Advances in crop modeling-Panchaal B

Presented by
Panchaal Bhattacharjee
PhD. (Hort.) 1st sem.
Fruit Science
Department of Horticulture
BACA, AAU, Anand

Crop modeling:
Modeling as a preliminary definition one could think of a model
as an attempt to describe a certain process or system through the
use of a simplified representation, preferably a quantitative
expression, that focuses on a relatively few key variables that
control the process or system.
The development of modern agricultural-horticultural crop
models was closely associated with the advent of computer
programming and faster computers during the last decades of the
20th century that facilitated the many calculations needed in
complex models.

Modeling of fruit crops-
In the present days we would like to emphasize carbon-based crop
productivity models with a focus on fruit tree models.
The purpose and orientation of the model may differ according to
the researcher’s interest – a variety of problems, Including –
 Water use efficiency
 Predicting phenology or fruit ripening
 Predicting climate effects, evaluation stress responses and/or
pest management
(Boote et al., 2006)

4
Fruit tree Growth Modeling: a multidisciplinary subject
Bio-climatology and Soil Sciences
Botany
Plant Architecture,Phenology
Agronomy:
Ecophysiology
Applied Mathematics
Stochastic Processes, Dynamical
Systems Optimization
Computer sciences
Simulation visualizationPlant Growth Simulation

Prerequisites for construction of a Model
• Conceptual understanding of the physiological processes involved.
• Imaginative, quantitative thinking.
• An extensive agricultural/biological database.
6
• A particular limitation for fruit tree crop models is the limited and incomplete database of good
quantitative data for modeling.
The best data and knowledge bases generally are for
• (1) Phenology
• (2) Leaf Photosynthesis (Light And Temperature
Responses)
• (3) Shoot Growth And Leaf Area Development
• (4) Fruit Growth And Respiration.
Some of the major gaps are
•(1) Root Growth Patterns, Respiration, Root Turnover Rates
•(2) Respiration Rates In General – Available data is almost all
short term measurements; responses to
temperature done in short term, not long-term.
• (3) The Seasonal Demands For Carbon Of Different Organs
• (4) Detailed Understanding Of Fruit Abscission Processes

8
A model combining two approaches
Biomass
water Nutriments
CO2
Organogenesis + empirical Geometry = Plant
Architecture.
Plant development coming from meristem trajectory
(organogenesis)
Biomass acquisition (Photosynthesis, root nutriment
uptake) + biomass partitioning (organ expansion)
Compartment level
Morphological models
=> simulation of 3D development
Process-based models
=>Yield prediction as a function of environmental
conditions
Functional-structural models

9
Flowchart for plant growth and plant development
seed
photosynthesis
H2O
Pool of biomass
leaves
roots
Organogenesis + organs
expansion
transpiration
CHO
fruits
branches
GreenLab Plant

Architectural modeling
• Architectural analysis was introduced by Hallé and co-workers (Hallé and Oldeman 1970; Hallé
et al. 1978).
• Based on the concept of “axis differentiation” in five main morphological criteria all related to
the meristem activity they have formed “23 architectural models” and are dedicated to famous
botanists.
• Growth direction : (Plagiotropic or Orthotropic)
• Growth rhythm : (Continuous or Rhythmic)
• Branching mode : (Monopodial or Sympodial)
• Sexual differentiation
of meristems : (Terminal or Auxillary)
• Polymorphism of axes : Short(Brachyblasts),medium (Mesoblasts) and long shoots (auxiblasts)

• It consists only one meristem and it is not branched.
• The meristem will converts into inflorescence and plant eventually dies
• Ex: Banana
1.Holttum’s model

Trunk is single, monopoidal and orthotropic in nature.
• Growth is indeterminate and auxiliary inflorescence is seen.
• Ex: Papaya, Datepalm
2.Corner’s model

• Trunk is monopoidal, orthotropic in nature.
• Lateral flowering is seen.
• Ex: Apple.
3.Rauh model

• Sympodial and plagiotropic in nature.
• Ex: Annona squamosa
4.Troll’s model

Green- Lab Model
This model requires two input files
• The mean leaf area of the shoot, its distribution along the main axis and
mean leaf size (mean shoot file).
• The other file describing plot layout and the number of shoots per plant
(plot file).

Green lab method
Figure 2: Modelling 3D Canopy Structure in Grapevine, Louarn et al. 2008

Figure 3: Comparison of photographs taken in a real vineyard (veraison, stage 35, Coombe) with the
corresponding simulations made for grape training systems.
Louarn et al. 2008

L-Modeling
• This plant model is expressed in terms of modules that represent plant
organs.
• Organs are represented as one or more elementary sources or sinks of
carbohydrates.
• The whole plant is modelled as a branching network of these sources and
sinks, connected by conductive elements.
20

• In this analogy, accounts the amount of carbon corresponds to an electric
charge.
• Carbon concentration to electric potential.
• Carbon fluxes to current flow.
Daily photosynthesis of individual leaves is represented as an
accumulation of charge that is calculated from the distribution of light in
canopy.
21

22
A formal grammar for plant development (L-system)
Alphabet = {metamers, buds}
(according to their physiological ages = morphogenetic characteristics)
Production Rules : at each growth cycle, each bud in the structure gives a
new architectural growth unit.
Factorization of the growth grammar factorization of the plant into
« substructures »
Computation time proportional to plant
chronological age and not to the number of
organs !

23
Inter-tree competition at stand level
Isolated tree
Central treeTree on the edge
Trees in competition for light
Method of intersections of projected areas

Figure . This figure demonstrates the potential of the model to simulate crop load effects on fruit and tree
growth, and carbon partitioning.
• In the first pair, fruit set is altered such
that the crop load in one tree is twice that
of the other.
• In response to this decrease in initial
fruit set, the model produced the
following results.
• by giving Lower variance in fruit size
within a tree, and greater partitioning of
carbon to vegetative growth.
Example:
26

• The tree on the left was simulated under
conditions of full irrigation whereas the tree
on the right experienced mild water stress
during growth.
• In this simulation leaf initiation and
stem elongation rate were both set to be
more sensitive to mild water stress.
Figure . This figure demonstrates the potential of the model to simulate the effects of irrigation frequency
or mild water stress on tree growth.
27

Effects of elevated CO2 on grapevine (Vitis vinifera L.): Physiological and
yield attributes
J. MOUTINHO-PEREIRA1, B. GONÇALVES1, E. BACELAR1, J. BOAVENTURA CUNHA1, J. COUTINHO2 and C.
M. CORREIA1
1) CITAB – Centre for the Research and Technology of Agro-Environment and Biological Sciences, University of Trás-os-Montese Alto Douro, Vila Real,
Portugal
2) Centre of Chemistry, University of Trás-os-Montes e Alto Douro, Vila Real, Portugal
Vitis 48 (4), 159–165 (2009)
Objective- The main purpose of this study was to
investigate the pattern of acclimation of
grapevine physiology and yield responses to
elevated [CO2] in Open-Top Chamber
(OTC).
To predict the grapevine performance
in a future scenario of climate change.
Pereira et al., 2009

A gs A/gs Ψmd
OTC-C 13.65 b 406.9 b 34.14 b -1.48 b
OTC-E 22.46 a 330.0 a 71.55 a -1.33 a
A= Net photosynthesis ( μmol m-2 s-1)
gs= Stomatal conductance (gs, mmol m-2 s-1)
A/gs=Intrinsic water use efficiency (A/gs, μmol CO2 mol-1 H2O)
Ψmd= Midday leaf water potential (MPa)
Table 2- Grapevines grown in ambient CO2 (OTC-C), elevated CO2 (OTC-E). Means (n=10)
followed by the same letter are not significantly different at P < 0.05 (Duncan’s test).
Grape (Vitis vinifera L.) cv. 'Touriga Franca' is taken for the experiment, which is conducted under ambient
(OTC-C, 365 ± 10 ppm) and elevated carbon dioxide [CO2] (OTC-E, 500 ± 16 ppm) under Open-top
chambers.

Table 3- Stomatal density (stomata mm-2) and leaf tissue thickness (μm) of grapevines grown in ambient CO2
(OTC-C), elevated CO2 (OTC-E).
Means (n=10) followed by the same letter are not significantly different at P < 0.05 (Duncan’s test).
Stomatal
density
Total
lamina
Palisade
parenchyma
Spongy
parenchyma
OTC-C 168.1 b 150.2 b 46.7 b 65.5 b
OTC-E 130.0 a 171.2 a 56.4 a 78.0 a
Yield
(kg·vine-1)
Cluster
(no’s·vine-1)
Cluster weight
(g)
Shoot
(no’s·vine-1)
OTC-C 2.80 ± 0.26 9.7 ± 1.1 303.7 ± 22.1 18.8 ± 1.7
OTC-E 4.20 ± 0.75 12.1 ± 2.2 367.3 ± 54.2 26.4 ± 2.6
P-value 0.062 0.295 0.047 0.025
Table 4- Yield, cluster number and weight, shoot number, of grapevines grown at
elevated CO2 (OTC-E) and ambient CO2 (OTC-C)

Existing models or modeling frameworks for fruit crops-
Hi-SAFE and Yield-SAFE
• The Hi-SAFE model was designed in response to the need for a
process-based model that could simulate tree-crop interaction and
management options in a temperate region (Dupraz et al., 2005).
 The typical agroforestry systems to be simulated by the model are walnut
(Juglans spp.), wild cherry (Prunus avium)or Mediterranean oaks (Quercus
spp.) with winter and summer annual crops, grass and alfalfa.
In Apple orchard modeling-

Conclusion
• Crop modeling in fruits provides knowledge about behavior of fruit
trees to various architectural modifications such as effect of root stock,
training, pruning, thinning and plant growth regulators along with
interaction related with environment.
• These modification helps the fruit growers to optimize their yield,
productivity and quality of produce suitable for export.
32

Advances in crop modeling-Panchaal B

More Related Content

What's hot (20)

Similar to Advances in crop modeling-Panchaal B (20)

More from Panchaal Bhattacharjee (12)

Recently uploaded (20)

Advances in crop modeling-Panchaal B