International Winter Wheat nurseries data: Facultative and Winter Wheat Observation Nurseries and International Winter Wheat yield trials for semi-arid and irrigated conditions

This data paper describes the content of 16 datasets collected under the International Winter Wheat Improvement Program (IWWIP), an alliance between Turkey-CIMMYT-ICARDA (TCI), during the 2015–2016, 2016–2017, 2017–2018 and 2018–2019 seasons. Data was collected from the Facultative and Winter Wheat Observation Nursery (FAWWON) and the International Winter Wheat Yield Trials (IWWYT) conducted under semi-arid and irrigated conditions across different countries. Data on all nurseries was collected during the growing season by IWWIP's team and cooperators in their local environments. It was compiled at the end of the wheat season by IWWIP's team. Multi-locational data can be used to select advanced lines that fit to collaborators’ growing environment. The selected germplasm can either be used as a parent in their breeding programs or be released as a variety in their country

Experimental on-farm trials data of faba bean and wheat intercropping field validation in Lebanon and Morocco

This data paper describes the content of four datasets col- lected by the International Center for Agricultural Research in the Dry Areas (ICARDA) as a partner in the project “Designing InnoVative plant teams for Ecosystem Resilience and agricultural Sustainability (DIVERSify)”with the objec- tive of assessing the feasibility of faba bean-wheat mix- ture in Mediterranean environments under diverse rainfed conditions. Data was collected during the trials conducted in Kfardan-Lebanon during 2017/2018 where 40 faba bean varieties were evaluated as sole and as mixture with 2 wheat cultivars ‘Margherita’ and ‘Miki’ and during 2018/2019 where 40 faba bean varieties and one durum wheat cultivar ‘Margherita’ were evaluated under low rainfall environments. Trials were also conducted in Tal Amara-Lebanon during 2019/2020 where 20 faba bean lines and one durum wheat cultivar ‘Margherita’ were evaluated under high rainfall en- vironments and in Marchouch-Morocco during 2019/2020 where 7 faba bean lines with 3 cultivars and one durum wheat cultivar ‘Margherita’ were evaluated under extremely low rainfall environments. A detailed list of the different bi- ological traits collected for wheat and faba bean is found in the specification table in this article. The Kfardan 2018/ 2019, Tal Amara and Marchouch data is related to the conference paper “Performance of faba bean-wheat mixture under di- verse Mediterranean environments”

Data on how tree planting and management practices influence tree seedling survival in Kenya and Ethiopia

Understanding which trees farmers prefer, what determines their survival and enhancing farmer knowledge of tree management is key to increasing tree cover in agricultural landscapes. This article presents data on tree seedling survival under different tree planting and management practices in Kenya and Ethiopia. Data were collected from 1600 households across three Counties in Kenya and 173 households across four Woredas in Ethiopia, using a structured questionnaire which was administered through the Open Data Kit. Data on seedling survival were collected at least six months after tree seedlings were planted. To understand how planting and management practices influence tree planting across the different socioeconomic and biophysical contexts, both household level and individual tree level data were collected. Household level data included socio-economic and biophysical characteristics of the households while tree specific data included when the tree seedling was planted, where it was planted, the management practices employed and whether surviving. The datasets described in this article help understand which options confer the best chance survival for the planted seedlings and in which socio-economic and biophysical contexts they are most successful. [Abstract copyright: © 2021 The Author(s). Published by Elsevier Inc.

Increasing interoperability between food and agricultural systems: CGIAR and FAO collaboration

It is crucial that data resources can talk to each other through thesaurus, ontologies and standards. Therfore, the integration of CGIAR controlled vocabularynto the AGROVOC thesaurus is key to interlink our data sets and publications in the food and agricultural domain and produce multilingual quality labeling. The Task Group and a curation team defined the added value for the CGIAR to formally contribute to AGROVOC, and how to organize CGIAR contribution in a coherent workflow. The recommendations are the following: 1. One CGIAR needs to strengthen its contribution to AGROVOC thus supporting the consolidation of the semantic landscape for labeling data in agriculture and food systems. 2.CGIAR centers should wait a bit till the affiliation process is complete so that the appropriate unit that will be responsible for AGROVOC can consume the Agreement since the timeline for the affiliation process is just some few months away. 3.OneCGIAR data managers will have to sustain the collaboration and submit terms to populate the ONECGIAR concepts schema newly created to provide direct visibility of the set of concepts (https://agrovoc.fao.org/skosmosOneCGIAR/cgiar/en/ ). Based on the collaboration concrete results, The TG recommends that the term submission effort and collaboration with FAO continues with proper allocation of data managers’ time and a training plan. Contribution to AGROVOC should be part of the data managers ToRs to concrete provide recognition of this role

Increasing interoperability between food and agricultural information systems: CGIAR and FAO collaboration

It is crucial that data resources can talk to each other through thesaurus, ontologies and standards. Therfore, the integration of CGIAR controlled vocabularynto the AGROVOC thesaurus is key to interlink our data sets and publications in the food and agricultural domain and produce multilingual quality labeling. The Task Group and a curation team defined the added value for the CGIAR to formally contribute to AGROVOC, and how to organize CGIAR contribution in a coherent workflow. The recommendations are the following: 1. One CGIAR needs to strengthen its contribution to AGROVOC thus supporting the consolidation of the semantic landscape for labeling data in agriculture and food systems. 2.CGIAR centers should wait a bit till the affiliation process is complete so that the appropriate unit that will be responsible for AGROVOC can consume the Agreement since the timeline for the affiliation process is just some few months away. 3.OneCGIAR data managers will have to sustain the collaboration and submit terms to populate the ONECGIAR concepts schema newly created to provide direct visibility of the set of concepts (https://agrovoc.fao.org/skosmosOneCGIAR/cgiar/en/ ). Based on the collaboration concrete results, The TG recommends that the term submission effort and collaboration with FAO continues with proper allocation of data managers’ time and a training plan. Contribution to AGROVOC should be part of the data managers ToRs to concrete provide recognition of this role