Statistical Model ii Phonological Model iii Mechanistic Model iv Deterministic Model v Stochastic Model Dynamic Model vii Static Model viii Crop Simulation Models ix Descriptive Model x Explanatory Model contact: dhota3@gmail.com

1. 1

2. i)Defination- Crop, Modeling and Stress
ii)Stress- Brief Introduction
iii)Crop Modeling
 Defination
 Need
 Applications
 Impact
 Types of Models
 Popular Models
 Limitation
iv) Cropping System
v) Remote Sensing
vi) Case Studies
vii) Conclusion

3. Crop :
 Aggregation of individual plant species grown
in a unit area for economic purpose.
Modeling :
 It is an act of mimicry or a set of equations,
which represents the behaviour of a system.
Stress:
 A phenomenon that limits crop productivity or
destroys biomass.

5. 5

6. 6
(ICAR-NIASM)

7. ABIOTIC STRESS
Any adverse factor acting on physiological processes/
biochemical activity of the plants is called as Abiotic stress.
Air pollution
Mechanical damage
Cold stress
Light stress
High temperature stress
Drought
salt stress
7

13. Research on Interaction of Plant, Soil, Weather and Management Practices.
 Prediction of Crop Growth as well as Limiting factors
On farm decision Making and Agronomic management.
Optimizing management using climatic predictions.
Precision Farming and Site Specific Experimentation.
Weather Based agro advisory services.
Yield analysis and Forecasting.
Introduction and Breeding of New Varieties.
Policy Management.

15. i Statistical Model
ii Phonological Model
iii Mechanistic Model
iv Deterministic Model
v Stochastic Model
vi Dynamic Model
vii Static Model
viii Crop Simulation Models
ix Descriptive Model
x Explanatory Model
Murthy, Hyderabad

16. 1. Statistical Model:
These models rely on Statistical techniques such as
Correlation and Regression of the appropriate plant and
environment variable.
Example of Such model is response of crop yield to
fertilizers application.

17. 2. Phenological models:
These models predict the crop development from one
crop growth stage to another. The Prediction is generally
based on accumulated Heat units.
3.Mechanistic Model:
 These models explains not only the relationship
between weather parameters and yield, but also the
mechanism of these models (explains the relationship of
influencing independent variable)

18. 4. Deterministic Model:
These models estimate the exact value of yield. It make
definite predictions for quantities without any probability,
variance or random element.
5.Stochastic Model:
 When Variation and Uncertainty reaches a high level, it
becomes advisable to develop a Stochastic Model.
For each set of Inputs ,different outputs are given along
with probabilities. It Defines status of dependent variable
at a given rate.

19. 6. Dynamic Model
Time is included as a variable. Both dependent and
independent variables are having values which remain
constant over a given period of time. After which these
variables changes due to change in independent
variable.
7. Static Model
 Time is not included as a variable. The dependent and
independent variable having values remain constant.

20. 8. Crop Simulation Model
These models predict the final yield and also provide
quantitative information on intermediates steps like daily
weight of plant parts.
It estimate agriculture production as a function of
weather and soil conditions as well as crop
management.
This model uses one or more differential equation over
time normally from planting until harvest.

21. 9. Descriptive Model
A descriptive model defines the behaviour of a system in
a simple manner. The model reflects little or none of the
mechanisms that are the causes of phenomena. But,
consists of one or more mathematical equations.
10. Explanatory Model
This consists of quantitative description of the
mechanisms and processes that cause the behaviour of
the system such as leaf area expansion, flowering, fruiting
etc. as crop growth is a consequence of these processes.

25. The term cropping system refers to the crops, crop sequences and
management techniques used on a particular agricultural field over
a period of years.
1. Mono-species orchards: Mono-species also referred as
monoculture.
 In this, fruit trees of a single species are planted in the field.
 This system is common in modern horticulture, where trees are
planted densely, using dwarf or semi-dwarf trees with modified
canopy to ensure better light interception and distribution and ease
of mechanization .

26. 2. Multi-storied cropping : Growing plants of different height in the
same field at the same time is termed as multi-storeyed cropping
Examples of some multi-storied cropping
i Coconut+ banana + pineapple
ii. Coconut+ banana
iii. Coconut+ pasture
iv. Mango+ pineapple
v. Mango+ papaya+ pineapple
vi. Coconut+ jackfruit+ coffee+ papaya+ pineapple
vii. Coconut+ papaya+ pineapple

27. 3. Intercropping:
Intercropping, as one of the multiple cropping systems,
has been practiced by farmers for many years in various
ways and most areas, and has played a very important role
in India.
Care should be taken that there should be no competition
between main crop and intercrop.

28.  Mixed Intercropping: Growing two or more crops simultaneously with
no distinct row arrangement .
 Row Intercropping: Growing two or more crops simultaneously where
one or more crops are planted in rows.
 Strip Intercropping: Growing two or more crops simultaneously in
different strip wide enough to permit independent cultivation but narrow
enough for the crops to interact agronomically.
 Relay Intercropping: Growing two or more crops simultaneously in
which second crop is planted after the first crop has reached its
reproductive stage.
Ref: Cropping System in the Tropics: SP Palaniappan & K.Sivaraman

29. Mango Based Intercropping System
Intercrop Treatment
(Kg/ha.)
Net Return
Elephant Foot Yam 80:60:80
107493
Elephant Foot Yam 40:30:40
106271
Sweet Potato 60:40:60 43480
Sweet Potato 30:20:30 42766
Cassava 75:50:75 39000
Cassava 37.5:25:37.5 38500
http://www.krishisewa.com/crop_system/369-fruit-crop-intercropping. html
(Prof. R.K. Bhoyar,Prof. Sevak A. Dhenge and Prof. V. Swami.,CoA,Tiwsa,Amravati (M.H.)
Three root tuber crops are planted in a Mango Orchard with full and
half doses of RDF.

30. Litchi Based Intercropping System
Intercrop Treatment Net Return
Sweet Potato (30:20:30 kg/ha.) 20046
Sweet Potato (60:40:60 kg/ha.) 27527
Elephant Foot Yam (40:30:40 kg/ha.) 108001
Elephant Foot Yam (80:60:80 kg/ha.) 140000
Colocassia (40:30:40 kg/ha.) 41749
Colocassia (80:60:80 kg/ha.) 47833
Turmeric (40:30:40 kg/ha.) 28750
Turmeric (80:60:80 kg/ha.) 32583
http://www.krishisewa.com/crop_system/369-fruit-crop-intercropping. html
(Prof. R.K. Bhoyar,Prof. Sevak A. Dhenge and Prof. V. Swami.,CoA,Tiwsa,Amravati (M.H.)

31. Intercropping - Fruit Crops with Other Horticultural Crops
Fruit Crop Intercrop
Guava Cauliflower, French Bean, Pea, Cucurbits
Grapes Pea, Cauliflower, Chillies, Spinach, Marigold, Gladiolus,
Jasmine.
Papaya Cauliflower , Onion , Tomato , Capsicum
Citrus Cauliflower, Onion, Tomato, Bottle Gourd, Okra
Peach Turmeric, Ginger, Cowpea
Litchi Turmeric, Ginger, Bottle Gourd
Mango Tomato, Radish , Cauliflower

33.  It is a technique used to collect information about an object or
area without actually being in contact with that object or area.
 Remote Sensing can be done through Aerial photography or by
satellite imaging.
 It may be of two types i.e. active and passive remote sensing
 “Passive" remote sensing (i.e., when the reflection of sunlight is
detected by the sensor)
 “Active" remote sensing (i.e., when a reflection by the object is
detected by the sensor).

34.  Every material on the earth absorbs and reflect the
solar energy. In addition they emit certain amount of
Internal energy.
 The absorbed, reflected and emitted energy is
detected by remote sensing instruments or sensors
which are carried by Aircraft or Satellites.
 The detection are made by the characteristics term
called “Spectral Signature” and “Images”

37. Spectral indicators of plant chlorophyll content
 Chlorophyll pigment content, in particular, is directly associated with
photosynthetic capacity and productivity (Gaussman, 1977; Curran et al., 1992).
 Reduced concentrations of chlorophyll are indicative of plant stress (Curran et
al., 1992).
 In stressed vegetation, leaf chlorophyll content decreases, thereby changing the
proportion of light-absorbing pigments, leading to a reduction in the overall
absorption of light (Murtha, 1982; Zarco-Tejada et al., 2000).
 These changes affect the spectral reflectance signatures of plants through a
reduction in green reflection and an increase in red and blue reflections,
resulting in changes in the normal spectral reflectance patterns of plants
(Murtha, 1982; Zarco-Tejada et al., 2000).
 Thus, detecting changes from the normal (unstressed) spectral reflectance
patterns is the key to interpreting plant stress.

39. Journal of Agricultural Research and Development
Vol. 2(1). pp. 001-006, March, 2013
Available online http://www.e3journals.org
ISSN: 2276-9897 © E3 Journals 2012
Crop modeling: A tool for agricultural research – A review
Patricia Oteng-Darko, S. Yeboah, S. N. T. Addy, S. Amponsah and
E. Owusu Danquah
CSIR-Crops Research Institute, P. O. Box 3785, Kumasi, Ghana
The Earth’s land resources are finite, whereas the number of people that the
land must support continues to grow rapidly. This creates a major problem for
agriculture.
Production (productivity) must be increased to meet rapidly growing
demands while natural resources must be protected.
 New agricultural research is needed to supply information to farmers, policy
makers and other decision makers on how to accomplish sustainable
agriculture over the wide variations in climate around the world.
 In this direction the use of crop models in research is being encouraged.

40. Journal of Experimental Botany,
Volume 58, Issue 4, 1 March 2007, Pages 869–880
https://doi.org/10.1093/jxb/erl231
Quantification of plant stress using remote sensing observations and
crop models: the case of nitrogen management
F. Baret, V. Houle`s and M. Guerif
INRA-CSE, Site Agroparc, F-84914 Avignon, France
Remote sensing techniques offer a unique solution for mapping stress and
monitoring its time-course.
 This article reviews the main issues to be addressed for quantifying stress
level from remote sensing observations, and to mitigate its impact on crop
production by managing cultural practices.
The case of nitrogen fertilization is used here as a paradigm.
It is used for nitrogen stress evaluation by comparison with a reference
unstressed situation.
 The combination of remote sensing observations with crop models provides
an elegant solution for stress quantification.

41. International Journal of Agriculture Science
Volume 8 , Issue 1,Januaray 2012: 174-178.
Effect of intercropping systems on growth, yield, fruit quality and leaf
nutrient status of mango under rainfed situation
S.C. SWAIN, S.C. SAHOO AND P.J. MISHRA
College of Agriculture, Orissa University of Agriculture and Technology,
Bhawanipatna, KALAHANDI,Odisha
An intercropping experiment comprised of nine treatments such as mango
ginger, turmeric, tomato, cowpea, French bean, ragi, niger, upland paddy and
control (without intercrop) was laid out in RBD with three replications to assess the
effect of various intercrops on the performance of mango in the rainfed uplands of
Odisha.
Among different intercropping systems tried, mango + guava +cowpea exhibited
better performance which has been reflected in the form of panicle production, fruit
retention, fruit weight and fruit yield of mango.
The leaf analysis result after completion of the study revealed that the N and P
content of mango leaf were found to be maximum under mango + guava + cowpea
intercropping system ;whereas the K content was estimated maximum in the
mango + guava + French bean system.

42.  Crop growth model is a very effective tool for predicting possible
impacts of climatic change on crop growth and yield.
 Proper cropping system will have the benefit of increased yield and
thus improve the economics of a grower.
 Remote sensing (RS) data has become an important tool for yield
modeling as the satellites are taking continuous images which give
an prediction of a crop situation and status for yield estimation and
for adopting suitable management practices.