose the right experiment for product type and stage. Investing in early development trials increases effectiveness of field experiments at later stages. • Rate calibration • Compatibility • Synergies • Early crop response

experiments.

biostimulant root growth claims in registration dossier

• Choice of adequate environmental range

and location number in late development testing.

Control

• Understanding of product efficacy across

Example: Detecting and quantifying early negative effect of mixing Biostimulant with fungicide

Biostimulant

environments, quantify variability in response.

Biostimulant

• Relying on credible, objective assessments

Corn

Fungicide

of in-season crop responses.

• Develop a robust, data-based product

Biostimulant + Fungicide

positioning strategy

Biostimulant

Biostimulant @ optimal rate

Soybean

Biostimulant+ Fungicide

Fungicide Biostimulant + Fungicide

Use of WinRhizo to quantify root growth daily

LATE DEVELOPMENT FIELD TRIALS Expand generated data with counter season experiments, ensure correlation between target and testing environments. • Target the right environment for project. • Design experiments to fit product development AND registration needs. • Maximize information collected from a limited number of sites. • Quantify crop response objectively.

Supplement visual vigor scores with objective crop health indicators. Ground-based NDVI sensors

NDVI = (NIR-VIS)/(NzIR+VIS). –1 to 1 indicator of crop canopy size and activity

Extend data generated via counter season experiments: Correlation between target and testing environments

“ Corn-centered” testing

“Stress-centered” testing

Target area “ Stresscentered” testing

“ Corncentered” testing

10-year average Drought Palmer Index

Weekly NDVI tracking from high-resolution satellite imagery Drought Palmer Index

R2 R5

Coefficient of variation (CV)

V5

Feb 5

Source: AgriThority ® database. 327 trials from 52 projects across NA and LATAM.

Jan 2

Minimize experimental error without restricting environmental range Coefficient of variation (CV) across an environmental range

Dec 10

Corn Acres

Trt Control Distance along trial (m x 10)

Field-scale trials assessment through digital tools Yield response breakout by sub-field environments

* Treatment differences are statistically significant at a=0.15. Analysis based on a mixed spatial model

Coefficient of variation (CV) = Experimental error Std. dev Trial mean

Testing in stressful environments: Abiotic stress in rainfed and managed stress sites

Managed stress environments

Select rainfed environments Subtropical region/higher disease pressure

Digital screening does not eliminate value of true replicates

Yield map

Field Elevation

High drought-heat stress

Moderate drought stress

High yield potential

Moderate drought stress / cool temperature

AGT-21458-C 2021


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