16 most essential nutrients of soil. These nutrients can be classified as: 1. The primary macronutrients: nitrogen (N), phosphorus (P), potassium (K) 2. The secondary macronutrients: calcium (Ca), sulfur (S), magnesium (Mg) 3. The micronutrients: boron (B), chlorine (Cl), manganese (Mn), iron (Fe), zinc (Zn), copper (Cu),molybdenum (Mo), nickel (Ni) These nutrients are supplied by the soil and by the addition of fertilizers such as manure, compost, and fertilizer salts. A soil testing program can be divided into four main components: Soil sample preparations Measurement Reference analysis Calibration Validation Predictions https://www.youtube.com/watch?v=Lm1UKqqUhQ8&t=42s

1. Spectroscopic sensing of soil nutrients
Presented By:
Bhawana Singh
Senior research fellow
V1 Agrionics

2. Content
• Soil nutrients
• Sensing techniques
• Spectroscopy basics
• Spectroscopy Types
• Detailed methodology
• Reference
2

3. 16 most essential nutrients of soil. These
nutrients can be classified as:
1. The primary macronutrients: nitrogen (N),
phosphorus (P), potassium (K)
2. The secondary macronutrients: calcium (Ca),
sulfur (S), magnesium (Mg)
3. The micronutrients: boron (B), chlorine (Cl),
manganese (Mn), iron (Fe), zinc (Zn), copper
(Cu),molybdenum (Mo), nickel (Ni)
These nutrients are supplied by the soil and by
the addition of fertilizers such as manure,
compost, and fertilizer salts.
What we want to sense?
3
Ref.
Soil Sampling and analysis
Soil Nutrients

4. 4
Soil Nutrients
nutrient Symbol Peak wavelength (nm)
Nitrogen N -
Potassium K 766.491
Calcium Ca 616.217
Magnesium Mg 518.360
Phosphorus P -
Sulfur S -
Sodium Na 568.820
Iron Fe 259.940
Boron B 249.772
Manganese Mn 257.610
Zinc Zn 213.857
Copper Cu 324.754
Between(200-800)
Ref.
Determination of available nutrients in soil using the Agilent 4200 MP-AES

5. How it can be sense?
Electrochemical sensing that uses ion-
selective electrodes which generate a
voltage or current output in response
to the activity of selected ions.(i.e. ion
selective field effect transistor )
Optical sensing that uses reflectance
spectroscopy to detect the level of
energy absorbed/reflected by soil
particles and nutrient ions.
Electro chemical sensing Spectroscopy
5
Ref.
Testing/Monitoring of Soil Chemical Level Using Wireless Sensor Network Technology
Electrochemical sensors for soil nutrient detection: opportunity and challenge
By Sensing techniques for soil nutrients

6. Ref.
Soil Analysis Using Visible and Near Infrared Spectroscopy
https://www.youtube.com/watch?v=dkARLSQWHH8
6
Why Spectroscopy over Electrochemical ??
1.This is non-destructive measurement.
2. no need to take large no of soil sample.
3. Less time consuming
4. Very small amount of sample is required.
5. Cost effective in the long run.

7. https://www.youtube.com/watch?v=dkARLSQWHH8 7
What is Spectroscopy???
Spectroscopy :it is the study of interaction of
electromagnetic radiation with matter
Spectrometer: it is a tool which is use to look
indirectly at molecule.
Spectra: A plot of the color profile
(wavelength)

8. Interaction methodologies
There are two ways in which interaction between matter and radiation can take place
8https://www.youtube.com/watch?v=dkARLSQWHH8

9. Molecular spectra
9https://www.youtube.com/watch?v=vt3WO2rf9Qs
Three types of molecular spectra are present:
1. Rotational spectra
2. Vibration rotational spectra
3. Electronic band spectra

10. http://slideplayer.com/slide/9200362/
10
Electromagnetic wave
•Transport energy
•Electric and magnetic field oscillate:
that’s the “wave”.
•Moves at speed of light.
•Wavelength, frequency, energy all
related
c= speed of light(3*10^(8) m/s)
E= energy
λ = wavelength
𝛎= frequency
H=planck’s constant(4*10^(-15) eV sec)

11. Type of Spectroscopy
Spectroscopic methods are classified according to the resign of the electromagnetic
spectrum used or produced such as
11
Ref. Optical Sensing Methods for Assessment of Soil Macronutrients and other Properties for Application in Precision
Agriculture:: A review
UV region = 200-400nm
Visible range = 400-780nm
NIR = 780-2500nm

12. Method of sensing by Spectroscopy
 A soil testing program can be
divided into four main
components:
1. Soil sample preparations
2. Measurement
3. Reference analysis
4. Calibration
5. Validation
6. Predictions
12
Ref. Soil Analysis Using Visible and Near Infrared Spectroscopy

13. Detailed Methodology
13
Ref.
Soil Analysis Using Visible and Near Infrared Spectroscopy
Diagnostic Nutrient Testing
1. Soil sample preparations
• Use air or oven dried soil
• Grind soil to < 2 mm particle size
2.Measurement
•Sample preparation and handling:
1.Make sure that the sample is thoroughly mixed in the sample
container .
2. Soils are heterogeneous
3. Pack the containers the same way for all samples
4. If the same container is to be used for several samples it is
important to clean it
between samples.
•White and dark reference:
1. Depending on instrument, this may be done automatically,
however for some instruments it needs to be done manually.

14. Detailed Methodology
14
3. Pre treatment of spectra
•Average spectra of repeated vis-NIR scans on the same soil sample to
avoid using false replicates.
•Transform the measured reflectance to apparent absorption through
log(1/reflectance) to enhance the linearity.
•To enhance the more chemically related peaks and reduce effects
such as baseline shifts and overall curvature, it is often recommended
to employ some additional pre-processing transformation of the
spectra
4. Reference soil analyses
• The calibration statistics can never be better than the quality of the chemical
reference analyses. That is, errors related to the traditional chemical analysis to
which the spectra are correlated will be included in the calibration model.
• Make a statistical analysis of the soil data before using it for calibration.

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Detailed Methodology
5. Calibration and validation
There are many different algorithms that can be used to calibrate soil vis–NIR
spectra to predict soil properties. They include
multiple linear regression (MLR),
principal component regression (PCR) and
Partial least squares regression (PLS)
6. Model assessment
There are several numerical measurements describing the performance of the
predictions. We recommend the use of the root mean squared error (RMSE), bias
(or mean error) and standard deviation of the error distribution (SDE) to account
for accuracy and imprecision of the predictions, and the ratio of performance to
deviation (RPD) for assessments across units:

16. Selection of Instrument depends on
16https://www.asdi.com/products-and-services/fieldspec-spectroradiometers/handheld-2-portable-spectroradiometer
What instrument to choose is largely
dependent on the application and
basically there is a trade-off between
price and performance.
•Resolution and noise
•Spectral range
•Flexibility

17. 17
References
1. “Soil Analysis Using Visible and Near Infrared Spectroscopy”, Johanna Wetterlind, Bo Stenberg Swedish, University of
Agricultural Sciences.
2. “Testing/Monitoring of Soil Chemical Level Using Wireless Sensor Network Technology”, Purvi Mishra, Sudha Mapara
Arya Institue of Engineering and Technology, Jaipur.
3. “Optical Sensing Methods for Assessment of Soil Macronutrients and other Properties for Application in Precision
Agriculture A review” , Shakuntala Laskar, Department of Electrical and Electronics Engineering, School of Technology
Assam Don Bosco University, Guwahati.
4. “Soil Sampling and analysis”, J.L. Walworth.
5. “Nutrients Detection in the Soil: Review Paper”, Ashwini A. Chitragar, Sneha M. Vasi, Sujata Naduvinamani, Akshata
J. Katigar and Taradevi I. Hulasogi,Department of Instrumentation Technology, B V Bhoomaraddi College of
Engineering and Technology, Hubli, INDIA.
6. “Near infrared Spectroscopy technology for soil nutrients detection bsaed on LS-SVM”, Yandan Qioa,central for
popularization of agriculture machinary technlogy for shanxi provinece.
7. “Electrochemical sensors for soil nutrient detection: opportunity and challenge”, ianhan Lin, Maohua Wang , Miao
Zhang, Yane Zhang, Li ChenKey Laboratory of Modern Precision Agriculture System Integration, Ministry of Education,
Beijing, China.
8. “Diagnostic Nutrient Testing”, R.S. Mylavarapu.
9. “Determination of available nutrients in soil using the Agilent 4200 MP-AES”, Dharmendra Vummiti Agilent
Technologies, India

18. Thank you
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