This dataset belongs to a framed economic field experiment conducted in 2016 in Bhilwara district in Rajasthan state in India. A public good game was framed as dam management challenge. We made incentivized payments based on the game earnings. The data are organized as a panel defined by players and experiment rounds. The dataset contains the experiment decisions in different phases of the experiment as well as socio-economic variables of the anonymized players. The data can be accessed through the Dataverse of the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) under the following link: https://doi.org/10.21421/D2/MFT8ZD. The data article is related to the research article Falk et al. [2] on “Experimental games for developing institutional capacity to manage common water infrastructure in India”.

This dataset belongs to a framed economic field experiment conducted in 2016 in Bhilwara district in Rajasthan state in India. A public good game was framed as dam management challenge. We made incentivized payments based on the game earnings. The data are organized as a panel defined by players and experiment rounds. The dataset contains the experiment decisions in different phases of the experiment as well as socio-economic variables of the anonymized players. The data can be accessed through the Dataverse of the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) under the following link: https://doi.org/10.21421/D2/MFT8ZD. The data article is related to the research article Falk et al. [2] on “Experimental games for developing institutional capacity to manage common water infrastructure in India”.

The data presented in this article contains information on 189 rice breeders from 51 rice-growing countries around the world. Firstly, this unique dataset permits to lay down a baseline of currently used breeding methods. Secondly, the data allow to make an assessment of the adoption behavior of rice breeders towards alternative breeding methods, and in specific rapid generation advance. A global online survey in Google Forms was conducted to obtain information about different aspect of the adoption process. Both the raw and cleaned data are made available, along with Stata code to promote further research into adoption of breeding methods by public and private breeding institutes.

The data presented in this article contains information on 189 rice breeders from 51 rice-growing countries around the world. Firstly, this unique dataset permits to lay down a baseline of currently used breeding methods. Secondly, the data allow to make an assessment of the adoption behavior of rice breeders towards alternative breeding methods, and in specific rapid generation advance. A global online survey in Google Forms was conducted to obtain information about the different aspects of the adoption process. Both the raw and cleaned data are made available, along with Stata code to promote further research into adoption of breeding methods by public and private breeding institutes.

This data article provides the datasets that are used in the holistic ex-ante impact evaluation of an irrigation dam construction project in Northern Ethiopia [1]. We used an expert knowledge elicitation approach as a means of acquiring the data. The data shared here captures all the parameters considered important in the impact pathway (i.e. the expected benefits, costs, and risks) of the decision to construct an irrigation dam. The dataset is disaggregated for two impact pathway models: one complementing the dam construction with catchment restoration and the other without catchment restoration. Both models are scripted in the R programming language. The data can be used to examine how the construction of an irrigation dam affects the incomes as well as the food and nutritional status of farmers that are affected by the intervention.

This data article provides the datasets that are used in the holistic ex-ante impact evaluation of an irrigation dam construction project in Northern Ethiopia [1]. We used an expert knowledge elicitation approach as a means of acquiring the data. The data shared here captures all the parameters considered important in the impact pathway (i.e. the expected benefits, costs, and risks) of the decision to construct an irrigation dam. The dataset is disaggregated for two impact pathway models: one complementing the dam construction with catchment restoration and the other without catchment restoration. Both models are scripted in the R programming language. The data can be used to examine how the construction of an irrigation dam affects the incomes as well as the food and nutritional status of farmers that are affected by the intervention.

This data article provides the datasets that are used in the holistic ex-ante impact evaluation of an irrigation dam construction project in Northern Ethiopia [1]. We used an expert knowledge elicitation approach as a means of acquiring the data. The data shared here captures all the parameters considered important in the impact pathway (i.e. the expected benefits, costs, and risks) of the decision to construct an irrigation dam. The dataset is disaggregated for two impact pathway models: one complementing the dam construction with catchment restoration and the other without catchment restoration. Both models are scripted in the R programming language. The data can be used to examine how the construction of an irrigation dam affects the incomes as well as the food and nutritional status of farmers that are affected by the intervention.

The dataset described in this data article represents four agricultural zones in West-Africa that are located in three countries: Benin, Mali and Sierra Leone. The dataset was created through a research collaboration between the Africa Rice Center (AfricaRice), Sierra Leone Agricultural Research Institute (SLARI) and the Institute for Rural Economy (IER). The dataset was compiled to investigate the potential for rice production in inland valleys of the three countries. The results of the investigation were published in Dossou-Yovo et al. (2017) and Djagba et al. (2018). The dataset describes the biophysical and socioeconomic conditions of 499 inland valleys in the four agricultural zones. In each inland valley data were collected through a focus group interview with a minimum of three farmers. In 499 interviews a total of 7496 farmers participated. The location of each inland valley was determined with handheld GPS devices. The geographic locations were used to extract additional parameters from digital maps on soils, elevation, population density, rainfall, flow accumulation, and distances to roads, market places, rice mills, chemical input stores, and settlements. The dataset contains 65 parameters in four themes (location, biophysical characteristics, socioeconomic characteristics, and inland valley land development and use). The GPS coordinates indicate the location of an inland valley, but they do not lead to the location of individual fields of farmers that were interviewed. The dataset is publicly shared as Supplementary data to this data article.

The dataset described in this data article represents four agricultural zones in West-Africa that are located in three countries: Benin, Mali and Sierra Leone. The dataset was created through a research collaboration between the Africa Rice Center (AfricaRice), Sierra Leone Agricultural Research Institute (SLARI) and the Institute for Rural Economy (IER). The dataset was compiled to investigate the potential for rice production in inland valleys of the three countries. The results of the investigation were published in Dossou-Yovo et al. (2017) and Djagba et al. (2018). The dataset describes the biophysical and socioeconomic conditions of 499 inland valleys in the four agricultural zones. In each inland valley data were collected through a focus group interview with a minimum of three farmers. In 499 interviews a total of 7496 farmers participated. The location of each inland valley was determined with handheld GPS devices. The geographic locations were used to extract additional parameters from digital maps on soils, elevation, population density, rainfall, flow accumulation, and distances to roads, market places, rice mills, chemical input stores, and settlements. The dataset contains 65 parameters in four themes (location, biophysical characteristics, socioeconomic characteristics, and inland valley land development and use). The GPS coordinates indicate the location of an inland valley, but they do not lead to the location of individual fields of farmers that were interviewed. The dataset is publicly shared as Supplementary data to this data article.

Food insecurity or insufficiency, among other factors, is triggered by structural inequalities. Food insecurity is an inflexible problematic situation in South Africa. The country has a custom of evidence-based decision making, stocked in the findings of generalized national household surveys. Conversely, the deep insights from the heterogeneity of the sub-national analysis remain a principally unexploited means of understanding of the contextual experience of food insecurity or insufficiency in South Africa. The data present the food insufficiency status with special focus on adult and children. The data also reveal the adult and children food insufficiency status across the provinces in South Africa. The data contains socioeconomic and demographic characteristics as well the living condition and food security status of the households.

Food insecurity or insufficiency, among other factors, is triggered by structural inequalities. Food insecurity is an inflexible problematic situation in South Africa. The country has a custom of evidence-based decision making, stocked in the findings of generalized national household surveys. Conversely, the deep insights from the heterogeneity of the sub-national analysis remain a principally unexploited means of understanding of the contextual experience of food insecurity or insufficiency in South Africa. The data present the food insufficiency status with special focus on adult and children. The data also reveal the adult and children food insufficiency status across the provinces in South Africa. The data contains socioeconomic and demographic characteristics as well the living condition and food security status of the households. | PR | IFPRI3; 1 Fostering Climate-Resilient and Sustainable Food Supply | DSGD

Food insecurity or insufficiency, among other factors, is triggered by structural inequalities. Food insecurity is an inflexible problematic situation in South Africa. The country has a custom of evidence-based decision making, stocked in the findings of generalized national household surveys. Conversely, the deep insights from the heterogeneity of the sub-national analysis remain a principally unexploited means of understanding of the contextual experience of food insecurity or insufficiency in South Africa. The data present the food insufficiency status with special focus on adult and children. The data also reveal the adult and children food insufficiency status across the provinces in South Africa. The data contains socioeconomic and demographic characteristics as well the living condition and food security status of the households.

Food insecurity or insufficiency, among other factors, is triggered by structural inequalities. Food insecurity is an inflexible problematic situation in South Africa. The country has a custom of evidence-based decision making, stocked in the findings of generalized national household surveys. Conversely, the deep insights from the heterogeneity of the sub-national analysis remain a principally unexploited means of understanding of the contextual experience of food insecurity or insufficiency in South Africa. The data present the food insufficiency status with special focus on adult and children. The data also reveal the adult and children food insufficiency status across the provinces in South Africa. The data contains socioeconomic and demographic characteristics as well the living condition and food security status of the households.

This paper presents data collected in 2013, 2014 and 2015 on the cultural practices and agronomic performance of cropping systems in 500 lowland rice fields located in five regions of three West African countries, Benin, Mali and Sierra Leone. Data were collected in two stages. In the first stage, the main regions containing inland valleys were identified in each of the three countries and the most cultivated inland valley in each region was selected. Weather data were obtained from weather stations located close to the selected inland valleys. In regions with no weather stations, Tinytag data loggers were installed in the inland valleys to collect data on temperature, rainfall and relative humidity. In the second stage, the location and size of all the farmers' fields in each inland valley were determined using GPS devices. In 2013, soil samples were collected in each farmer's field and the soil physical-chemical properties were determined. Agronomic and socio-economic surveys were conducted to collect data on cultivated crops, crop sequences and management techniques using questionnaires and informal interviews. Crop yields were determined in each farmer's field in the growing season. The database contains a total of 131 variables divided into 9 themes: field characteristics, land preparation, field maintenance, irrigation, residue management, soil data, weather data, crop productions in the dry season and crop production in the rainy season.

This paper presents data collected in 2013, 2014 and 2015 on the cultural practices and agronomic performance of cropping systems in 500 lowland rice fields located in five regions of three West African countries, Benin, Mali and Sierra Leone. Data were collected in two stages. In the first stage, the main regions containing inland valleys were identified in each of the three countries and the most cultivated inland valley in each region was selected. Weather data were obtained from weather stations located close to the selected inland valleys. In regions with no weather stations, Tinytag data loggers were installed in the inland valleys to collect data on temperature, rainfall and relative humidity. In the second stage, the location and size of all the farmers' fields in each inland valley were determined using GPS devices. In 2013, soil samples were collected in each farmer's field and the soil physical-chemical properties were determined. Agronomic and socio-economic surveys were conducted to collect data on cultivated crops, crop sequences and management techniques using questionnaires and informal interviews. Crop yields were determined in each farmer's field in the growing season. The database contains a total of 131 variables divided into 9 themes: field characteristics, land preparation, field maintenance, irrigation, residue management, soil data, weather data, crop productions in the dry season and crop production in the rainy season.

peer reviewed | This paper presents data collected in 2013, 2014 and 2015 on the cultural practices and agronomic performance of cropping systems in 500 lowland rice fields located in five regions of three West African countries, Benin, Mali and Sierra Leone. Data were collected in two stages. In the first stage, the main regions containing inland valleys were identified in each of the three countries and the most cultivated inland valley in each region was selected. Weather data were obtained from weather stations located close to the selected inland valleys. In regions with no weather stations, Tinytag data loggers were installed in the inland valleys to collect data on temperature, rainfall and relative humidity. In the second stage, the location and size of all the farmers’ fields in each inland valley were determined using GPS devices. In 2013, soil samples were collected in each farmer's field and the soil physical-chemical properties were determined. Agronomic and socio-economic surveys were conducted to collect data on cultivated crops, crop sequences and management techniques using questionnaires and informal interviews. Crop yields were determined in each farmer's field in the growing season. The database contains a total of 131 variables divided into 9 themes: field characteristics, land preparation, field maintenance, irrigation, residue management, soil data, weather data, crop productions in the dry season and crop production in the rainy season. © 2019 The Author(s)

publishedVersion | The gonadotropins follicle-stimulating hormone (Fsh) and luteinizing hormone (Lh) play essential roles in vertebrate reproduction. This article presents data on molecular weight validation of recombinant medaka (Oryzias latipes) (md) gonadotropins Fshβ (mdFshβ), Lhβ (mdLhβ), Fshβα (mdFshβα), and Lhβα (mdLhβα) generated by Pichia pastoris, as well as data on a validation of produced antibodies against Fshβ and Lhβ by Western blot analysis. Furthermore, the article includes data on Fsh and Lh protein levels in male medaka pituitaries using recombinant mdFshβα and mdLhβα within enzyme-linked immunosorbent assays (ELISAs), in which protein amounts were analyzed related to body weight and age of the fish. This dataset is associated with the research article entitled “Medaka Follicle-stimulating hormone (Fsh) and Luteinizing hormone (Lh): Developmental profiles of pituitary protein and gene expression” (Burow et al., in press).

The gonadotropins follicle-stimulating hormone (Fsh) and luteinizing hormone (Lh) play essential roles in vertebrate reproduction. This article presents data on molecular weight validation of recombinant medaka (Oryzias latipes) (md) gonadotropins Fshβ (mdFshβ), Lhβ (mdLhβ), Fshβα (mdFshβα), and Lhβα (mdLhβα) generated by Pichia pastoris, as well as data on a validation of produced antibodies against Fshβ and Lhβ by Western blot analysis. Furthermore, the article includes data on Fsh and Lh protein levels in male medaka pituitaries using recombinant mdFshβα and mdLhβα within enzyme-linked immunosorbent assays (ELISAs), in which protein amounts were analyzed related to body weight and age of the fish. This dataset is associated with the research article entitled “Medaka Follicle-stimulating hormone (Fsh) and Luteinizing hormone (Lh): Developmental profiles of pituitary protein and gene expression” (Burow et al., in press).

International audience | The data presented here was obtained during a decade-long macromycete inventory on the island of Cyprus and is supplementary to the research article "Present status and future of boletoid fungi (Boletaceae) on the island of Cyprus: cryptic and threatened diversity unravelled by ten-year study” [1]. A new, rainfall-based sampling protocol for documenting fungal diversity in Mediterranean ecosystems, is described in detail.

The data presented here was obtained during a decade-long macromycete inventory on the island of Cyprus and is supplementary to the research article “Present status and future of boletoid fungi (Boletaceae) on the island of Cyprus: cryptic and threatened diversity unravelled by ten-year study” [1]. A new, rainfall-based sampling protocol for documenting fungal diversity in Mediterranean ecosystems, is described in detail.