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Crop wild relatives have a long history of use in potato breeding, particularly for pest and disease resistance, and are expected to be increasingly used in the search for tolerance to biotic and abiotic stresses. Their current and future use in crop improvement depends on their availability in ex situ germplasm collections. As these plants are impacted in the wild by habitat destruction and climate change, actions to ensure their conservation ex situ become ever more urgent. We analyzed the state of ex situ conservation of 73 of the closest wild relatives of potato (Solanum section Petota) with the aim of establishing priorities for further collecting to fill important gaps in germplasm collections. A total of 32 species (43.8%), were assigned high priority for further collecting due to severe gaps in their ex situ collections. Such gaps are most pronounced in the geographic center of diversity of the wild relatives in Peru. A total of 20 and 18 species were assessed as medium and low priority for further collecting, respectively, with only three species determined to be sufficiently represented currently. Priorities for further collecting include: (i) species completely lacking representation in germplasm collections; (ii) other high priority taxa, with geographic emphasis on the center of species diversity; (iii) medium priority species. Such collecting efforts combined with further emphasis on improving ex situ conservation technologies and methods, performing genotypic and phenotypic characterization of wild relative diversity, monitoring wild populations in situ, and making conserved wild relatives and their associated data accessible to the global research community, represent key steps in ensuring the long-term availability of the wild genetic resources of this important crop.

Summary Heterogeneous and multidisciplinary data generated by research on sustainable global agriculture and agrifood systems requires quality data labeling or annotation in order to be interoperable. As recommended by the FAIR principles, data, labels, and metadata must use controlled vocabularies and ontologies that are popular in the knowledge domain and commonly used by the community. Despite the existence of robust ontologies in the Life Sciences, there is currently no comprehensive full set of ontologies recommended for data annotation across agricultural research disciplines. In this paper, we discuss the added value of the Ontologies Community of Practice (CoP) of the CGIAR Platform for Big Data in Agriculture for harnessing relevant expertise in ontology development and identifying innovative solutions that support quality data annotation. The Ontologies CoP stimulates knowledge sharing among stakeholders, such as researchers, data managers, domain experts, experts in ontology design, and platform development teams.

Crop wild relatives of sweetpotato [Ipomoea batatas (L.) Lam., I. series Batatas] have the potential to contribute to breeding objectives for this important root crop. Uncertainty in regard to species boundaries and their phylogenetic relationships, the limited availability of germplasm with which to perform crosses, and the difficulty of introgression of genes from wild species has constrained their utilization. Here, we compile geographic occurrence data on relevant sweetpotato wild relatives and produce potential distribution models for the species. We then assess the comprehensiveness of ex situ germplasm collections, contextualize these results with research and breeding priorities, and use ecogeographic information to identify species with the potential to contribute desirable agronomic traits. The fourteen species that are considered the closest wild relatives of sweetpotato generally occur from the central United States to Argentina, with richness concentrated in Mesoamerica and in the extreme Southeastern United States. Currently designated species differ among themselves and in comparison to the crop in their adaptations to temperature, precipitation, and edaphic characteristics and most species also show considerable intraspecific variation. With 79% of species identified as high priority for further collecting, we find that these crop genetic resources are highly under-represented in ex situ conservation systems and thus their availability to breeders and researchers is inadequate. We prioritize taxa and specific geographic locations for further collecting in order to improve the completeness of germplasm collections. In concert with enhanced conservation of sweetpotato wild relatives, further taxonomic research, characterization and evaluation of germplasm, and improving the techniques to overcome barriers to introgression with wild species are needed in order to mobilize these genetic resources for crop breeding.

This chapter describes the application of ILCYM (Insect Life Cycle Modelling) software, which supports the development of process-oriented temperature-driven and age-stage structured insect phenology/population models. ILCYM interactively leads the user through the steps for developing insect phenology models, for conducting simulations, and for producing potential population distribution and risk mapping under current or future temperature (climate change) scenarios. The phenology model developed for the potato tuber moth Phthorimaea operculella (Lepidoptera: Gelechiidae) is used to demonstrate the resulting modelling outputs.

Insect Life Cycle Modelling (ILCYM) software is an open-source computer-aided tool built on R and Java codes and linked to the uDig platform, which is a basic geographic information system (GIS). The software package consists of three modules: (i) the 'model builder'; (ii) the 'validation and simulations'; and (iii) the 'potential population distribution and risk mapping' module. ILCYM's model builder contains a library of several empirical linear and non-linear models, including the derivations of biophysical models, which have been proposed to define critical temperature effects in insects' development. Several statistical measures are incorporated in this module for estimation of parameters and comparison of models. The validation and simulations module demonstrates the application of the phenology models for estimating and simulating insect population abundance under constant and fluctuating temperatures. Outputs of the simulations are demographic parameters that include: (i) net reproduction rate; (ii) mean generation time; (iii) intrinsic rate of increase; (iv) finite rate of increase; and (v) the doubling time. Through these analyses, the biology and temperature requirements of insects are defined, and the effects of different diets or host plants in insects' demographic are assessed. The ILCYM-GIS component estimates three indices (the establishment risk index (EI), the generation index (GI) and the activity index (AI)) that guide in assessing the potential population distribution and abundance of a particular species. Several functionalities for vector (dbf to shape, raster to points, raster to polygons, extract by points) and raster analysis (merge, cut, mask, aggregate/disaggregate, re-class, describe, raster calculator) are part of the ILCYM-GIS component. Such features improve the manipulation of large datasets and help ILCYM's users in analysing and visualizing the risk assessment maps. The phenology model developed for the potato tuber moth Phthorimaea operculella (Zeller) (Lepidoptera: Gelechiidae) a worldwide pest of potato (Solanum tuberosum L.) is used to demonstrate resulting modelling outputs.

BackgroundPredicting anopheles vectors’ population densities and boundary shifts is crucial in preparing for malaria risks and unanticipated outbreaks. Although shifts in the distribution and boundaries of the major malaria vectors (Anopheles gambiae s.s. and An. arabiensis) across Africa have been predicted, quantified areas of absolute change in zone of suitability for their survival have not been defined. In this study, we have quantified areas of absolute change conducive for the establishment and survival of these vectors, per African country, under two climate change scenarios and based on our findings, highlight practical measures for effective malaria control in the face of changing climatic patterns.MethodsWe developed a model using CLIMEX simulation platform to estimate the potential geographical distribution and seasonal abundance of these malaria vectors in relation to climatic factors (temperature, rainfall and relative humidity). The model yielded an eco-climatic index (EI) describing the total favourable geographical locations for the species. The EI values were classified and exported to a GIS package. Using ArcGIS, the EI shape points were clipped to the extent of Africa and then converted to a raster layer using Inverse Distance Weighted (IDW) interpolation method. Generated maps were then transformed into polygon-based geo-referenced data set and their areas computed and expressed in square kilometers (km2).ResultsFive classes of EI were derived indicating the level of survivorship of these malaria vectors. The proportion of areas increasing or decreasing in level of survival of these malaria vectors will be more pronounced in eastern and southern African countries than those in western Africa. Angola, Ethiopia, Kenya, Mozambique, Tanzania, South Africa and Zambia appear most likely to be affected in terms of absolute change of malaria vectors suitability zones under the selected climate change scenarios.ConclusionThe potential shifts of these malaria vectors have implications for human exposure to malaria, as recrudescence of the disease is likely to be recorded in several new areas and regions. Therefore, the need to develop, compile and share malaria preventive measures, which can be adapted to different climatic scenarios, remains crucial.

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