Recipient Organization
PURDUE UNIVERSITY
(N/A)
WEST LAFAYETTE,IN 47907
Performing Department
Agricultural Economics
Non Technical Summary
Digital agriculture can address long standing challenges faced by participants throughout the industry. Impacts, however, will flow beyond agriculture to adjacent sectors, consumers, and society as a whole. Producers will be equipped with objective research to make better investment decisions. As the number of digital farm management platforms grows, producers will increasingly demand unbiased sources of information. Practices that do not improve profitability or generate off-farm benefits will be discouraged while beneficial solutions will be uncovered. The project will also help producers gain efficiencies through optimal use of digital agriculture. The conditions and practices under which activities such as variable rate application or UAV scouting improve profitability will be better understood. The promise of precision agriculture as a means of mitigating environmental damages has not been fully explored. Precision fertilizer application could reduce nutrient leaching and runoff, a major source of water pollution. Research performed in this area will inform on-farm practices, policy recommendations, and incentive programs that benefit downstream users and reward producers. Digital agriculture may help reverse the "brain drain" from rural farming communities to urban centers. As digital farming raises the demand for specialized labor, young people with technical skills will face higher opportunity costs of leaving agriculture. This trend, along with the expansion of internet access, could help revitalize rural communities. Research driven insights can help aid this process.Domestically, blockchain technology will be transformational in two agricultural areas: supply chain management and food traceability. Blockchain links chunks of data together in "blocks" that, once added to the "chain," cannot be altered, thereby ensuring security and reducing counterparty risk. The need for third party authentication is eliminated by requiring approval from participants in the blockchain before new blocks can be added. The world's first blockchain based agricultural trade place in January of 2018. A shipment of U.S. soybeans to China was handled entirely by a blockchain platform that cut the transaction time in half. More promising are "smart contracts" which automatically execute pre-agreed upon terms (e.g. payment for grain delivered to an elevator) in real time when the conditions of the agreement are authenticated in the blockchain.Blockchain will also dramatically improve food safety and traceability. Products passing through the supply chain are tracked and verified at each step from producer to processor to consumer, ensuring compliance. Walmart, in partnership with IBM, trialed a blockchain tracking system for sliced mangos that cut the amount of time required to trace the product back to its source from one week to 2.2 seconds. Blockchain may also diminish food fraud. In October of 2018, three Nebraska corn and soybean growers were charged with selling conventionally grown crops as certified organic for a period of seven years, pocketing close to $11 million. Combining blockchain technology with on-farm data can prevent such cases where conventional certification is inadequate. While blockchain and smart contracts present unique opportunities, enthusiasm from industry and media may overstate their impact on agriculture. The project will ground this enthusiasm in unbiased research.
Animal Health Component
100%
Research Effort Categories
Basic
(N/A)
Applied
100%
Developmental
(N/A)
Goals / Objectives
The overarching goal of this project is to understand the economic implications of emergent digital technologies in agriculture with an emphasis on the collection and analysis of agricultural data. Five specific objectives are to be addressed:Estimate the costs and benefits to producers of adopting various digital agriculture technologies and identify the practices necessary for profitable implementation. Cost-benefit analyses will help guide farmers' investment decisions.Discover how distributed ledger technology (i.e., blockchain and smart contracts) can be leveraged to improve traceability, ensure food safety, demonstrate sustainability, and reduce transactions costs across the supply chain.Investigate how precision technologies and data analytics can improve environmental and sustainability metrics and internalize environmental externalities.Explore solutions to data privacy concerns that incentivize data sharing while ensuring privacy and creating value for producers.
Project Methods
This project will make use of methods that span existing economic analysis tools used to measure value, estimate relationships among variables, and identify causal effects. The specific methods employed will vary by objective. As a first approximation of the extent of digital agriculture's current reach, the project will rely heavily on primary data collection, i.e. surveys and field experiments. The basic characterization of the digital agriculture marketplace represents the "low hanging fruit" of this project and is best achieved using survey methods. Both the Center for Food and Agricultural Business (CAB) and the Center for Commercial Agriculture (CCA) possess survey tools and, most importantly, lists of targeted survey audiences which the project will leverage. Institutional Review Board exempt status approval will be obtained before conducting the surveys. The project will also seek grants and other external funding sources which will facilitate the collection of primary field data. The project director applied as a co-PI for a NSF/NIFA Innovations at the Nexus of Food, Energy and Water Systems (INFEWS) grant and a USDA NIFA Food and Agriculture Cyberinformatics and Tools Initiative (FACT) grant in the fall of 2018 with collaborators from multiple disciplines and universities. Though the grants address separate issues, INFEWS will research the potential for precision technologies to reduce water use in fruit and tree nut production while FACT will focus on using field data to improve nutrient recommendations, they will both, if funded, generate substantial primary data for analysis.To estimate the economic viability of digital agriculture technologies, standard methods of cost-benefit analysis will be used. Cost-benefit analysis calculates the discounted net present value of future payoffs and can be used to determine the lifetime profitability of a technology investment. New techniques that incorporate uncertainty in yield, prices, input supplies, etc. into traditional cost-benefit analysis such as option value theory and Monte Carlo simulation provide realistic modelling scenarios (Carey and Zilberman, 2002). Where possible, the project will conduct randomized control trials (RCT) where adoption of a technology and non-adoption are randomly assigned to farmer participants or to specific fields within a farmer's land holdings. RCTs are the best method for identifying causal treatment effects, conditional on observable factors. Once estimated, treatment effects can then be plugged in to other analyses tools such partial budgets and cost-benefit. To estimate optimal implementation of investments such as variable rate technology (VRT) or drones, the project will analyze spatial data using GIS software. Datasets will include field and sub-field level information on farm management practices (chemical application rates, irrigation, soil sampling densities, etc.), agro-climatic conditions (soil characteristics, precipitation, temperature, etc.), and output measures (crop yield, soil erosion, carbon sequestration, etc.). Data will be analyzed using both spatial and time-series econometric tools where available. Spatial econometrics captures neighborhood effects that exist among variables observed in space while time-series econometrics capture temporal relationships among longitudinal variables. Both tools are useful for evaluating optimal use of precision agriculture techniques. Various econometric techniques will be used to estimate the impact of blockchain and its derivative, "smart contracts" (protocols that automatically execute when certain pre-defined conditions are satisfied within a blockchain) on the food system. These technologies change the trust dynamics among supply chain participants. Third parties required to solve information problems could be replaced by blockchain-based systems that ensure accountability. For producers, processors, and distributors, the impact of trust-enhancing technologies will be examined through their effects on delivery times, transactions costs, and vertical integration. Data may be observed at the firm or industry level. To estimate consumer responses to traceability, changes in demand and preferences for foodstuffs will be observed. Consumer data may include point-of-sale scanner data or surveys. The project will evaluate the potential for digital agriculture to improve environmental and sustainability outcomes that flow off-farm. The benefits and costs of these outcomes are often unrealized by the producers generating them. To understand how digital agriculture can help producers internalize these externalities, this project will rely on field experiments, observational data, and producer surveys and apply various statistical techniques to identify causal effects. The primary focus will be the effect of nutrient runoff (nitrogen (N), phosphorus (P), and potassium (K)) but will also consider localized environmental conflicts such as chemical drift (e.g., dicamba) across property lines. Data may be collected from drainage tile or in-field sensors measuring environmental conditions and related back to the use of precision application or digital solution designed to reduce damage using statistical techniques. Data issues will be analyzed through producer and agribusiness surveys that measure how data is used, perceptions of data security, and ways to incentivize data sharing. Data privacy is a major concern among producers. However, opportunities to create value through data collaboration exist. Growers willing to share farm management data demonstrating sustainable practices may enjoy higher prices or be eligible for more favorable marketing terms. The project will make use of both quantitative and qualitative analysis methods to discover these potential sources of value.