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Policymakers and donors often need to identify the locations where technologies are most likely to have important effects, to increase the benefits from agricultural development or extension efforts. Higher-quality information may help to target the high-benefit locations, but often actions are needed with limited information. The value of information (VOI) in this context is formalized by evaluating the results of decision making guided by a set of specific information compared with the results of acting without considering that information. We present a framework for management performance mapping that includes evaluating the VOI for decision making about geographic priorities in regional intervention strategies, in case studies of Andean and Kenyan potato seed systems. We illustrate the use of recursive partitioning, XGBoost, and Bayesian network models to characterize the relationships among seed health and yield responses and environmental and management predictors used in studies of seed degeneration. These analyses address the expected performance of an intervention based on geographic predictor variables. In the Andean example, positive selection of seed from asymptomatic plants was more effective at high altitudes in Ecuador. In the Kenyan example, there was the potential to target locations with higher technology adoption rates and with higher potato cropland connectivity, i.e., a likely more important role in regional epidemics. Targeting training to high management performance areas would often provide more benefits than would random selection of target areas. We illustrate how assessing the VOI can contribute to targeted development programs and support a culture of continuous improvement for interventions.[Formula: see text] Copyright © 2022 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.

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Seed systems have an important role in the distribution of high-quality seed and improved varieties. The structure of seed networks also helps to determine the epidemiological risk for seedborne disease. We present a new approach for evaluating the epidemiological role of nodes in seed networks, and apply it to a regional potato farmer consortium (Consorcio de Productores de Papa [CONPAPA]) in Ecuador. We surveyed farmers to estimate the structure of networks of farmer seed tuber and ware potato transactions, and farmer information sources about pest and disease management. Then, we simulated pathogen spread through seed transaction networks to identify priority nodes for disease detection. The likelihood of pathogen establishment was weighted based on the quality or quantity of information sources about disease management. CONPAPA staff and facilities, a market, and certain farms are priorities for disease management interventions such as training, monitoring, and variety dissemination. Advice from agrochemical store staff was common but assessed as significantly less reliable. Farmer access to information (reported number and quality of sources) was similar for both genders. However, women had a smaller amount of the market share for seed tubers and ware potato. Understanding seed system networks provides input for scenario analyses to evaluate potential system improvements. [Formula: see text] Copyright © 2017 The Author(s). This is an open access article distributed under the CC BY 4.0 International license .

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The effects of host biodiversity on disease risk may vary greatly depending on host population structure and climatic conditions. Agricultural diseases such as potato late blight, caused by Phytophthora infestans, provide the opportunity to study the effects of intraspecific host diversity that is relatively well-defined in terms of disease resistance phenotypes and may have functional impacts on disease levels. When these systems are present across a climatic gradient, it is also possible to study how season length and conduciveness of the environment to disease may influence the effects of host diversity on disease risk. We developed a simple model of epidemic progress to evaluate the effects on disease risk of season length, environmental disease conduciveness, and host functional divergence for mixtures of a susceptible host and a host with some resistance. Differences in disease levels for the susceptible vs. resistant genotypes shifted over time, with the divergence in disease levels first increasing and then decreasing. Disease reductions from host diversity were greatest for high host divergence and combinations of environmental disease conduciveness and season length that led to moderate disease severity. We also compared the effects of host functional divergence on potato late-blight risk in Ecuador (long seasons), two sites in Peru (intermediate seasons) in El Niño and La Niña years, and the United States (short seasons). There was some evidence for greater disease risk reduction from host diversity where seasons were shorter, probably because of lower regional inoculum loads. There was strong evidence for greater disease reduction when host functional divergence was greater. These results indicate that consideration of season length, environmental conduciveness to disease, and host functional divergence can help to explain the variability in disease response to host diversity.

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Farmer field school programs incorporating farmer participatory research (FPR-FFS) have the potential to provide important benefits to their participants and to other farmers who benefit from improved cultivars and management techniques. An FPR-FFS program in San Miguel, Cajamarca, Peru, has been in place since 1999 with an emphasis on management of potato late blight, caused by Phytophthora infestans, the most important problem facing Andean potato growers. Farmers' knowledge of late blight was surveyed to determine useful components for the FPR-FFS curriculum. The benefits to participants of FPR-FFS programs were evaluated first by measuring knowledge of late blight management of participants and nonparticipants. Studies of the Peruvian FPR-FFS program indicate that participants are more knowledgeable and that their expertise further increases after an additional year of participation. The benefits to participants can be evaluated more directly by comparing the productivity of participants' farms compared with nonparticipants' farms. For the Peruvian FPR-FFS program, participants had significantly higher average levels of productivity. The benefits of FPR-FFS programs for the development of better cultivars and management techniques can be evaluated indirectly in terms of improved estimates of performance. Estimates of the overall performance of a particular cultivar or technique become more precise as data from more sites are included in calculating the estimate. A more direct evaluation of benefits from FPR-FFS input may be based on the ability of farmers in FPR-FFS programs to eliminate undesirable genotypes and to recommend desirable genotypes based on criteria in addition to those used by breeders.

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Genebank collection databases can be used for ecogeographical studies under the assumption that the accessions are a geographically unbiased sample. We evaluated the representativeness of a collection of wild potatoes from Bolivia and defined and assessed four types of bias: species, species-area, hotspot, and infrastructure. Species bias is the sampling of some species more often than others. Species-area bias is a sampling that is disproportionate to the total area in which a species is found. Hotspot bias is the disproportionate sampling of areas with high levels of diversity. Infrastructure bias is the disproportionate sampling of areas near roads and towns. Each of these biases is present in the Bolivian wild potato collection. The infrastructure bias was strong: 60% of all wild potato accessions were collected within 2 km of a road, as opposed to 22%, if collections had been made randomly. This analysis can serve as a guide for future collecting trips. It can also provide baseline information for the application of genebank data in studies based on geographic information systems.

RESUMEN: Las bases de datos de los bancos de germoplasma pueden ser usadas para estudios ecogeográficos bajo el supuesto que las entradas constituyen una muestra geográficamente imparcial. Evaluamos la representatividad geográfica de una colección de papas silvestres de Bolivia y definimos y evaluamos cuatro tipos de sesgos: sesgos de especie, de especie-área, de áreas con gran diversidad ( hotspot), y de infraestructura. El sesgo de especie implica el muestrear más algunas especies que otras. El sesgo de especie-área es un muestreo que es desproporcionado con respecto al total del área en la cual se encuentra una especie. El sesgo de "hotspot" es el muestreo desproporcionado de áreas con niveles altos de diversidad. El sesgo por infraestructura es aquel muestreo desproporcionado de áreas cercanas a carreteras y pueblos. Cada uno de estos sesgos se presenta en la colección de papas silvestres de Bolivia. El sesgo por infraestructura fue muy elevado: 60% de todas las entradas de papas silvestres fueron colectados dentro de un radio de 2 km de distancia de las carreteras, cuando se debería esperar un 22% si las colectas se hubieran hecho de manera aleatoria. Este análisis puede servir como guía para futuras exploraciones y proporciona una base para la aplicación de los datos de bancos de genes en estudios basados en sistemas de información geográfica.