Source: UNIVERSITY OF NEW HAMPSHIRE submitted to NRP
HARNESSING CHEMICAL ECOLOGY TO ADDRESS AGRICULTURAL PEST AND POLLINATOR PRIORITIES
Sponsoring Institution
National Institute of Food and Agriculture
Project Status
COMPLETE
Funding Source
Reporting Frequency
Annual
Accession No.
1013736
Grant No.
(N/A)
Cumulative Award Amt.
(N/A)
Proposal No.
(N/A)
Multistate No.
NE-1501
Project Start Date
Oct 1, 2017
Project End Date
Sep 30, 2020
Grant Year
(N/A)
Program Code
[(N/A)]- (N/A)
Recipient Organization
UNIVERSITY OF NEW HAMPSHIRE
51 COLLEGE RD SERVICE BLDG 107
DURHAM,NH 03824
Performing Department
Natural Resources and the Environment
Non Technical Summary
Apple is the major fruit crop in New Hampshire with 1,400 to 1,600 acres harvested on 146 farms, and a farm gate value fluctuating between $7 and 10 million (USDA 2015). Fruit pests and diseases have the potential to cause significant economic losses in apple production. There are currently no commercial varieties that are resistant to insect pests, which are increasingly problematic for Northeast growers. This project will assess the economic value of apple pest resistance through the intercropping of domesticated and heirloom/cider varieties that vary in their susceptibility but also in their market values. We will use farm production cost surveys, a three-year survey, econometric analyses, and computational modeling to (1) estimate apple production costs; (2) assess whether agrobiodiversity reduces pest risk; (3) recommend apple variety mixes and orchard designs that minimize pest infestations while maximizing profits. As a result of this project, we anticipate producing knowledge that reduces farm pesticide use and the associated financial (input costs) and environmental (pollinators) costs, while maximizing apple farm profits.
Animal Health Component
25%
Research Effort Categories
Basic
75%
Applied
25%
Developmental
0%
Classification

Knowledge Area (KA)Subject of Investigation (SOI)Field of Science (FOS)Percent
2161110208050%
6051110301050%
Goals / Objectives
Develop chemical ecology tools and information to support sustainable agriculture by reducing damage by pests in crops such as potatoes, brassicas, cucurbits, apples, blueberries, and sweet corn, while maintaining pollinator health in agricultural systems.
Project Methods
1 Apples enterprise budgetsWe will first develop enterprise budgets (i.e., production cost studies) for apple orchards in New Hampshire. These are a listing of all inputs and associated costs involved in apple production, including fixed and variable costs. These costs, combined with merchantable yield and price scenarios, indicate combinations of yields and prices where a farmer breaks even (see Atallah and Gómez 2013). We will develop these budgets by conducting a literature review of apple enterprise budgets for regions with comparable production systems (scale of production, varieties, etc.) (e.g., VirginiaTech hard cider apple enterprise budget, Farris, Peck, and Groover 2013). We will then hold focus group meetings with New Hampshire apple farmers to modify these enterprise budgets and adapt them to the representative farms in the state.2 Econometric evidence of the impact of agrobiodiversity of yields and production risk.Focus groups. The focus group interviews aim to understand adoptability, which is instrumental to determining the feasibility of a resilient ecological system from the human perspective. Focus group interviews are well suited for revealing the words, concepts, and activities of participants as they relate to complex concepts, such as technology adoption and ecosystem services. We will collect data on growers' awareness and perceptions of the pest control services that can be provided by agrobiodiversity, as well as on the perceptions and desirability of different agrobiodiversity-enhancing systems. We propose to organize several focus groups of six to eight participants each for the different typologies of apple growers. A trained moderator will conduct the focus group interviews using a specially designed script to give every participant the opportunity to share insights and perceptions (Krueger 1994). We will audiotape the sessions and transcribe them to allow for systematic analysis. We will verify the intent of participant comments by a post-focus-group review of the transcripts and audiotape. We will use Atlas software to analyze the group interview data using iterative coding, content analysis (Krippendorff 1980), and thematic matrices. The analysis will enable us to consider the words, context, internal consistency, frequency, and extensiveness (Krueger 1998). In addition, the focus groups will also generate important background data for designing the farmer survey and provide a convenient setting to conduct economic experiments with participants as well as meet the requirements of a field experiment (Harrison and List, 2004). The second half of each focus group session will be devoted to experimental auctions (bidding games) to assess landowners' willingness to accept compensation for adopting multi-variety cropping systems. Uniform price and discriminative price auctions will be tested for their efficiency and suitability to the task of eliciting incentive-compatible bids.Grower survey. Given that growers would directly experience changes in the costs and benefits of agrobiodiversity, the contingent valuation (CV) method is most appropriate as it is capable of capturing passive-use values (Freeman, 2003). The first stage of the econometric model, the adoption decision, will be estimated using a probit regression. The second stage, the quantity decision, will be estimated using a truncated regression (tobit). From this second stage, we will estimate a grower's land allocation (i.e., the area) to an agrobiodiversity production system regime (i.e., cider varieties). A multi-attribute choice framework will be used in order to permit estimation of the marginal willingness to accept compensation for alternative agrobiodiversity production system regimes. We will follow UNH Institutional Review Board guidelines to ensure anonymity. Standard mail survey procedures will follow pre-testing the survey instrument. We will make repeated follow-up contacts to ensure a high response rate (Dillman, 2000). In addition to the CV experiment, the survey will collect data on yields, the number of on-farm apple varieties, distance to and composition of neighboring abandoned apple farms, pest incidence, pesticide use, and fertilizer use per acre. We will use this additional data to estimate the marginal productivity of agrobiodiversity, pesticide use, and fertilizer use or each of the mean, variance, and skewness of apple yields (Di Falco and Chavas (2006).3 Bioeconomics of agrobiodiversity and apple pest resilienceWe propose to follow Atallah et al. (2015) to develop a tree-level, bio-economic simulation model of codling moth (or plum curculio, depending on data availability) infestation in an apple orchard block composed of multiple tree varieties (including yield-maximizing domesticated varieties and pest-resistant non-commercial varieties). The model is stochastic due to the random nature of pest initialization and dispersal, and spatially-explicit due to the critical role of spatial mixing patterns of apple varieties on orchard block-level invasion, opportunity costs (forgone yields or price premium), pest damages, and net revenues. We plan to parameterize the model using estimates from experimental trials in apple orchards in New York and in the NYSAES, estimates from the enterprise budgets (Objective 1), and estimates from the econometric analysis (Objective 3). We plan to conduct computational experiments manipulating the mix and configuration of apple tree varieties in the orchard block.

Progress 10/01/17 to 09/30/20

Outputs
Target Audience:A total of 9 students (3 undergraduates seniors, 3 MS, 3 PhD) received training in ecological-economic modeling (EREC 760/860 Ecological-economic Modeling for Decision Making) using a model developed under this project, namely Model 1 (A bioeconomic model of codling moth infestation dynamics in a multi-variety apple orchard). One PhD students received experience as a teaching assistant while using this model to develop modeling labs for this course. The students are from different backgrounds: resource economics, economics, environmental engineering, and natural resources. A total of 20 apple farmers attended a presentation titled "The economics of intercropping cider and commercial apple varieties for protection against pests" at the New Hampshire Farm, Forest, Garden Expo. Changes/Problems:Due to CODI-19 restrictions, we were not able to conduct farmer focus groups and surveys. We diverted our efforts planned for survey work to additional modeling work. What opportunities for training and professional development has the project provided?- One Ph.D. student gained experience in mechanistically modeling the spread and chemical control of three sweet corn pests in New Hampshire farms (the corn earworm (CEW), European corn borer (ECB), and fall armyworm (FAW) and the Bayesian modeling of one sweet corn pest in New York farms; - One Ph.D. student gained experience in modeling the spread and ecological control of an apple pest in New Hampshire apple orchards. -One Ph.D. student gained experience as a teaching assistant using a model developed under this project. How have the results been disseminated to communities of interest?A total of 20 apple farmers attended a presentation titled "The economics of intercropping cider and commercial apple varieties for protection against pests" at the 2020 New Hampshire Farm, Forest, Garden Expo. What do you plan to do during the next reporting period to accomplish the goals? Nothing Reported

Impacts
What was accomplished under these goals? Major goals of the project Develop chemical ecology tools and information to support sustainable agriculture by reducing damage by pests in crops such as potatoes, brassicas, cucurbits, apples, blueberries, and sweet corn, while maintaining pollinator health in agricultural systems What was accomplished under these goals? Apple is the major fruit crop in New Hampshire with 1,400 to 1,600 acres harvested on 146 farms, and a farm gate value fluctuating between $7 and 10 million (USDA 2015). Fruit pests and diseases have the potential to cause significant economic losses in apple production. There are currently no commercial varieties that are resistant to insect pests, which are increasingly problematic for Northeast growers. This project accessed the economic value of apple pest resistance through the intercropping of domesticated and heirloom/cider varieties that vary in their susceptibility but also in their market values. We used computational modeling to estimate production costs and potential profits of increasing levels of intercropping commercial varieties with heirloom varieties for increased resilience to pests. We incorporated feedback received from apple farmers to generate additional simulation results that they expressed interest in.

Publications


    Progress 10/01/18 to 09/30/19

    Outputs
    Target Audience:Research results were presented to professional audiences for scientific feedback. Changes/Problems:We did not conduct the survey with growers and will conduct it in the next cycle instead. Reason: The survey relies on some of the results from models 1 and 2 and needed to be moved until the models were presented for scientific feedback and refined accordingly. What opportunities for training and professional development has the project provided?Two graduate students gained experience in using a bioeconomic model as a data generation process for machine learning to findpest management solutions that have lower sensitivity to data uncertainty. One undergraduate student gained experience in online data collection. How have the results been disseminated to communities of interest?We have disseminated the results to three distinct communities of interest: graduate students (UNH Graduate Research Conference, Durham NH), agricultural economists (Northeastern Agricultural and Resource Economics meetings, Portsmouth NH), and computer scientists (Microsoft conference at McGill University in Montreal). What do you plan to do during the next reporting period to accomplish the goals?We plan to make improvements to Model 2 and submit a manuscript for peer review. We plan to use UNH Integrated Pest Management Data IPM data to build and calibrate a model of multi-pest management in sweet corn. We plan to design a choice experiment survey for growers to assess the adoptability of a pest management decision support system.

    Impacts
    What was accomplished under these goals? Apple is the major fruit crop in New Hampshire with 1,400 to 1,600 acres harvested on 146 farms, and a farm gate value fluctuating between $7 and 10 million (USDA 2015). Fruit pests and diseases have the potential to cause significant economic losses in apple production. There are currently no commercial varieties that are resistant to insect pests, which are increasingly problematic for Northeast growers. This project accessed the economic value of apple pest resistance through the intercropping of domesticated and heirloom/cider varieties that vary in their susceptibility but also in their market values.We used computational modeling toestimateproduction costs and potential profits applying different percentages and different spatial distributions forintercropping of cider apples with dessert apples to reduce insect pest risks. Model 1 is a model of an apple orchard under codling moth infestations. Given cider and commercial apple prices, production costs, and codling moth damage information, the modelsolves for the proportion of mixing commercial vs. cider apple trees that minimize infestations (through the natural defenses of cider varieties) while maximizing profits. This optimumis 20% cider variety and 80% commercial variety. However, this optimum changes as themarket price difference of the two apple varieties changes:the optimal proportion of cider decreases to zero when the price difference is greater than $0.3/lb. We consider eight different spatial configurations for the intercropping, in addition to the baseline random spatial intercropping and find that the diagonal configuration yields the highest profits and requires the lowest amount of cider intercropping (4%). Random spatial intercropping, in contrast, ranks seventh and has the second-highest optimal proportion of cider (30%). We find that the optimal mixing depends on how risk-averse a farmer is:the optimal cider variety percentage for a moderately risk-averse grower increases to 38% compared to the baseline case of 20% of a risk-neutral grower. We also document the risk-reducing effect of apple agrobiodiversity by characterizing how the risk premium decreases with increasing proportions of cider. In Model 2, we determine the threshold number of insects that should trigger sprays, given an infested multi-variety orchard consisting of the optimal proportion of cider varieties, arranged in a random spatial configuration. We use historical degree-day (DD) data and associated established DD threshold-based spray recommendations to add pesticide application features to our Model 1 and then use it as a simulator to generate data on infestation and damage level over time. We then use Reinforcement Learning (RL) to find the robust optimal pesticide application threshold. Here, the term robust refers to thresholds that are not too sensitive to data uncertainty. The model solution shows a greater degree of sensitivity to uncertainty in pesticidecosts compared to the uncertainty in the pest growth rate.

    Publications

    • Type: Theses/Dissertations Status: Published Year Published: 2019 Citation: Siddique, T. (2019). Agrobiodiversity for pest management: An integrated bioeconomic simulation and machine learning approach (Order No. 27668663). Available from Dissertations & Theses @ University of New Hampshire. (2353662085). Retrieved from https://unh.idm.oclc.org/login?url=https://search-proquest-com.unh.idm.oclc.org/docview/2353662085?accountid=14612
    • Type: Conference Papers and Presentations Status: Accepted Year Published: 2019 Citation: Talha Siddique; Jia Lin Hau; Marek Petrik; Shadi Atallah."Robust Pest Management Using Reinforcement Learning" RLDM 2019 The 4th Multidisciplinary Conference on Reinforcement Learning and Decision Making, July 7-10, 2019, McGill University, Montr�al, Qu�bec, CANADA http://rl2.cs.unh.edu/pub/Siddique2019.pdf
    • Type: Conference Papers and Presentations Status: Accepted Year Published: 2019 Citation: Talha Siddique, Shadi Atallah, Marek Petrik, Jia Hau, "Simulation-based Machine Learning Framework For Robust Optimization in Pest Management". Northeastern Agricultural and Resource Economics Association Meetings, Portsmouth NH, June 9  12, 2019.


    Progress 10/01/17 to 09/30/18

    Outputs
    Target Audience:A presentation on Agrobiodiversity as a pest control strategy: A bioeconomic model application to apples and codling moth was presented to theNortheast Agricultural and Resource Economics Association. Preliminary results for Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?The graduate student on the project gained training on bioeconomic modeling using the software AnyLogic and the language Java. How have the results been disseminated to communities of interest?FY 18 was the first year of this project.Modeling concepts were presented to professional audiences for feedback: Agrobiodiversityas a pest control strategy was presented to theNortheast Agricultural and Resource Economics Association in 2018. Preliminary results foroptimal farm spatial configurations for increased pest reliance in apple orchards were presented at the UNH Graduate Research Conference in 2018 What do you plan to do during the next reporting period to accomplish the goals?Objective 1. Apple enterprise budgets Send the enterprise budget for review by apple growers. Objective 2. Econometric analysis of New Hampshire apple farms Obtain Institutional Review Board approval and implement the survey of apple farmers to econometrically estimate farmers' willingness to adopt a decision support system (DSS) for apple production. Objective 3. Computational experimentation on the bio-economics of agrobiodiversity and apple pest resilience Use a simulation model as a data generation process to train a machine learning algorithm.

    Impacts
    What was accomplished under these goals? Apple is the major fruit crop in New Hampshire, Northeast, and the U.S. Fruit pests and diseases have the potential to cause significant economic losses in apple production and there are currently no commercial varieties that are resistant to insect pests, which are increasingly problematic for Northeast growers. Using chemical ecology principles can be used for the development of novel, cutting-edge and economically attractive approaches that will provide options and allow growers to integrate environmentally friendly, non-pesticidal control of various agricultural pests and improve management of pollinator services. Objective 1. Apple enterprise budgets We developed the first draft for a New Hampshire apple enterprise budget titled "Gala and cider apple production in New Hampshire: sample costs and profitability analysis." This enterprise budget offers a cost and revenue comparative analysis of growing Gala versus heirloom/cider apple. Objective 2. Econometric analysis of New Hampshire apple farms We developed a draft survey of apple farmers that will be deployed in 2019 to econometrically estimate farmers' willingness to adopt a decision support system (DSS) for apple production. Objective 3. Computational experimentation on the bio-economics of agrobiodiversity and apple pest resilience We created a computational model that can be used as DSS in apple pest management. The model uses chemical ecology of codling moth to recommend orchard optimal mix (commercial vs. heirloom apple varieties) and spatial designthat maximize an orchard's resilience to the pest in economically sound ways. CHANGE IN KNOWLEDGE: with increased pest pressure, it might make economic sense to intercrop commercial apples with more pest-resistant, less economically-attractive heirloom/cider varieties. The optimal mix depends on the price differential between the two crops and the pest pressure. In addition, there are spatially-optimal ways to intercrop the pest-resistant trees.

    Publications

    • Type: Conference Papers and Presentations Status: Accepted Year Published: 2018 Citation: Agrobiodiversity as a pest control strategy: A bioeconomic model application to apples and codling moth. NAREA Annual Meetings 2018, Philadelphia PA.
    • Type: Conference Papers and Presentations Status: Accepted Year Published: 2018 Citation: Optimal farm spatial configurations for increased pest reliance: a bio-economic application to apple orchards. UNH Graduate Research Conference, Durham NH.