Some authors reported little effect of changes in the cost of shipping fertilizer from the distributor to local retailer [21,58]. No, Is the Subject Area "Urea" applicable to this article? The “new” phosphorus fertilization guidelines for maize by FERTASA. The main goal of this paper was to describe price variation within and between countries and to use spatial interpolation models to predict local prices of urea, a commonly used source of inorganic nitrogen. We used the town name to assign geographic coordinates to each location. Sown/planted areas, yields and value of production 14 4. The LSMS data for Mali and Nigeria had many more outliers (25% and 24%) than Ethiopia (13%), Tanzania (10%), and Malawi (1.6%) (Table 1). There are 132 npk fertilizer suppliers, mainly located in Africa. Although the Africa fertilizer model performed slightly better than the LSMS model (ER: 0.26 vs 0.21); LSMS had much more data, and a better geographic coverage. Made in South Africa Npk Fertilizer Directory - Offering Wholesale South African Npk Fertilizer from South Africa Npk Fertilizer Manufacturers, Suppliers and Distributors at TradeKey.com For truck/bus/minibus this relationship was 6.23%; for bicycle taxi was 5.11%; and for own bicycle/oxcart was 3.13%. LATEST NEWS. 9%. Yes Figure 2: Fertilizer consumption in South Africa, 2009 - 2018 Source: FERTASA For Tanzania, the performance of the models was better for Africa Fertilizer but in this case LSMS also performed well (correlation coefficient 0.42 vs 0.58 and ER 0.21 vs 0.26). 1.48. The slopes (that is, how much the price of NPK/DAP/CAN changes for a one dollar increase in the urea price) were 1.07 USD kg-1 for NPK; 1.16 USD kg-1 for DAP; and 0.95 USD kg-1 for CAN (Fig 3). A downside of using such algorithmic methods is that there is no direct way to estimate uncertainty. Countries where the model performed very well, such as Côte d’Ivoire, Kenya, Senegal, Tanzania, and Uganda had a relatively high range in observed prices. An obstacle to using empirical data on sub-national variation in fertilizer prices is the scarcity of such data. No, PLOS is a nonprofit 501(c)(3) corporation, #C2354500, based in San Francisco, California, US, https://doi.org/10.1371/journal.pone.0227764, https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/E0EHLO, http://surveys.worldbank.org/lsms/programs/integrated-surveys-agriculture-ISA, https://doi.org/10.5067/MEaSUREs/GFSAD/GFSAD30AFCE.001. Prices are for 25 kg or 50 kg bags and expressed in the national currency. In 10 countries, predictions were at least 25% better than a null-model that assumes no spatial variation. In Senegal, prices are much higher south of The Gambia, which is a region of Senegal that is relatively difficult to reach from the other part of the country (Figs 5 and 6). Yes The outliers were not clustered in a specific region of the country. https://doi.org/10.1371/journal.pone.0227764.g007. We had 159 cases from twelve countries from Africa Fertilizer data where we had subsidized and non-subsidized fertilizer prices from the same town. It is important to note that cross-validation results may be inflated for such regions because, on average, model skill should decrease with the distance from a location to locations with known prices (cf., [63]). Africa Fertilizer reports prices over time for major towns in different countries. In Nigeria, 48% of the outliers were associated with small quantities (10 kg or less) and 35% were associated with quantities below 4 kg. Yearly rate of inflation** 8.5%. Countries where the spatial prediction model did not perform very well were relatively small (e.g. Writing – review & editing, Affiliation For more information about PLOS Subject Areas, click Political influence can affect the allocation of subsidies, with politically well-connected villages receive more input compared to less connected villages [52, 53, 54] or to reward loyalty [55, 56, 57]. View Range. Net fertilizer price trends 28 14. 1.61. Data Availability: Data are available in: (https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/E0EHLO). We propose that spatial price estimation methods such as the ones we employ here may serve for better approximating heterogeneous economic market landscapes, until such time as truly comprehensive local market price information systems become available. Crop yields in Sub-Saharan Africa (SSA) are generally very low [1, 2]. To better understand patterns of, and opportunities for, fertilizer use, location specific fertilizer price data may be relevant. A number of hypotheses have been proposed to explain the low usage of inorganic fertilizer in SSA: (a) on many African soils, crops do not respond well to fertilizer, perhaps because of a low soil organic matter content or soil degradation [8, 9, 10, 11, 12]; (b) farmers are not aware of, or do not believe in the utility of inorganic fertilizer [13, 14, 15]; (c) farmers have a cash-flow problem, and need better access to credit to buy fertilizers [13, 16, 17]; (d) variability in rainfall makes it too risky to invest in fertilizers, and insurance programs may be needed to support fertilizer use [5, 18]; and (e) after accounting for agronomic responses to fertilizer; local input and output prices are such that fertilizer investments are insufficiently profitable for many farmers [18, 19, 20, 21]. 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