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© Malvern Panalytical 2017 Contamination to soil and its implications to plant health: using NIR to check for health of plants in our garden city NIR LabSpec/FieldSpec Alice Ng (Application Specialist)

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Page 1: Contamination to soil and its implications to plant health ... · Soil Analytical quality control by traditional and spectroscopic techniques: Constructing the future of a hybrid

© Malvern Panalytical 2017

Contamination to soil and its implications to plant health: using NIR to check for health of plants in our garden city –NIR LabSpec/FieldSpec

Alice Ng (Application Specialist)

Page 2: Contamination to soil and its implications to plant health ... · Soil Analytical quality control by traditional and spectroscopic techniques: Constructing the future of a hybrid

© Malvern Panalytical 2017

NIR Spectrum in Vegetation

Red edge refers to the region of rapid

change in reflectance of vegetation in the

near infrared range of the

electromagnetic spectrum. Chlorophyll

contained in vegetation absorbs most of

the light in the visible part of the spectrum

but becomes almost transparent at

wavelengths greater than 700 nm.

Page 3: Contamination to soil and its implications to plant health ... · Soil Analytical quality control by traditional and spectroscopic techniques: Constructing the future of a hybrid

© Malvern Panalytical 2017

Agricultural Applications

Page 4: Contamination to soil and its implications to plant health ... · Soil Analytical quality control by traditional and spectroscopic techniques: Constructing the future of a hybrid

© Malvern Panalytical 2017

Plant Species Mapping

DiPietro, et al, 2002

Page 5: Contamination to soil and its implications to plant health ... · Soil Analytical quality control by traditional and spectroscopic techniques: Constructing the future of a hybrid

© Malvern Panalytical 2017

Measurement of soil attributes

• Brazil study published in Geoderma 337 (2019) 111-121

• Multiple laboratories

• Used 4 ASD systems

• Analysis using the average lab result and 4 individual ASD

spectroradiometers

• Data compiled here is the average of the 4 ASD systems

Soil Analytical quality control by traditional and spectroscopic techniques: Constructing the future of a hybrid

laboratory for low environmental impact

Jose Alexandre M. Dematte, Andre Carnieletto Dotto, Luis Gustavo Bedin, Veridiana Maria Sayao, Arnaldo Barros e Sousza

Geoderma 337 (2019) 111–121

R2 RMSECV R2 RMSEP

Al 0.92 3.35 0.85 5.39

Ca 0.84 8.33 0.70 11.14

K 0.81 0.97 0.66 1.59

Mg 0.80 4.77 0.73 7.91

P 0.48 24.41 0.31 30.23

AS 0.84 8.04 0.63 13.17

BS 0.82 8.26 0.69 11.65

CEC 0.95 9.93 0.87 17.66

H+Al 0.91 10.20 0.81 14.89

SB 0.82 11.63 0.68 21.31

OM 0.90 3.30 0.79 4.41

pH 0.76 0.27 0.61 0.39

Sand 0.90 6.48 0.87 7.67

Clay 0.91 5.08 0.88 6.08

Silt 0.86 3.29 0.80 4.65

Calibration Validation

Root Mean Squared Error Cross Validation (RMSECV) is an internal method to

'test' your model (or calibration model) to make sure it isn't badly skewed by a

data point or if the model is over fitted, or if there are any outliers. RMSECV is

determined by the validation method chosen.

RMSEP stands for Root Mean Square Error of Prediction. SEP stands for Standard

Error of Prediction. RMSEP or SEP is the simplest and most efficient measure of

the uncertainty in NIR predictions. This value is a measure of the average

uncertainty that can be expected when predicting new samples.

Page 6: Contamination to soil and its implications to plant health ... · Soil Analytical quality control by traditional and spectroscopic techniques: Constructing the future of a hybrid

© Malvern Panalytical 2017

Measurement of Soil Organic Carbon

• Analysis of intact soil

• NIR predicted Cationic Exchange Capacity (CEC) well

• Real time

• Easy and fast

• Low cost measurement

• RSQ = 0.93, SECV = 1.6

• RSQ validation = 0.86, SEP =2.35

• RPD = 2.66

Malvern Panalytical using soil library of samples from Illinois from NRCS RaCA program

Page 7: Contamination to soil and its implications to plant health ... · Soil Analytical quality control by traditional and spectroscopic techniques: Constructing the future of a hybrid

© Malvern Panalytical 2017

Investigation of water stress and relationship with Vegetative Indices

• Nanjing University of Information Science and Technology study

• Included 5 years of data of several vegetative indices including NDVI,

RDVI, TCARI, OSAVI, LWC, REP, TVI, LWC, LWP, LAI, Chlorophyll

content and CWSI (crop water stress index)

• NDVI, RDVI best related to chlorophyll content and LAI

• REP (Red Edge) best related to chlorophyll

• Paper was successful in investigating the relationship between water

stress and Vegetative Indices

Evaluating Structural, Chlorophyll-Based and Photochemical Indices to Detect Summer Maize Responses to Continuous

Water Stress, Meng Li, Ronghao Chu, Qian Yu, Abu Reza Md. Towfiqul Islam, Shuren Chou and Shuanghe Shen

Water 2018, 10, 500; doi:10.3390/w10040500

Leaf Area Index (LAI) is the ratio of foliage area to ground area. LAI can be determined directly by taking a statistically significant sample of foliage from a plant canopy, measuring the leaf area per sample plot and dividing it by the plot land surface area.

Page 8: Contamination to soil and its implications to plant health ... · Soil Analytical quality control by traditional and spectroscopic techniques: Constructing the future of a hybrid

© Malvern Panalytical 2017

Summary

• Wide variety of applications using NIR in agriculture

• Use of traditional Remote Sensing (i.e. Identify health of different species

of plants)

• Strategies for environmental bioremediation

• Soil quality measurements

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Page 9: Contamination to soil and its implications to plant health ... · Soil Analytical quality control by traditional and spectroscopic techniques: Constructing the future of a hybrid

© Malvern Panalytical 2017

Thank You!

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