{"product_id":"mathematical-modeling-in-agriculture-hardback-9781394233694","title":"Mathematical Modeling in Agriculture (Hardback) 9781394233694","description":"\u003cfont face=\"Georgia\"\u003e\r\n\u003cp\u003e\u003cfont size=\"6\"\u003eMathematical Modeling in Agriculture\u003c\/font\u003e\u003cbr\u003e\r\n\r\n\r\n\r\n\r\n\r\n\u003c\/p\u003e\n\u003cp\u003e\u003cfont size=\"4\"\u003eSabyasachi Pramanik (Edited by), S Pramanik (Author), Niranjanamurthy M. (Edited by), Ankur Gupta (Edited by), Ahmed J. Obaid (Edited by)\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e9781394233694, Wiley\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eHardback, published 1 November 2024\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e464 pages\u003cbr\u003e22.9 x 15.2 x 2.8 cm, 0.857 kg\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\r\n\r\n\u003cp align=\"justify\"\u003e\u003cstrong\u003e\u003cfont size=\"3\"\u003e\u003cp\u003e\u003cb\u003eThe main goal of the book is to explore the idea behind data modeling in smart agriculture using information and communication technologies and tools to make agricultural practices more functional, fruitful and profitable.\u003c\/b\u003e \u003c\/p\u003e\n\u003cp\u003eThe research in the book looks at the likelihood and level of use of implemented technological components with regard to the adoption of different precision agricultural technologies. To identify the variables affecting farmers’ choices to embrace more precise technology, zero-inflated Poisson and negative binomial count data regression models were utilized. Outcomes from the count data analysis of a random sample of various farm operators show that various aspects, including farm dimension, farmer demographics, soil texture, urban impacts, farmer position of liabilities, and position of the farm in a state, were significantly associated with the approval severity and likelihood of precision farming technologies. \u003c\/p\u003e\n\u003cp\u003eFarm management information systems (FMIS) have constantly advanced in complexity as they have incorporated new technology, the most recent of which is the internet. However, few FMIS have fully tapped into the internet’s possibilities, and the newly developing idea of precision agriculture receives little or no support in the FMIS that are now being sold. FMIS for precision agriculture must meet a few more criteria beyond those of regular FMIS, which increases the technological complexity of these systems’ deployment in a number of ways. In order to construct an FMIS that meet these extra needs, the authors here evaluated various cutting-edge web-based methods. The goal was to determine the requirements that precision agriculture placed on FMIS.\u003c\/p\u003e\u003c\/font\u003e\u003c\/strong\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e\u003cp\u003ePreface xiii\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Analyzing the Impact of Food Safety Regulations on Agricultural Supply Chains: A Mathematical Modeling Perspective 1\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eNimit Kumar, Shwetha M.S., Govind Shay Sharma, Nitin Ubale, Nuzhat Fatima Rizvi and Dharmesh Dhabliya\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e1.1 Introduction 2\u003c\/p\u003e \u003cp\u003e1.2 Resources and Techniques 4\u003c\/p\u003e \u003cp\u003e1.3 Results and Analysis 6\u003c\/p\u003e \u003cp\u003e1.3.1 Knowledge, Application, and Obstacles to Food Modeling 6\u003c\/p\u003e \u003cp\u003e1.3.2 Obstacles to Our Company’s Use of Mathematical Modeling 7\u003c\/p\u003e \u003cp\u003e1.4 Conclusion 12\u003c\/p\u003e \u003cp\u003eReferences 13\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Modeling the Effects of Land Degradation on Agricultural Productivity: Implications for Legal and Policy Interventions 17\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eAmit Verma, Istita Auddy, Murli Manohar Gour, Dhwani Bartwal, Sukhvinder Singh Dari and Ankur Gupta\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e2.1 Introduction 18\u003c\/p\u003e \u003cp\u003e2.2 Materials and Procedures 20\u003c\/p\u003e \u003cp\u003e2.2.1 Content of Minerals 23\u003c\/p\u003e \u003cp\u003e2.3 Results and Analysis 24\u003c\/p\u003e \u003cp\u003e2.4 Conclusion 28\u003c\/p\u003e \u003cp\u003eReferences 29\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Mathematical Modeling of Carbon Sequestration in Agricultural Soils: Implications for Climate Change Mitigation Policies 33\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eKailash Malode, Brijpal Singh Rajawat, Amar Shankar S., Ravindra Kumar, Deepti Khubalkar and Sabyasachi Pramanik\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e3.1 Introduction 34\u003c\/p\u003e \u003cp\u003e3.2 Resources and Techniques 35\u003c\/p\u003e \u003cp\u003e3.2.1 Reference Trial 36\u003c\/p\u003e \u003cp\u003e3.2.2 Interviews with Agriculturists in London Suburb and Liverpool 38\u003c\/p\u003e \u003cp\u003e3.2.2.1 Overall Explanation of the Sampled Region and Organized Interviews 38\u003c\/p\u003e \u003cp\u003e3.2.3 Online Tools for Calculating CF 38\u003c\/p\u003e \u003cp\u003e3.3 Results 40\u003c\/p\u003e \u003cp\u003e3.3.1 Agricultural Data as Model I\/P 40\u003c\/p\u003e \u003cp\u003e3.3.1.1 Case Study 40\u003c\/p\u003e \u003cp\u003e3.3.1.2 From Discussions with Farmers 41\u003c\/p\u003e \u003cp\u003e3.3.2 Farms’ Estimated GHG Emissions 43\u003c\/p\u003e \u003cp\u003e3.3.3 Effects of Mitigating Measures 44\u003c\/p\u003e \u003cp\u003e3.4. Discussion 44\u003c\/p\u003e \u003cp\u003e3.4.1 Evaluating the Possible Effects of Mitigating Measures 46\u003c\/p\u003e \u003cp\u003e3.5 Conclusions 47\u003c\/p\u003e \u003cp\u003eReferences 48\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Optimizing Livestock Feed Formulation for Sustainable Agriculture: A Mathematical Modeling Approach 51\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eRutul Patel, Upasana, Ashutosh Pattanaik, Deepak Kumar, Ahmar Afaq and Soma Bag\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e4.1 Introduction 52\u003c\/p\u003e \u003cp\u003e4.2 Managing Swine Herds Using Modeling 53\u003c\/p\u003e \u003cp\u003e4.2.1 System of a Sow Herd 53\u003c\/p\u003e \u003cp\u003e4.2.2 Major Statistical Techniques Used in Modeling Cattle Herds 55\u003c\/p\u003e \u003cp\u003e4.2.2.1 Literature Review on Herd Modeling for Cattle 55\u003c\/p\u003e \u003cp\u003e4.2.2.2 Models for Simulation 56\u003c\/p\u003e \u003cp\u003e4.2.2.3 Models for Optimization 56\u003c\/p\u003e \u003cp\u003e4.2.2.4 The Integration of Simulation and Optimization 57\u003c\/p\u003e \u003cp\u003e4.3 Models of a Sow Herd 58\u003c\/p\u003e \u003cp\u003e4.3.1 Chosen Models 58\u003c\/p\u003e \u003cp\u003e4.3.2 Input Criteria 59\u003c\/p\u003e \u003cp\u003e4.3.2.1 Parameters Used as Inputs in Optimization Models 59\u003c\/p\u003e \u003cp\u003e4.3.2.2 Parameters Used as Inputs in Simulation Techniques 60\u003c\/p\u003e \u003cp\u003e4.3.3 Results from the Models 61\u003c\/p\u003e \u003cp\u003e4.3.4 The Models’ Validation 62\u003c\/p\u003e \u003cp\u003e4.3.5 Opportunities for Implementation and Integration 63\u003c\/p\u003e \u003cp\u003e4.3.6 Management of Risk 64\u003c\/p\u003e \u003cp\u003e4.3.7 Additional Submissions and Literature Review 64\u003c\/p\u003e \u003cp\u003e4.4 Discussion 65\u003c\/p\u003e \u003cp\u003e4.5 Conclusions 68\u003c\/p\u003e \u003cp\u003eReferences 69\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Modeling the Economic Impact of Agricultural Regulations: A Case Study on Environmental Compliance Costs 81\u003c\/b\u003e\u003cbr\u003e \u003ci\u003eVikesh Rami, Sunil Kumar, Gautham Krishna, Abhinav, Sukhvinder Singh Dari and Dharmesh Dhabliya\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e5.1 Introduction 82\u003c\/p\u003e \u003cp\u003e5.2 Mechanisms Study Time and Location 83\u003c\/p\u003e \u003cp\u003e5.3 Sampling 85\u003c\/p\u003e \u003cp\u003e5.4 Analysis, Both Physical and Chemical 85\u003c\/p\u003e \u003cp\u003e5.5 Module for Water Quality 87\u003c\/p\u003e \u003cp\u003e5.6 Particulate Phosphorus and Suspended Solids 87\u003c\/p\u003e \u003cp\u003e5.7 Calculation of PP 88\u003c\/p\u003e \u003cp\u003e5.8 Model Caliphy 89\u003c\/p\u003e \u003cp\u003e5.9 Scientifications Described by the Model 94\u003c\/p\u003e \u003cp\u003e5.10 Simulation of Sediment Trap 96\u003c\/p\u003e \u003cp\u003e5.11 Pumping Profile Modifications Simulation 98\u003c\/p\u003e \u003cp\u003e5.12 Conclusion 98\u003c\/p\u003e \u003cp\u003eReferences 99\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Quantifying the Economic Benefits of Precision Agriculture Technologies: A Mathematical Modeling Study 103\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eDeepak Kumar, Apexaben Rathod, Sachchida Nand Singh, Meena Y. R., Rushil Chandra and Ankur Gupta\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e6.1 Introduction 104\u003c\/p\u003e \u003cp\u003e6.2 Method and Materials 107\u003c\/p\u003e \u003cp\u003e6.3 Conclusion and Results 110\u003c\/p\u003e \u003cp\u003e6.4 Conclusions 112\u003c\/p\u003e \u003cp\u003eReferences 113\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Optimizing Resource Allocation in Agribusinesses: A Mathematical Modeling Approach Considering Legal Factors 115\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eVishvendra Singh, Navghan Mahida, Anand Janardan Madane, Sudhakar Reddy, Parth Sharma and Sabyasachi Pramanik\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eIntroduction 116\u003c\/p\u003e \u003cp\u003eMethods 119\u003c\/p\u003e \u003cp\u003eA Framework for the Transmission and Command\u003c\/p\u003e \u003cp\u003eof Brucellosis: A Case Study Overview 120\u003c\/p\u003e \u003cp\u003eBrucellosis Nominal Transmission Modeling 120\u003c\/p\u003e \u003cp\u003eModeling Disease Costs and Control Capabilities 124\u003c\/p\u003e \u003cp\u003eCreating a Cost Model and Confronting the Challenge of Control Design 125\u003c\/p\u003e \u003cp\u003eAnalysis, Design, and Parameterization Techniques 127\u003c\/p\u003e \u003cp\u003eOverview of the Control and Surveillance Design 128\u003c\/p\u003e \u003cp\u003eNetwork Model Identification and Validation for Zoonoses 129\u003c\/p\u003e \u003cp\u003eResults 130\u003c\/p\u003e \u003cp\u003eIndicative Model 131\u003c\/p\u003e \u003cp\u003eControl Strategy Modeling 135\u003c\/p\u003e \u003cp\u003eOptimized Approaches 137\u003c\/p\u003e \u003cp\u003eParameterization 143\u003c\/p\u003e \u003cp\u003eDiscussion 143\u003c\/p\u003e \u003cp\u003eWide-Ranging Perspectives on High-Performance Control 144\u003c\/p\u003e \u003cp\u003eTalking About Parameterzing Models 147\u003c\/p\u003e \u003cp\u003eConclusion 148\u003c\/p\u003e \u003cp\u003eReferences 150\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Modeling the Dynamics of Agricultural Cooperatives and Legal Implications for Farmer Organizations 153\u003c\/b\u003e\u003ci\u003e\u003cbr\u003e Shiv Shankar Shankar, Prashantkumar Zala, Ashutosh Awasthi, Ezhilarasan G., Sukhvinder Singh Dari and Soma Bag\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e8.1 Introduction 154\u003c\/p\u003e \u003cp\u003e8.2 Resources and Techniques 155\u003c\/p\u003e \u003cp\u003e8.3 Conclusion 160\u003c\/p\u003e \u003cp\u003eReferences 160\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Optimizing Agroforestry Systems for Sustainable Agriculture: A Mathematical Modeling Approach 163\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eBeemkumar Nagappan, Aakriti Chauhan, Chandni Mori, Praveen Kumar Singh, Shilpa Sharma and Sabyasachi Pramanik\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e9.1 Introduction 164\u003c\/p\u003e \u003cp\u003e9.2 Relationships Between Structure and Activity (SAR) and the Level of Toxicological Involvement 169\u003c\/p\u003e \u003cp\u003e9.3 Threshold Approaches 174\u003c\/p\u003e \u003cp\u003e9.4 Reciprocal Analysis 178\u003c\/p\u003e \u003cp\u003e9.5 Chemical-Specific Adjustments 183\u003c\/p\u003e \u003cp\u003eConclusion 184\u003c\/p\u003e \u003cp\u003eReferences 185\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Simulating the Effects of Climate-Smart Agriculture Practices on Farm Resilience: A Mathematical Modeling Approach 189\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eKiran K. S., Meenakshi Dheer, Mukesh Laichattiwar, Devendra Pal Singh, Vaidehi Pareek and Soma Bag\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e10.1 Introduction 190\u003c\/p\u003e \u003cp\u003e10.2 Definitions, Concepts, and Methods for the Analytical Framework 191\u003c\/p\u003e \u003cp\u003e10.3 Results 194\u003c\/p\u003e \u003cp\u003e10.4 Consequences for Political Implementations 203\u003c\/p\u003e \u003cp\u003e10.5 Advanced Research 204\u003c\/p\u003e \u003cp\u003e10.6 Conclusions 206\u003c\/p\u003e \u003cp\u003eReferences 207\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Modeling the Dynamics of Agrochemical Regulations and Impacts on Agricultural Productivity 211\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eHannah Jessie Rani, Akanchha Singh, Aishwary Awasthi, Ashwani Rawat, Nuvita Kalra and Ankur Gupta\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e11.1 Introduction 212\u003c\/p\u003e \u003cp\u003e11.2 Resources and Techniques 213\u003c\/p\u003e \u003cp\u003e11.3 Results 216\u003c\/p\u003e \u003cp\u003e11.4 Discussion 217\u003c\/p\u003e \u003cp\u003e11.5 Conclusion 219\u003c\/p\u003e \u003cp\u003eReferences 220\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 Optimizing Energy Consumption in Greenhouse Production: A Mathematical Modeling Approach 223\u003c\/b\u003e\u003ci\u003e\u003cbr\u003e Beemkumar Nagappan, Arun Gupta, Sachin Gupta, Diksha Nautiyal, Aarti Kalnawat and Dharmesh Dhabliya\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e12.1 Introduction 224\u003c\/p\u003e \u003cp\u003e12.2 Literature Review 227\u003c\/p\u003e \u003cp\u003e12.3 The Creation of Mathematical Models a Range of Models 229\u003c\/p\u003e \u003cp\u003e12.4 Formulation of a Model 231\u003c\/p\u003e \u003cp\u003e12.5 Modeling of Groundwater Quality 242\u003c\/p\u003e \u003cp\u003e12.6 Conclusion 244\u003c\/p\u003e \u003cp\u003eReferences 244\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13 Analyzing the Economic and Legal Impacts of Intellectual Property Rights on Plant Breeding Innovations: A Mathematical Modeling Study 249\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eGopalakrishna K., Bhirgu Raj Maurya, Rajeev Kumar, Sushila Arya, Himanshi Bhatia and Ankur Gupta\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e13.1 Introduction 250\u003c\/p\u003e \u003cp\u003e13.2 Competition Postulates 251\u003c\/p\u003e \u003cp\u003e13.3 Transparent Competition 251\u003c\/p\u003e \u003cp\u003e13.3.1 Effect of Competitiveness-Density 252\u003c\/p\u003e \u003cp\u003e13.3.2 Changes to the Population’s Size Structure 252\u003c\/p\u003e \u003cp\u003e13.4 Concurrence Inter-Specific 253\u003c\/p\u003e \u003cp\u003e13.4.1 Adding Damage 254\u003c\/p\u003e \u003cp\u003e13.4.2 Neighborhood Function 256\u003c\/p\u003e \u003cp\u003e13.4.3 Innovative Design and Analysis 256\u003c\/p\u003e \u003cp\u003e13.5 Dynamic Plant Growth and Competition Models 256\u003c\/p\u003e \u003cp\u003e13.5.1 Dynamic Population 258\u003c\/p\u003e \u003cp\u003e13.6 Aspects Impacting the Result of Competitiveness 259\u003c\/p\u003e \u003cp\u003e13.7 Crop-Weed Competition Models Applied in Practical Situations 260\u003c\/p\u003e \u003cp\u003e13.8 Conclusion 261\u003c\/p\u003e \u003cp\u003eReferences 262\u003c\/p\u003e \u003cp\u003e\u003cb\u003e14 Simulating the Effects of Land Use Regulations on Agricultural Land Values: A Mathematical Modeling Study 265\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eAshwani Rawat, Ramachandran T., Yogesh Chandra Gupta, Manoj Kumar Mishra, Gabriela Michael and Sabyasachi Pramanik\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e14.1 Introduction 266\u003c\/p\u003e \u003cp\u003e14.2 Models of Component Agricultural Systems 267\u003c\/p\u003e \u003cp\u003e14.3 Present-Day Farming System Frameworks in Relation to Certain Application Situations 284\u003c\/p\u003e \u003cp\u003e14.4 Discussion 286\u003c\/p\u003e \u003cp\u003eReferences 290\u003c\/p\u003e \u003cp\u003e\u003cb\u003e15 Simulating the Effects of Agricultural Land Fragmentation on Farm Effciency: A Mathematical Modeling Analysis 295\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eDiksha Nautiyal, Manjunath H. R., Praveen Kumar Singh, Umesh Kumar Tripathi, Saurabh Raj and Soma Bag\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e15.1 Introduction 296\u003c\/p\u003e \u003cp\u003e15.2 Conceptual Foundation 297\u003c\/p\u003e \u003cp\u003e15.3 Resources and Techniques Household Polls 299\u003c\/p\u003e \u003cp\u003e15.4 Results 306\u003c\/p\u003e \u003cp\u003e15.5 Discussion 313\u003c\/p\u003e \u003cp\u003e15.6 Conclusions 316\u003c\/p\u003e \u003cp\u003eReferences 317\u003c\/p\u003e \u003cp\u003e\u003cb\u003e16 Simulating the Effects of Land Use Policies on Agricultural Productivity: A Mathematical Modeling Perspective 321\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eVinaya Kumar Yadav, Sushila Arya, Asha Rajiv R., Devendra Pal Singh, Siddharth Ranka and Dharmesh Dhabliya\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e16.1 Introduction 322\u003c\/p\u003e \u003cp\u003e16.2 Upcoming Applications of NextGen Farming Frameworks 326\u003c\/p\u003e \u003cp\u003e16.3 Envisioned Consumers of the Application Chain Beneficiaries 331\u003c\/p\u003e \u003cp\u003e16.4 Conclusion and Research Plan 340\u003c\/p\u003e \u003cp\u003eReferences 341\u003c\/p\u003e \u003cp\u003e\u003cb\u003e17 Quantifying the Economic Benefits of Agricultural Extension Services: A Mathematical Modeling Analysis 345\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eRajeev Kumar, Satendra Kumar, Pradeepa P., Akanchha Singh, Karun Sanjaya and Ankur Gupta\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e17.1 Introduction 346\u003c\/p\u003e \u003cp\u003e17.2 Creating New Models for the Future: A Demand-Driven, Prospective Strategy 347\u003c\/p\u003e \u003cp\u003e17.3 Potential Improvements to Model Elements 355\u003c\/p\u003e \u003cp\u003e17.4 Conclusions 367\u003c\/p\u003e \u003cp\u003eReferences 368\u003c\/p\u003e \u003cp\u003e\u003cb\u003e18 Modeling the Impact of Agricultural Investment Incentives on Rural Development: Legal and Economic Perspectives 373\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eDal Chandra, Manoj Kumar Mishra, Ankit Pant, Ahmadi Begum, Sukhvinder Singh Dari and Dharmesh Dhabliya\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e18.1 Introduction 374\u003c\/p\u003e \u003cp\u003e18.2 Approach 376\u003c\/p\u003e \u003cp\u003e18.3 Conversation 384\u003c\/p\u003e \u003cp\u003e18.4 Conclusion 390\u003c\/p\u003e \u003cp\u003eReferences 391\u003c\/p\u003e \u003cp\u003e\u003cb\u003e19 Optimizing Harvest Scheduling in Agriculture: A Mathematical Modeling Approach Considering Legal Restrictions 397\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eHeejeebu Shanmukha Viswanath, Umesh Kumar Tripathi, Minnu Sasi, Kishore Kumar Pedapenki, Prashant Dhage and Ankur Gupta\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e19.1 Initialization 398\u003c\/p\u003e \u003cp\u003e19.2 Structure of the System 406\u003c\/p\u003e \u003cp\u003e19.3 Irrigation Community Event 409\u003c\/p\u003e \u003cp\u003e19.4 Assessment and Authentication 412\u003c\/p\u003e \u003cp\u003e19.5 Conclusions 416\u003c\/p\u003e \u003cp\u003eReferences 418\u003c\/p\u003e \u003cp\u003e\u003cb\u003e20 Quantifying the Economic Benefits of Agricultural Data Sharing: A Mathematical Modeling Perspective 421\u003c\/b\u003e\u003cbr\u003e \u003ci\u003eAruno Raj Singh, Vinaya Kumar Yadav, Laishram Zurika, Dasarathy A. K., Abhishekh Benedict and Dharmesh Dhabliya\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e20.1 Introduction 422\u003c\/p\u003e \u003cp\u003e20.2 Model for Data Mining Process 423\u003c\/p\u003e \u003cp\u003e20.3 Techniques for Machine Learning 424\u003c\/p\u003e \u003cp\u003e20.4 Website Tools 429\u003c\/p\u003e \u003cp\u003e20.5 Case Study: Grading of Mushrooms 431\u003c\/p\u003e \u003cp\u003e20.6 Conclusion 432\u003c\/p\u003e \u003cp\u003eReferences 433\u003c\/p\u003e \u003cp\u003eIndex 437\u003c\/p\u003e\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eSubject Areas: Agriculture \u0026amp; farming [\u003ca title=\"See our other books on Agriculture \u0026amp; farming\" href=\"https:\/\/freshlyprintedbooks.co.uk\/search?q=%22Agriculture%20\u0026amp;%20farming%20%5BTV%5D%22\"\u003eTV\u003c\/a\u003e]\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003c\/font\u003e","brand":"Wiley-Scrivener","offers":[{"title":"Brand New","offer_id":52433222140184,"sku":"9781394233694","price":134.69,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0730\/2037\/5320\/files\/9781394233694.jpg?v=1784852101","url":"https:\/\/freshlyprintedbooks.co.uk\/products\/mathematical-modeling-in-agriculture-hardback-9781394233694","provider":"Freshly Printed Books","version":"1.0","type":"link"}