Crop Modeling and Decision Support (eBook)

Preface 5
Table of Contents 7
Modeling Time of Seedling Emergence of Spring Wheat 10
1 Introduction 10
2 Materials and Methods 11
3 Results and Discussion 14
Acknowledgements 18
References 18
Complete Parameterization of Photosynthesis Models—An Example for Barley 21
1 Introduction 22
2 Model 22
3 Material and Methods 23
3.1 Experimental Design and Plant Material 23
3.2 Gas Exchange Measurements 23
3.3 Supplementary Measurements 24
3.4 Model Parameterisation 24
4 Results and Discussion 25
4.1 Parameter—Nitrogen Relationships 25
4.2 Integration of the LEAFC3-N Model into Crop Models 29
5 Conclusion 30
Acknowledgements 30
References 30
Studies on Photosynthesis Model of Mini-Cucumber Leaf in Greenhouse 33
1 Introduction 33
2 Materials and Methods 33
2.1 Materials 33
2.2 Methods 34
2.2.1 Daily Variation of Photosynthesis 34
2.2.2 Light Response of Photosynthesis 34
2.2.3 Photosynthesis and Light and Temperature Factor Between the Statistical Models 34
3 Results and Analysis 35
3.1 Daily Variation of Photosynthesis 35
3.2 Light Response of Photosynthesis 36
3.3 Model of Photosynthesis 37
3.3.1 Data Analyze 37
3.3.2 Model Validation 37
3.4 Model Analyses 38
Acknowledgements 38
References 38
Finding a Suitable CO2 Response Algorithm for Crop Growth Simulation in Germany 39
1 Introduction 39
2 Material and Methods 41
2.1 The FACE Experiment 41
2.2 The Model Framework 41
2.3 The CO2 Response Algorithms 42
2.3.1 The Mitchell Approach for CO2 Impact on Photosynthesis 42
2.3.2 The Nonhebel Approach for CO2 Impact on Photosynthesis 43
2.3.3 The Hoffmann Approach for CO2 Impact on Photosynthesis 43
2.3.4 The Allen/Yu Approach for CO2 Impact on crop Transpiration 44
2.4 Model Calibration and Algorithm Testing 44
3 Results 44
4 Discussion 47
5 Conclusions 49
Acknowledgements 49
References 49
Bringing Genetics and Genomics to Crop Simulations: Experiences with Wheat,Sorghum and Common Bean in Solving the GEM-to-P Problem 53
1 Introduction 53
2 Gene-Based Estimation of Model Parameters 54
3 Improved Physiology 57
4 Plant Systems Biology 58
5 How Well Can We Solve the GEM-to-P Problem? 59
References 60
Establishment of Dynamic Model for the Nutrient Uptake and Development about Tomato in Greenhouse 63
1 Model Establishment 63
1.1 Sub Model of NPK Uptake 63
1.2 Sub Model of Crop Growth 64
2 Model Validation 66
3 Conclusions and Discussion 66
Acknowledgements 67
References 67
CANON: A Canonical Composition for Building Plant Shoots From the Bottom Up 68
1 Introduction 68
2 Phytomer Unit and Building Plant Canopies 69
3 Translation of Phytomer Concept into OO Design 71
4 Initial Implementation Efforts of OO Design 74
5 Discussion 75
Acknowledgements 77
References 78
A Quantitative Analysis on Leaf Curvature Characteristics in Rice 80
1 Introduction 80
2 Materials and Methods 81
2.1 Experiment and Measurement 81
2.2 Deduction of Leaf Curve Equation 81
2.3 Resolution of Leaf Curve Equation 82
3 Results and Analysis 83
3.1 Sensitivity Analysis of Leaf Curve Equation 83
3.2 Simulation Analysis of Leaf Curve Equation 83
4 Discussion 85
References 85
The Response of Canopy Direction Reflectance Spectrum for the Wheat Vertical Leaf Distributing. 86
1 Introduction 86
2 Materials and Methods 87
2.1 The Training Experiment 87
2.2 Measured Traits and Methods 88
2.3 Data Analysises 88
3 Results 89
3.1 The Spectral Curve Responses for Wiped off Different Leaves Layers 89
3.2 The Analysis of Layers Spectral Reflectivity Characteristic at Different View Angles 89
3.3 The ANOVA Analysis of Spectral Reflectivity for Different Leaves Layers 91
4 Discussion 93
Acknowledgements 93
References 93
Modeling Leaf Sheath and Internode Growth Dynamics in Wheat 95
1 Introduction 95
2 Material and Methods 95
2.1 Experiment Design 95
2.2 Measurement 96
2.3 Data Use 96
2.4 Model Description 96
2.4.1 Leaf Sheath Growth Dynamic 96
2.4.2 Internode Length Dynamic 97
2.4.3 Internode Thickness Dynamic 97
3 Model Validation 98
4 Summary and Discussion 99
References 99
Modeling Fruit Morphological Formation on Muskmelon 101
1 Introduction 101
2 Materials and Methods 102
2.1 Experiment Design 102
2.2 Observation Method 102
2.3 Data Analysis and Utilization 103
3 Results and Analysis 103
3.1 Growth Dynamic of Fruit Size (Vertical Diameter and Horizontal Diameter) 103
3.2 Growth Dynamic of Fruit RGB Color 104
3.3 Growth Dynamic of Fruit Netted (Stripe Length, Stripe Diameter) 104
3.4 Test of Fruit Vertical Diameter, Horizontal Diameter, RGB Color and Netted 105
4 Discussions 106
Acknowledgements 107
References 107
Shape Modeling of Organs and Structures Generating for Crops 108
1 Introduction 108
2 Related Work 109
3 Modeling Crop Organs 109
3.1 Skeleton Description and Generation 109
3.2 Generating Geometry of Organs 110
3.2.1 Generating Geometry of Organs from Axis Skeleton 110
3.2.2 Generating Geometry of Organs from Silhouette-Axis Skeleton 110
3.2.3 Generating Geometry of Organs from Double Silhouette-Axis Skeleton 111
3.3 Details Description 112
3.3.1 Texture Mapping 112
3.3.2 Hairs Generating 112
3.4 Compound Organ 113
3.5 Examples of Organs Shape 113
4 Interactive Generating Crop Structure 113
4.1 Templates of Organ and Morphing 114
4.2 Guidance for Constructing Crop Structure 114
5 Conclusions 116
Acknowledgements 116
References 116
Modeling Shoot and Root Biomass of Lucerne Crops—New Insights on the Seasonality of Dry Matter Partitioning and Root Maintenance Respiration 118
1 Introduction 118
2 Materials and Methods 119
3 Results and Discussion 119
References 123
A Morphogenetic Crop Model for Sugar-Beet (Beta vulgaris L.) 125
1 Introduction 125
2 Materials and Methods 126
3 Results and Discussion 129
4 Conclusion 136
Acknowledgements 137
References 137
Coupling Process-Based Models and Plant Architectural Models: A Key Issue for Simulating Crop Production 139
1 Introduction 139
2 Advantages and Limitations of PBMs and FSPMs 140
3 Modeling Plant Development 142
4 Modeling the Biomass Production 145
5 Modeling Biomass Transport and Partitioning 148
6 Conclusion: Why Architecture for Plant Growth Models? 154
References 154
A Functional-Structural Plant Model—Theories and Its Applications in Agronomy 157
1 Introduction 157
2 General Presentation 158
3 Three Levels of the GreenLab Model and Their Applications 159
3.1 GL1 and Parameter Identification for Maize 159
3.2 GL2 and Case Study on Wheat 161
3.3 GL3 and Sweet Pepper 162
4 Theoretical Study 164
4.1 Possible Link with Quantitative Trait Loci (QTL) 164
4.2 Yield Optimization 164
4.3 Plant Competition 166
5 Conclusion and Discussion 167
Acknowledgements 168
References 168
New Approach for the Study of Source-Sink Dynamics on Maize 170
1 Introduction 170
2 Materials and Method 171
3 Results 174
3.1 Maximization of Cob Weight with Fixed Expansion Duration 174
3.2 Maximization of Cob Weight with Variable Expansion Duration 175
4 Discussions 175
Acknowledgements 177
References 177
A Review of Research on the Virtual Plants 178
1 Definition and Signification of the Virtual Plants Research 178
1.1 Definition of Virtual Plants 178
1.2 Research Signification 179
2 Research Situation of the Virtual Plants 179
2.1 Research Status 179
2.2 Virtual Plants Technology 180
2.2.1 Virtual Plant Model 180
2.2.2 Instruments for Virtual Plants Research 180
2.2.3 Main Research Body 181
2.3 Difficulties in the Virtual Plants Research 181
3 Conclusions 182
References 182
Concepts and Applications of AquaCrop: The FAO Crop Water Productivity Model 184
1 Introduction 184
2 Model Description 185
2.1 Model Growth-Engine and Flowchart 185
2.2 The Atmosphere 187
2.3 The Crop 187
2.4 Canopy Development 187
2.5 Biomass and Yield 188
2.6 Transpiration 189
2.7 Responses to Water Stress 189
2.8 The Soil-Root System 190
2.9 The Management 191
3 Model Performance 191
3.1 Maize 191
3.2 Cotton 193
3.3 Soybean 194
3.4 Quinoa 197
4 Concluding Discussion 197
Acknowledgements 198
References 198
Simulating Biomass and Grain Yields of Barley and Oat Crops with the Sirius Wheat Model 201
1 Introduction 202
2 Materials and Methods 203
2.1 Observed Data 203
2.2 Simulations 203
3 Results and Discussion 204
3.1 Final Grain and Crop Biomass Yields 204
3.2 Biomass Accumulation, Partitioning and Canopy Development 206
3.2.1 Barley 206
3.2.2 Oats 207
4 Summary and Conclusions 209
Acknowledgements 210
References 210
Application of the CERES-Wheat Model to Winter Wheat Yield Forecast in Beijing 212
1 Introduction 212
2 Materials and Methods 213
2.1 Experiment Data 213
2.2 CERES-Wheat Model 214
2.3 Cultivar Calibration 214
3 Result and Discussion 215
3.1 Simulation Results and Prediction Results Evaluation 215
4 Summary and Conclusion 216
References 216
Improving the Calibration Process of GreenLab Model on the Cotton Plant 218
1 Introduction 218
2 Materials and Methods 219
2.1 The GREENLAB Model Description 219
2.1.1 Modeling Concepts 219
2.1.2 Summary of Plant Parameters Used in the GREENLAB Model 220
2.2 The Method of Estimating Model Parameters 220
2.2.1 The Single-Stemmed Cotton Plant 220
2.2.2 Estimating the Ground Projection Area (Sp) 221
2.2.3 Estimating Sink Strength Parameters for the Leaf 221
2.2.4 Estimating Sink Strength Parameters for the Internode 222
2.3 Testing the Method with Real Data 222
2.3.1 Source of Data for the Test 222
2.3.2 Data Processing 222
2.3.3 Evaluation of the Proposed Method 222
3 Results 223
3.1 Calculated Parameter Values from Real Data 223
3.2 Fitting the GreenLab Model to Measured Data 224
3.3 Comparison of the Initial and Final Values of Model Parameters 225
4 Discussion and Conclusions 226
Acknowledgements 226
References 226
Dry Matter Production and Partitioning in Tomato: Evaluation of a General Crop Growth Model 228
1 Introduction 228
2 Model Description 228
3 Materials and Methods 229
3.1 Experiment 229
3.2 Model Validation 229
4 Results and Discussion 229
4.1 Dry Matter Production and Distribution 229
4.2 Leaf Area Index 231
4.3 Individual Leaf Area 231
4.4 Truss Appearance and Node Number 232
5 Conclusion 232
Acknowledgements 232
References 233
Spatial and Seasonal Simulations of Irrigated Processing Tomato 234
1 Introduction 234
2 Materials and Methods 235
3 Results and Discussion 238
4 Conclusions 247
Acknowledgements 248
References 248
Development of Feeding Strategies for Cows in Small Scale Dairy Farming Systems in the Highlands of Central Mexico by a Simulation Model and On-Farm Experiments. Phase : Development of a Novel Framework 250
1 Introduction 250
2 Materials and Methods 251
3 Conclusions 256
References 256
Development of Feeding Strategies for Cows in Small Scale Dairy Farming Systems in the Highlands of Central Mexico by a Simulation Model and On-Farm Experiments. Phase : On-farm Experiments and Validation of a Simulation Model 258
1 Introduction 258
2 Materials and Methods 259
3 Results 261
4 Discussion 264
5 Conclusions 265
References 266
The Dynamic Model of Crop Growth System under the Multi-Environment External Force Action and Result Simulation 267
1 Introduction 267
2 The Influence of Interaction Between Multi-Environment External Forces 267
2.1 Photosynthesis Efficiency 267
2.2 Water Regulation 268
2.3 Nitrogen Nutrient Absorption 268
3 Growth Analysis and Quantification 269
3.1 Photosynthesis Stage Quantification 269
3.2 Plant Respiration Stage Quantification 270
3.3 Biomass Growth and Storage Stage Quantification 270
4 Example and Result Simulation 271
4.1 Experiments Setting 271
4.2 The Simulation Result 271
5 Conclusion 272
Acknowledgements 272
References 272
APSIM-Lucerne Validation in the Temperate Climate of New Zealand 274
1 Introduction 274
2 Materials and Methods 274
3 Results 275
3.1 Frost 275
3.2 Increased Leaf Area Removal 275
3.3 Cardinal Temperature 275
3.4 Reducing Stem Populations 276
3.5 Radiation Use Efficiency 276
3.6 Validation 277
4 Discussion 279
References 279
Decision Support System for Greenhouse Environment Control Based on Model 280
1 Introduction 280
2 Materials and Methods 281
2.1 The Principle of Greenhouse Environment Control Based on Model 281
2.2 GHMDSS Develop 281
2.2.1 GHMDS Function 281
2.2.2 GHMDS Construction 282
2.2.3 Knowledge Base System (KBS) 283
2.2.4 Model Base System (MBS) 283
2.2.5 Database System 283
3 Results and Analysis 283
Acknowledgements 284
References 284
A Simulation Analysis on Climate Change –Threats or Opportunities for Agriculture 286
1 Introduction 286
2 Methods 287
3 Results 288
4 Conclusion 289
References 290
Spatial Analysis of Soil Water Balance in an Agricultural District of Southern Italy 291
1 Introduction 291
2 Materials and Methods 292
3 Results and Discussion 294
4 Conclusions 298
Acknowledgements 299
References 299
Uncertainty in Multi-Criteria Evaluation Techniques When Used for Land Suitability Analysis 300
1 Introduction 300
2 Land Suitability Analysis 301
3 Uncertainty Analysis 302
4 AHP Model Predictions 304
5 Experimental Results 304
6 Summary 305
References 307
Simulation of Spatial Variability of Organic Matter on the Vineyard Area Using the Model of Artificial Neural Networks 308
1 Introduction 308
2 Materials and Methods 309
3 Results and Discussion 311
References 314
Integration of a Crop Simulation Model and Remote Sensing Information 316
1 Introduction 316
2 Materials and Methods 317
2.1 Software Implementation Technologies 317
2.2 Requirements Analysis 318
2.3 Simulated Processes 318
2.4 Real Time Access to Remote Detection Information for Forcing and Assimilation 319
3 Results and Discussion 319
3.1 Model Calibration and Validation 319
3.2 LAI Forcing 320
3.3 DSS Software 322
4 Conclusions 324
References 324
Research of Maize Leaf Disease Identifying Models Based Image Recognition 326
1 Introduction 326
2 Material and Method 327
2.1 Images of Diseased Leave Acquisition 327
2.2 Feature Extraction from Images of Disease Spot 327
2.3 System Development Environment 328
3 Results and Analyses 328
3.1 Image Segmentation 328
3.2 Disease Spot Features Extraction 329
3.3 Diagnosis Flow 329
3.4 Program Development 329
4 Discussions 331
5 Conclusions 332
Acknowledgement 332
References 332
Spectral Characteristics of Cotton Infected with Verticillium Wilt and Severity Level of Disease Estimated Models 334
1 Introduction 334
2 Material and Methods 335
2.1 Experiment Field 335
2.2 Design of Experiments 335
2.3 Sampling and SL Classification 336
2.4 Data Collections 336
2.5 Data Analysis 336
3 Results And Analysis 337
3.1 Spectral Characteristics for Leaves of Verticillium Wilt with Different SL 337
3.2 Sensitive Wave Band and Spectral Reflectance Predicting Models 338
3.3 Estimating Models for Verticillium Using First Derivative Spectrum 339
3.4 Estimating Models for Verticillium Using Red Edge Parameters 340
4 Discussions 340
5 Conclusions 341
Acknowledgement 341
References 341