Abstract
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.
Specifications Table
| Subject area | Agricultural Sciences, Social Sciences |
| More specific subject area | Food security, Agriculture |
| Type of data | Table (Excel format) |
| How the data were acquired | Face-to-face farmer surveys using questionnaires and informal interviews, geographic locations obtained with GPS devices, direct observations. |
| Data format | Raw, cleaned |
| Experimental factors | Not applicable |
| Experimental features | Not applicable |
| Data source location | The data were collected in 5 regions in 3 countries, see also Fig. 1. Benin, 2 regions 1. Mono 2. Couffo Mali, 1 region: 3. Sikasso Sierra Leone, 2 regions: 4. Bo 5. Kenema The geographic coordinates of each farmer's field are included in the data base. |
| Data accessibility | Data are provided with this article |
| Related research article | T. Furlan, R. Ballot, L. Guichard, J. Huat. Possible ex-ante assessment of rice-vegetable systems performances when facing data scarcity: use of the PERSYST model in West Africa. European Society for Agronomy. September 7th – September 10th, 2015, International Symposium for Farming Systems Design, 2015, Montpellier, France. |
Value of the data
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1. Data
The database contains the location, weather, soil, crop sequence, management techniques, and yield data on 500 lowland rice fields located in five regions of three West African countries: Benin (227 lowland rice fields), Mali (173) and Sierra Leone (100) (see Fig. 1). The five regions cover three climate zones ranging from tropical humid (Bo and Kenema) in Sierra Leone to tropical sub-humid humid (Mono and Couffo) in Benin and sub-humid dry (Sikasso) in Mali. Each farmer's field is geolocated with latitude/longitude coordinates. For each farmer's field, 131 variables are grouped in 9 themes: field characteristics, land preparation, field maintenance, irrigation, residue management, soil data, weather data, crop production in the dry season and crop production in the rainy season (Table 1). Data were obtained from either farmers' responses during surveys conducted in the 2013, 2014 and 2015 growing seasons or from direct field observations and measurements. Table 1 summarizes the database and the variables it contains.
Fig. 1.
Location of the study areas in West Africa.
Table 1.
Summary of the variables included in the database grouped by theme.
| Variables | Scale type | Scale class | Source of data |
|---|---|---|---|
| Theme 1: Field characteristics | |||
| Code to identify the field | Nominal | Unique code starting with the letter B for Benin, M for Mali and S for Sierra Leone. The letter is followed by an integer | surveys |
| GPS coordinates in decimal degrees | Numeric | surveys | |
| Ecology of the field | Nominal | Lowland, upland | surveys |
| Location in the topo sequence | Nominal | Upper part, fringe, lower part of the topo sequence | surveys |
| Surface area of the field in ha | Numeric | surveys | |
| Theme 2: Land preparation operations | |||
| Code to identify the field | Nominal | Refer to field code in Theme 1 | surveys |
| Code to identify the crop | Nominal | Name of crop in English | surveys |
| Cropping year | Numeric | surveys | |
| Cropping season | Nominal | Cold dry season, warm dry season and rainy season | surveys |
| Type of land preparation | Nominal | Tillage, no-tillage, raised board, flat board | surveys |
| Period of land cleaning | Numeric | Number of the week in the year when the land was cleaned | surveys |
| Manpower used for cleaning | Numeric | surveys | |
| Period of tilling the land | Numeric | Number of the week in the year when the land was tilled | surveys |
| Manpower used for tillage | Numeric | surveys | |
| Period of land puddling | Numeric | Number of the week in the year when the land was puddled | surveys |
| Manpower used for puddling | Numeric | surveys | |
| Period of land leveling | Numeric | Shouldn't the ‘Number of the week in the year when the land was levelled’ be included here? | surveys |
| Manpower used for land leveling | Numeric | surveys | |
| Other complementary land preparation operations | Nominal | Nursery | surveys |
| Period of implementation of other operations | Numeric | Number of the week in the year when nursery was planted | surveys |
| Manpower used for other operations | Numeric | ||
| Theme 3: Field maintenance operations | |||
| Code to identify the field | Nominal | Refer to field code in Theme 1 | surveys |
| Code to identify the crop | Nominal | Refer to crop code in Theme 2 | surveys |
| Cropping year | Numeric | surveys | |
| Cropping season | Nominal | Cold dry season, warm dry season and rainy season | surveys |
| Quantity of seed sown | Numeric | surveys | |
| Method of sowing | Nominal | Pocket, broadcasting, transplanting, cuttings, direct sowing | surveys |
| Date of sowing | Nominal | surveys | |
| Source of manure | Nominal | Rice straw; rice husks; poultry droppings; pig manure; other? manure; litter and compost | surveys |
| Quantity of manure used for first application | Numeric | surveys | |
| Quantity of manure used for second application | Numeric | surveys | |
| Date of first application of organic manure | Nominal | surveys | |
| Date of second application of organic manure | Nominal | surveys | |
| Manpower used for first application of organic manure | Numeric | surveys | |
| Manpower used for second application of organic manure | Numeric | surveys | |
| Number of organic manure applications | Numeric | surveys | |
| Quantity of NPK supplied during first application | Numeric | surveys | |
| Quantity of NPK supplied during second application | Numeric | surveys | |
| Quantity of NPK supplied during third application | Numeric | surveys | |
| Date of first application of NPK | Nominal | surveys | |
| Date of second application of NPK | Nominal | surveys | |
| Date of third application of NPK | Nominal | surveys | |
| Formulation NPK fertilizer | Nominal | surveys | |
| Manpower used for application of NPK fertilizer | Numeric | surveys | |
| Quantity of urea supplied during first application | Numeric | surveys | |
| Quantity of urea supplied during second application | Numeric | surveys | |
| Date of first urea application | Nominal | surveys | |
| Date of second urea application | Nominal | surveys | |
| Manpower used for urea application | Numeric | surveys | |
| Number of urea and NKP fertilizer applications | Numeric | surveys | |
| Mode of fertilizer application | Nominal | ||
| Other complementary operations aside from manure, pesticide and herbicide applications | Nominal | weeding | surveys |
| Date of first complementary operation | Nominal | surveys | |
| Date of second complementary operation | Nominal | surveys | |
| Manpower used for first complementary operation | Numeric | surveys | |
| Manpower used for second complementary operation | Numeric | surveys | |
| Quantity of herbicide applied in the field (mL) | Numeric | surveys | |
| Date of herbicide application | Nominal | surveys | |
| Commercial name of herbicide | Nominal | surveys | |
| Active substance in herbicide | Nominal | surveys | |
| Number of herbicide applications | Numeric | surveys | |
| Manpower used for herbicide application | Numeric | surveys | |
| Quantity of pesticide used to treat a field | Numeric | surveys | |
| Date of first pesticide application | Nominal | surveys | |
| Date of second pesticide application | Nominal | surveys | |
| Date of third pesticide application | Nominal | surveys | |
| Date of fourth pesticide application | Nominal | surveys | |
| Commercial name of pesticide | Nominal | surveys | |
| Active substance in pesticide | Nominal | surveys | |
| Number of pesticide applications | Numeric | surveys | |
| Theme 4: Field irrigation operations | |||
| Code for field identification | Nominal | surveys | |
| Field area | Numeric | surveys | |
| Code to identify crops | Nominal | surveys | |
| Cropping year | Numeric | surveys | |
| Cropping season | Numeric | surveys | |
| Period of irrigation | Numeric | surveys | |
| Use of well as water source | Nominal | Yes, No | surveys |
| Use of drilling as water source | Nominal | Yes, No | surveys |
| Use of river as water source | Nominal | Yes, No | surveys |
| Use of another source | Nominal | Yes, No | surveys |
| Type of reservoir used for irrigation | Nominal | Calabash, pump and seal | surveys |
| Number of days of irrigation per month | Numeric | three times a week, twice a week, twice a day five days a week, twice a day four days a week, twice a day seven days a week | surveys |
| Volume of reservoir | Numeric | surveys | |
| Mode of irrigation used | Nominal | Pocket and sprinkler | surveys |
| Duration of irrigation (h) | Numeric | surveys | |
| Manpower used per irrigation event | Numeric | surveys | |
| Total irrigated water | Numeric | surveys | |
| Water quantity per irrigation event | Numeric | surveys | |
| Theme 5: Field residue management practices | |||
| Code to identify the field | Nominal | surveys | |
| Code to identify the crop | Nominal | surveys | |
| Cropping year | Numeric | surveys | |
| Cropping season | Numeric | surveys | |
| Date of harvest | Nominal | surveys | |
| Crop residues from the field | Nominal | Yes, No | surveys |
| Crop residues used to feed animals | Nominal | Yes, No | surveys |
| Crop residues burned | Nominal | Yes, No | surveys |
| Crop residues incorporated in the soil | Nominal | Yes, No | surveys |
| Crop residues used for compost | Nominal | Yes, No | surveys |
| Crop residues abandoned | Nominal | Yes, No | surveys |
| Crop residues used for other purposes | Nominal | Yes, No | surveys |
| Theme 6: Weather data | |||
| Daily rainfall (mm) | Numeric | Weather stations | |
| Minimum daily temperature (°C) | Numeric | Weather stations | |
| Maximum daily temperature (°C) | Numeric | Weather stations | |
| Minimum daily relative humidity (%) | Numeric | Weather stations | |
| Maximum daily relative humidity (%) | Numeric | Weather stations | |
| Theme 7: Soil data | |||
| Code to identify village | Nominal | Soil sampling and laboratory analysis | |
| Code to identify field | Nominal | Soil sampling and laboratory analysis | |
| Sampling period during the year | Nominal | Soil sampling and laboratory analysis | |
| pH of water | Numeric | Soil sampling and laboratory analysis | |
| Soil organic carbon (%) | Numeric | Soil sampling and laboratory analysis | |
| Total nitrogen (%) | Numeric | Soil sampling and laboratory analysis | |
| Available phosphorus (ppm) | Numeric | Soil sampling and laboratory analysis | |
| Cation exchange capacity (meq/100g) | Numeric | Soil sampling and laboratory analysis | |
| Exchangeable calcium (cmolc kg−1) | Numeric | Soil sampling and laboratory analysis | |
| Exchangeable magnesium (cmolc kg−1) | Numeric | Soil sampling and laboratory analysis | |
| Exchangeable potassium (cmolc kg−1) | Numeric | Soil sampling and laboratory analysis | |
| Exchangeable sodium (cmolc kg−1) | Numeric | Soil sampling and laboratory analysis | |
| Percentage of sand (%) | Numeric | Soil sampling and laboratory analysis | |
| Percentage of silt (%) | Numeric | Soil sampling and laboratory analysis | |
| Percentage of clay (%) | Numeric | Soil sampling and laboratory analysis | |
| Theme 8: Crop production in the dry season | |||
| Code to identify the field | Nominal | ||
| Code to identify the crop | Nominal | ||
| Cropping year | Numeric | ||
| Cropping season | Numeric | ||
| Number of plots | Numeric | 4 m2 quadrat in the field | |
| Plot surface area (m2) | Numeric | 4 m2 quadrat in the field | |
| Number of plants in a plot | Numeric | 4 m2 quadrat in the field | |
| Number of plants harvested per plot | Numeric | 4 m2 quadrat in the field | |
| Number of tubers | Numeric | 4 m2 quadrat in the field | |
| Number of non-perished tubers | Numeric | 4 m2 quadrat in the field | |
| Number of perished tubers | Numeric | 4 m2 quadrat in the field | |
| Total weight of harvested tubers (kg) | Numeric | 4 m2 quadrat in the field | |
| Weight of non-undamaged harvested tubers (kg) | Numeric | 4 m2 quadrat in the field | |
| Weight of undamaged harvested tubers (kg) | Numeric | 4 m2 quadrat in the field | |
| Number of broken tubers | Numeric | 4 m2 quadrat in the field | |
| Number of small caliber tubers | Numeric | 4 m2 quadrat in the field | |
| Weight of broken tubers (kg) | Numeric | 4 m2 quadrat in the field | |
| Weight of small caliber tubers (kg) | Numeric | 4 m2 quadrat in the field | |
| Weight of other crops except rice and potatoes (kg) | Numeric | 4 m2 quadrat in the field | |
| Theme 9: Crop production in the rainy season | |||
| Code to identify the field | Nominal | ||
| Code to identify the crop | Nominal | ||
| Cropping year | Numeric | ||
| Cropping season | Numeric | ||
| Number of plots | Numeric | 4 m2 quadrat in the field | |
| Number of plants at 20 days after sowing | Numeric | 4 m2 quadrat in the field | |
| Number of plants at 75 days after sowing | Numeric | 4 m2 quadrat in the field | |
| Number of panicles per plot | Numeric | 4 m2 quadrat in the field | |
| Average height of plants at maturity per plot (m) | Numeric | 4 m2 quadrat in the field | |
| Number of grains per panicle | Numeric | 4 m2 quadrat in the field | |
| Average percentage of whole grain (%) | Numeric | 4 m2 quadrat in the field | |
| Average 1000 grain weight (kg) | Numeric | 4 m2 quadrat in the field | |
The database is in Microsoft Excel format and contains eleven sheets. The first sheet (Variables description) provides an explanation of the variables. The second sheet (VILLAGE) contains the names of lowlands investigated, the names of the villages, and regions in which the lowlands are located. The third sheet (FIELD) contains the list of fields cultivated by each farmer, their geolocation and surface area. The fourth sheet (FIELD PREPARATION) describes all land preparation operations, the period the operations were undertaken and the manpower allocated to each farmer's field. The fifth sheet (FIELD MAINTENANCE) describes planting, crop maintenance operations (manuring, weeding and pesticide application) and manpower allocated for all the operations implemented in each farmer’ field. The sixth sheet (FIELD IRRIGATION) describes irrigation operations including methods, frequency and the amount of water supplied. The seventh sheet (FIELD RESIDUES) contains the quantity of residues exported, left in the field or used to feed livestock for each farmer's field. The eighth sheet (WEATHER) contains daily weather data (temperature, relative humidity and rainfall) from 2013 to 2015 concerning the inland valley in which the village is located. The ninth sheet (FIELD SOIL ANALYSES) contains data on soil physical-chemical characteristics (particle size distribution, pH of the water, organic carbon, total nitrogen, available phosphorus, total potassium, cation exchange capacity, exchangeable calcium, magnesium and sodium) for each farmer's field. The tenth sheet (PLOT FIELD CS) contains yield data measured in each farmer's field in the 2013, 2014 and 2015 dry seasons. The eleventh sheet (PLOT PROD HIV) contains yield data measured in each farmer's field in the 2013, 2014 and 2015 rainy seasons.
Many values are missing in the tables for different reasons: data were not collected or we were not able to collect them, data were not viable after checking, no agronomic measurements were done or no technical operation was done in the field by the farmers.
2. Experimental design, materials and methods
This section provides a summary of the methods used to create the database. Data were collected in two stages. In the first stage, the main regions containing inland valleys in three West African countries viz. Benin, Mali and Sierra Leone were identified and the most cultivated inland valley in each region was selected. Weather data were collected from weather stations located close to the inland valleys concerned. In regions with no weather stations, Tinytag data loggers were installed in each of the selected inland valleys and used to record daily data on temperature, rainfall and relative humidity. In the second stage, the location and surface area of all the farmers' fields in each inland valley were determined with handheld GPS devices. In 2016, soil samples were collected in each farmer's field and the soil physical-chemical properties were determined. Socio-economic surveys were conducted from 2013 to 2015 to collect data on farmers' crops, crop sequences and management techniques using questionnaires and informal interviews. Crop yields were determined in 4 m2 quadrats in each farmer's field in the 2013, 2014 and 2015 growing seasons. Table 1 gives an overview of the 131 variables in the database and their source (surveys, weather stations, soil sampling and laboratory analyses or direct field observations and measurements).
Acknowledgements
The data was collected in the framework of the project: ‘Realizing the agricultural potential of the inland valleys in sub-Saharan Africa while maintaining their environmental services’ (RAP-IV), funded by the European Union (C-ECG-65-WARDA). The authors are grateful to field staff of the Institute of Rural Economy of Mali, the Rokupr Agricultural Research Centre of the Sierra Leone Agricultural Research Institute and the National Institute for Agricultural Research in Benin who took part in the field surveys.
Footnotes
Transparency document associated with this article can be found in the online version at https://doi.org/10.1016/j.dib.2019.103876.
Supplementary data to this article can be found online at https://doi.org/10.1016/j.dib.2019.103876.
Transparency document
The following is the transparency document related to this article:
Appendix A. Supplementary data
The following is the Supplementary data to this article:
References
- 1.Furlan T., Ballot R., Guichard L., Huat J. International Symposium for Farming Systems Design; Montpellier, France: 2015. Possible ex-ante assessment of rice-vegetable systems performances when facing data scarcity: use of the PERSYST model in West Africa.http://fsd5.european-agronomy.org European Society for Agronomy. September 7th – September 10th, 2015. [Google Scholar]
- 2.Hengl T., Walsh M.G., Tilahun H., Wheeler I., Leenaars J.G.B., Berkhout E., Kwabena N.A., Shepherd K.D., Mamo T., Cooper M., Fegraus E. Soil nutrient maps of Sub-Saharan Africa: assessment of soil nutrient content at 250 m spatial resolution using machine learning. Nutrient Cycl. Agroecosyst. 2017;109:77–102. doi: 10.1007/s10705-017-9870-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.MacDonald A.M., Bonsor H.C., O Dochartaigh B.E., Taylor R.G. Quantitative maps of groundwater resources in Africa. Environ. Res. Lett. 2012;7(7) 024009. [Google Scholar]
- 4.Dossou-Yovo E.R., Baggie I., Djagba J.F., Zwart S.J. Diversity of inland valleys and opportunities for agricultural development in Sierra Leone. PLoS One. 2017;12(6) doi: 10.1371/journal.pone.0180059. e0180059. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Rodenburg J., Zwart S.J., Kiepe P., Narteh L.T., Dogbe W., S Wopereis M.C. Sustainable rice production in African inland valleys: seizing regional potentials through local approaches. Agric. Syst. 2014;123:1–11. [Google Scholar]
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