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The global peace and food security; a case study of the Global South and the South Pacific Island nations; the need for affordable wheat and grain supply

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DataONE2026-02-25 更新2026-02-28 收录
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Most countries in the Global South, Africa, and Pacific Islands have irregular rainfall patterns, with strains of El Niño patterns causing severe food shortages. Plant breeding on grains is non-existent in Pacific Island nations, and the main staple foods are imported rice and wheat, although their prices are exorbitant. Food labelling and marketing of affordable energy grains from conventional and mutational plant breeding programs are fundamental for producers and consumers to establish in the global food trade. A new paradigm shift in the agrifood system was modelled to accompany energy alone food aid from the regions of the wheat and grain producing countries, deviating from the recent bio-fortification race. Main attentions are stressed on plant breeding and agronomic practices to secure food security but however food losses from different factors along the way from farm to fork have most times being neglected. The data on food loss is sourced from FAOSTAT 2022(top 10 crop species ..., , # The global peace and food security; a case study of the Global South and the South Pacific Island nations; the need for affordable wheat and grain supply Dataset DOI: [10.5061/dryad.kwh70rzk7](https://doi.org/10.5061/dryad.kwh70rzk7) ## Description of the data and file structure Records of food loss and their contributing factors are analyzed in this data. The data is extracted from FAOSTAT2022(2000-2022). The data was used mainly to assess the plant breeding stress from the bio-fortification of nutrients. The data found significant food losses without characters in critical areas of field specializations. The data is however readable by Scholars studying factors of food losses. ### Files and variables #### File: Food_Loss__Top_ten_by_country.csv **Description:** Data recorded from column down as per headings ##### Variables/Columns * Column A; code of country * Column B; country where food loss measured * Column C; region/specific location(Empty spaces means no data available)...,
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2026-02-25
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