Agricultural Biotechnology: Food Security Hot Spots

Cover
Half Title
Series Page
Title Page
Copyright Page
Table of Contents
Preface
Editors
Contributors
Chapter 1 Agricultural System Modeling and Analysis
1.1 Introduction
1.2 Brief History
1.3 Definition of Agricultural System Model
1.4 Farming Systems Innovation
1.5 The Users of Agricultural Systems Models
1.6 Types of Agricultural Systems
1.7 Challenges to Systems Modeling for Farming Systems Innovation
1.7.1 Involving the Right People in the Right Way to Ensure Compatibility with User Needs and Processes
1.7.2 Determining What System to Model to Remain Relevant to Stakeholder Concerns
1.7.3 Representing in Models What Farm Managers Might Do
1.7.4 Making Sound Comparisons between Alternative Farm Management Policies
1.8 Evolution of Modeling Approaches in Farming Systems
1.8.1 Subsistence Agriculture
1.8.2 Commercial Agriculture
1.8.3 Extensive and Intensive Agriculture
1.9 Conclusion
References
Chapter 2 A Discourse beyond Food Security and Environmental Security: Dear Epistemic Community, Should We Consider Agro-Security?
2.1 Introduction
2.2 Theoretical Contextualization
2.3 Human Security Concerns: The Simultaneous Equation between Food Security and Environmental Security
2.4 Dear “Epistemic Community”, Should We Consider Agro-Security?
2.5 The Way Forward: The Dynamics of Leveraging Agro-Security as an Alternative
2.6 Conclusion
References
Chapter 3 The Epistemic Communities, Food and Agriculture Organisation (FAO)
and Food Security in the Third World
3.1 Introduction
3.2 FAO and the Epistemic Communities: A Succinct Introduction
3.2.1 Food and Agriculture Organisation: A Background
3.2.2 Epistemic Communities: A Theory and Concept
3.3 Food Security in the Third World Countries
3.4 Four Dimensions of Food Security in the Third World
3.5 Emerging Limitations to Food Security from the Third World
3.6 The Epistemic Community, FAO and the State of Food Security in the Third World
3.7 Conclusion
References
Chapter 4 Recent Advances in Application of Biostimulants Derived from Beneficial
Microorganisms: Agriculture and Environmental Perspective
4.1 Introduction
4.2 Modes of Action of Biostimulants
4.3 Concept of Biostimulation
4.4 Microbial and Non-microbial Biostimulants
4.4.1 Non-microbial Biostimulants
4.4.1.1 Humic and Fluvic Acid
4.4.1.2 Protein-Based Biostimulant
4.4.1.3 Seaweed Extracts
4.4.2 Micriobial Bisotimulants
4.4.2.1 Plant Growth Promoting Microorganisms
4.5 Conclusion and Future Recommendation
References
Chapter 5 Genome Engineering in Agriculturally Beneficial Microorganisms
Using CRISPR-Cas9 Technology
5.1 CRISPR–Cas9 Technology – A Powerful Tool for Genome Engineering
5.1.1 Introduction to Genome Engineering
5.1.2 Basics and History of CRISPR–Cas9 Technology
5.1.3 Mechanism of CRISPR-Cas System
5.1.4 Classification of Cas Proteins in CRISPR-Cas Systems
5.1.5 Online Resources to Design CRISPR Nucleases
5.1.6 CRISPRi and CRISPRa for Precise Control of Gene Expression
5.1.7 Applications of CRISPR-Cas9 Technology
5.2 Agriculturally Beneficial Microorganisms
5.2.1 Important Functions of Agriculturally Beneficial Microorganisms
5.2.1.1 Microorganisms as Fertilizer
5.2.1.2 Microorganisms as Plant Growth Promoter
5.2.1.3 Microorganisms as Stress Defender
5.2.2 Necessity of Genome Editing in Agriculturally Beneficial Microorganisms
5.3 CRISPR-Cas9 Assisted Genome Engineering in Agriculturally Beneficial Microbes
5.3.1 Enhancing Plant Growth and Nutrient Availability
5.3.2 Understanding the Basics of the PM Interactions
5.3.3 Enhancing Plant Biotic Stress Resistance
5.4 Conclusion
References
Chapter 6 AI-Based Agricultural Knowledge System
6.1 Introduction
6.2 Importance of Agricultural Information Systems and Their Needs for Agricultural Production
6.3 Defining of Agricultural Information System
6.3.1 GIS (Geographic Information System)
6.3.2 Centre of Agriculture
6.4 Types of Information, Providers and Users
6.5 Sources of Agricultural Information
6.6 Brief Explanation of Traditional System Design and Implementation Processes
6.6.1 Access Fund Balance Online
6.6.2 Process A
6.7 Developing a Framework for Market Access
6.7.1 Management
6.7.2 Infrastructure
6.7.3 Technology
6.7.4 Funding
6.7.5 Inputs and Outputs
6.8 End Users
6.9 Conclusion
References
Chapter 7 Augmentation of Precision Agriculture by Application of Artificial Intelligence
7.1 Introduction
7.2 Geospatial Technologies in Precision Agriculture
7.2.1 Global Positioning System
7.2.1.1 Role of GPS in PA
7.2.1.2 Barriers to Using GPS in PA
7.2.2 Geographic Information Systems
7.2.2.1 Role of GIS in PA
7.2.2.2 Barriers to Using GIS in PA
7.2.3 Remote Sensing
7.2.3.1 Role of RS in PA
7.2.3.2 Barriers to Using RS in PA
7.3 AI-Based Crop Management
7.3.1 Neural Nets
7.3.1.1 ANN
7.3.1.2 Convolutional Neural Network (CNN)
7.3.2 Machine Learning
7.3.2.1 Support Vector Machine (SVM)
7.3.2.2 K Nearest Neighbor
7.3.3 Bio-Inspired
7.3.3.1 Swarm
7.3.3.2 Evolutionary
7.4 AI-Based Soil Management
7.4.1 Neural Nets
7.4.1.1 Artificial Neural Network (ANN)
7.4.1.2 Convolutional Neural Network
7.4.2 Machine Learning
7.4.2.1 Support Vector Machine (SVM)
7.4.2.2 K Nearest Neighbor
7.4.3 Bio-Inspired
7.4.3.1 Swarm
7.4.3.2 Evolutionary
7.5 AI-Based Water Management
7.5.1 Neural Nets
7.5.1.1 Artificial Neural Network (ANN)
7.5.1.2 Convolutional Neural Network (CNN)
7.5.2 Machine Learning
7.5.2.1 Support Vector Machine (SVM)
7.5.2.2 K Nearest Neighbor
7.5.3 Bio-Inspired
7.5.3.1 Swarm
7.5.3.2 Evolutionary
7.6 Future Scope and Challenges of AI in Precision Agriculture
7.7 Conclusion
Acknowledgments
References
Chapter 8 Modes of Action of Beneficial Microorganism as a Typical Example of
Microbial Pesticides
8.1 Introduction
8.2 Beneficial Microorganisms
8.3 Biopesticides
8.3.1 Microbial Pesticides
8.3.1.1 Bacteria
8.3.1.2 Fungi
8.3.1.3 Virus
8.3.1.4 Nematode
8.3.1.5 Protozoa
8.4 Conclusion
References
Chapter 9 Genetically Modified Orange: From Farm to Food the Undiscovered
Medicinal and Food Benefits
9.1 Introduction
9.2 Mutation and Conventional Techniques for the Breeding of Orange Varieties
9.3 Recent Advances on Genetically Modified Oranges with Some Specific Examples
9.4 Anticancer Activity of Orange
9.5 Antioxidant Properties
9.6 Anti-Canker
9.7 Conclusion and Future Recommendation
References
Chapter 10 Advancing Aquaculture with Artificial Intelligence
10.1 Introduction
10.2 Smart Fish Farm Systems
10.3 Artificial Intelligence for the Development of Aquaculture Systems
10.3.1 Technologies Employed in Support of Artificial Intelligence
10.3.1.1 Data Acquisition for Aquaculture Processing
10.3.1.2 Computerized Models
10.3.1.3 Decision Systems
10.4 Artificial Intelligence Concepts Commonly Used in Aquaculture Systems
10.4.1 Expert Systems (ES) or Knowledge Based Systems (KBS)
10.4.2 Neural Networks
10.5 Processes Prevalent in Aquaculture Systems
10.5.1 Management of Fish Feed
10.6 Disease Detection in Fish
10.7 Water Quality Monitoring
10.8 Swarm Intelligence in Fishing
10.8.1 Need for Optimization in Aquaculture
10.8.2 Swarm Intelligence
10.8.3 Particle Swarm Optimization (PSO)
10.8.4 Applications of PSO in Aquaculture
10.8.5 Swarm Robotics
10.9 Challenges and Future Scope
Declaration
Authors Contribution
Acknowledgments
Availability of Data and Material
Competing Interests
Funding
Consent for Publication
Ethics Approval and Consent to Participate
References
Chapter 11 A Computational Approach for Prediction and Modelling of Agricultural
Crop Using Artificial Intelligence
11.1 Introduction
11.2 Fuzzy Set in Agriculture
11.2.1 Fuzzy Sets in Agricultural Sustainability
11.2.1.1 Sustainability in Agriculture
11.2.1.2 Modelling Sustainability with Fuzzy Sets
11.3 Creating Fuzzy Logic Models
11.3.1 FLMs and Image Processing Techniques
11.3.2 Fuzzy Expert System in Agriculture
11.3.3 Neural Network Approach in Agricultural Sector
11.4 Agriculture Crop Prediction Using Artificial Neural Network
11.4.1 Feed-Forward Neural Network Using Back Propagation Algorithm
11.4.2 Model Design with GUI
11.4.2.1 Data Collection
11.4.2.2 Build/Develop the Prediction Model
11.5 Classification of Predicted Crop
11.6 Appropriate Fertilizer Based on the Required Crop
11.6.1 Agricultural Crop Growth and Soil Fertility Using Self-Organizing Maps
and Multilayer Feed-Forward Neural Network Using Back Propagation
Algorithm
11.6.1.1 Clustering Using Self-Organizing Map on IRIS Dataset
11.6.1.2 Limitations of Self-Organizing Maps
11.7 Evolutionary Computing in Agriculture
11.7.1 Multi-Objective Optimization Methods
11.7.1.1 Weighted Sum Method (WSM)
11.7.1.2 ε-Constraint Method
11.7.1.3 Non-Dominated Sorting Genetic Algorithm (NSGAII)
11.7.2 Evolutionary Strategies
11.7.3 Evolutionary Programming
11.7.4 Genetic Algorithm
11.8 Swarm Intelligence
11.8.1 Swarm Intelligence Techniques for Annual Crop Planning
11.8.1.1 Cuckoo Search (CS)
11.8.1.2 Firefly Algorithm (FA)
11.8.1.3 Glow-Worm Swarm Optimization (GSO)
11.8.1.4 Case Study: Comparison of CS, FA, GSO and Genetic
Algorithm (GA)
11.8.2 Crop Classification Using Artificial Bee Colony Optimization
Declaration
Authors Contribution
Acknowledgements
Availability of Data and Material
Competing Interests
Funding
Consent for Publication
Ethics Approval and Consent to Participate
References
Chapter 12 Artificial Intelligence in Crop Monitoring
12.1 Introduction
12.2 Field Mapping
12.2.1 Aerial Photography
12.2.2 UAV Method
12.3 Precision Agriculture (PA)
12.3.1 Drone Systems
12.3.2 Using GPS
12.3.3 UAV Models
12.3.4 Site-Specic fiManagement
12.4 Remote Sensing
12.4.1 Airborne Technique
12.4.2 ANN Model for Crop Yield Responding to Soil Parameters
12.5 Conclusion
Declaration
Authors Contribution
Acknowledgements
Availability of Data and Material
Competing Interests
Funding
Consent for Publication
Ethics Approval and Consent to Participate
References
Chapter 13 Application of Microbial Enzyme in Food Biotechnology
13.1 Introduction
13.2 Microbial Enzymes for Food Application
13.3 Microbial Enzymes in Food Biotechnology and Processing
13.4 Conclusion and Future Recommendation to Knowledge
References
Chapter 14 Nanosensor Technology for Smart Intelligent Agriculture
14.1 Introduction
14.2 Plant Signaling Molecules for Monitoring Crop Health
14.3 Nanosensors Technology
14.3.1 Electrochemical Nanosensors
14.3.2 Optical Nanosensors
14.3.3 Piezoelectric Nanosensors
14.3.4 Metal or Metalloid Nanoparticles-Based Nanosensors
14.3.5 Quantum Dots
14.4 Developments in Nanosensor Technology
14.4.1 FRET Nanosensors
14.4.1.1 Surface-Enhanced Raman Scattering Nanosensors (SERS)
14.4.2 CoPhMoRe Nanosensors
14.4.3 Array-Based Nanosensors
14.4.4 Wearable Nanosensors
14.4.5 Genetically Encoded Nanosensors
14.5 Emerging Nanodiagnostic Tools for Plant Diseases
14.5.1 Detecting Plant Infections
14.5.2 Detecting Abiotic Stress-Induced Plant Disease
14.5.3 Monitoring Plant Growth
14.5.4 Detecting GM Crops
14.6 Smart Sensing Technology for Monitoring Crop Health Status
14.6.1 The Point-Of-Care Technology
14.6.2 Mobile Technology for Crop Diagnostics
14.6.3 Wireless Sensor Network Technology
14.7 Monitoring of Crop Health Status in Real-Time
14.8 Nanosensor Communication and Actuation System with Machines
14.9 Challenges and Future Perspectives
14.10 Conclusions
References
Chapter 15 Artificial Intelligence-aided Bioengineering of Eco-friendly Microbes for Food Production: Policy and Security Issues in a Developing Society
15.1 Introduction
15.2 Artificial Intelligence-aided Bioengineering of Eco-friendly Microbes for Food
Production
15.2.1 Biotechnology/Bioengineering in Food Production and Processing
15.3 Application of Artificial Intelligence-aided Bioengineering of Eco-friendly Microbes
for Food Production
15.4 Policy and Security Issues on AI-Bioengineered Microbes
15.5 Conclusion and Future Recommendations
References
Chapter 16 Recent Developments and Application of Potato Plant-Based Polymers
16.1 Introduction
16.2 Comparison with Other Bioequivalent Material
16.3 Dynamics of Potato Biopolymer in Regional Bioeconomic Growth
16.3.1 Applications of Potato Biopolymer and Their Consequential Economic Advantages
16.3.1.1 Potato Biopolymer in Food Industries
16.3.1.2 Potato Biopolymer in Constructions
16.4 Recent Advances in Potato Starch and Biopolymer Applications
16.4.1 Film Making
16.4.2 Food and Beverage Industry
16.4.3 Paper Industry
16.4.4 Adhesive
16.4.5 Stabilizer in Yogurt Manufacturing
16.4.6 Textile Manufacturing
16.4.7 Nanoparticles Synthesis
16.4.8 Oil Drilling and Mining
16.4.9 Water Treatment
16.4.10 Pharmaceutical Industries
16.4.11 Thermoplastic Starch
16.4.12 Ceramic Processing
16.4.13 Packaging Material
16.5 Techniques Advanced for the Exploration of Recyclable Potato-Based
16.6 Factors Affecting Medium-Large Scale Production of Potato Polymers
16.6.1 Competition with Food Need
16.6.2 Rising Cost of Food
16.6.3 High-Quality Feedstock
16.6.4 Performance of Potato Polymers
16.6.5 Cost of Production
16.6.6 Process Ability
16.6.7 Biodiversity and Global Warming
16.6.8 Research and Technology
16.7 Conclusion
References
Chapter 17 The Introduction of Biotechnology into Food Engineering
17.1 Introduction
17.1.1 Biotechnology
17.1.2 Food Engineering
17.2 The Role of Biotechnology in Modern Food Production
17.3 Challenges
References
Chapter 18 Plant Resident Microorganisms: A Boon for Plant Disease Management
18.1 Introduction
18.2 Ecology of Endophytes
18.2.1 Population Dynamics of Endophytes in Different Plant Parts
18.2.2 Influence of Climate and Topography on Population Diversity of Endophytes
18.3 Method of Isolation
18.4 Mode of Entry
18.5 Applications in Agriculture
18.5.1 Biotic Stress Alleviation
18.5.2 Abiotic Stress Alleviation
18.6 Conclusion
References
Chapter 19 Application of Remote Sensing in Smart Agriculture Using Artificial Intelligence
19.1 Introduction
19.2 Application of Remote Sensing in Agriculture
19.3 Precision Farming
19.3.1 Tools and Equipment
19.3.2 Image Related Issues
19.4 Crop Yield Forecasting
19.4.1 Optical Remote Sensing-Based Mapping Method
19.4.2 Microwave Remote Sensing-Based Mapping Method
19.5 Climate Change Monitoring
19.5.1 Surface Processes
19.5.2 Subsurface Processes
19.5.2.1 A Functional Climate-Permafrost Model
19.5.2.2 A General Approach on Climate Monitoring over All Regions
19.6 Crop Identification
19.7 Limitations
19.8 Conclusion
Declaration
Authors Contribution
Acknowledgements
Availability of Data and Material
Competing Interests
Funding
Consent for Publication
Ethics Approval and Consent to Participate
References
Chapter 20 Trends in Processing, Preservation of Tomatoes and Its Allied Products: A Review
20.1 Introduction
20.2 Products from Tomato Processing
20.2.1 Tomato Paste
20.2.2 Tomato Juice
20.2.3 Tomato Ketchup
20.2.4 Tomato Sauces
20.3 Tomato Preservation
References
Chapter 21 Relevance of Natural Bioresources and Their Application in Pharmaceutical, Food and Environment
21.1 Introduction
21.2 Natural Bioresources and Their Application in Pharmaceutical, Food and Environment
21.3 Plant Bioresources
21.4 Marine Bioresources
21.5 Edible Insects Bioresources
21.6 Agricultural-Based Bioresources
21.7 Conclusion and Future Recommendation to Knowledge
References
Chapter 22 Genetically Modified and Wild Potatoes: Depository of Biologically Active Compounds and Essential Nutrients
22.1 Introduction
22.2 Biologically Active Compounds of Genetically Modified Potatoes
22.3 List of Phytochemicals and Biologically Active Components Present in Potatoes
22.3.1 Anti-Inflammatory In Vitro and In Vivo
22.3.2 Cardiovascular Effect
22.3.3 Neuroprotective Effect
22.4 Antidiabetic Activity of Genetically Modified Potatoes
22.5 Antifungal Activity
22.6 Antiviral Activity
22.6.1 In Vivo Antiviral Activity
22.7 Antibacterial Activity
22.8 Antiulcer Activity of Genetically Modified Potato
22.9 Anti-Hyperlipidemic Activity
22.10 Anticancer Activity
22.11 Anti-Allergen
22.12 Antioxidant Properties
22.13 Conclusion and Future Recommendation
References
Chapter 23 Recent Advances in the Application of Metagenomic in Promoting Food Security, Human Health, and Environmental Sustainability
23.1 Introduction
23.2 Recent Advances in the Application of Metagenomic in Promoting Food Security
23.3 Recent Advances in the Application of Metagenomic in Promoting Human Health
23.4 Recent Advances in the Application of Metagenomic in Promoting Environmental  Sustainability
23.5 Conclusion and Future Recommendation to Knowledge
References
Index