Journal: Journal of Agriculture and Food Research

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Publisher

Elsevier

Journal Volumes

ISSN

2666-1543

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2023 - 20254
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Publications 1 - 4 of 4
  • Towards improving farmers livelihood in Nigeria using food price forecasting
    Item type: Journal Article
    Odion , Divinefavour; Gajardo Castillo, Joaquin; Defraeye , Thijs; et al. (2025)
    Journal of Agriculture and Food Research
    Nigeria's agricultural sector represents approximately 25 % of the country's overall GDP and is a major source of employment for its population. This sector is largely driven by smallholder farmers who grow fruits and vegetables on farms under 4 ha. Despite their significant contribution to food production in Nigeria, most smallholder farmers, approximately 70 %, live in poverty, earning less than $1.9 per day. One of the key factors contributing to this situation is a lack of access to market price information. Farmers currently rely only on historical prices observed in local markets to decide on when, what, where and the price to sell their produce. This can lead to suboptimal decisions, resulting in food loss and loss of potential income. To address this challenge, we developed a machine learning online pipeline. It utilizes a Random Forest model trained on historical monthly fresh produce prices and other macroeconomic factors like currency exchange rates for Nigeria, that are regularly scraped from the internet. We deployed our trained model through an open-source mobile application, Coldtivate. Our model accurately predicted market prices for crops such as tomatoes, onions, potatoes, and plantains in various Nigerian states. The prediction success rate of our model varied across the various states in Nigeria. It ranged from 1 % to 20 % in Mean Absolute Percentage Error (MAPE) for predictions up to 8 months ahead. When evaluated on a hold-out test set, it yielded an RMSE of ₦45.16. The average MAPE of our model, when considering state-time-commodity averages, is up to 5 % lower than other baseline models, including the benchmark rolling-average, CatBoost, XGBoost, and SARIMA. By detecting patterns and trends in food prices, farmers can use our tool to make more informed decisions about when and what to sell to optimize profit, thereby improving revenue. Furthermore, our model provides a foundation for future machine learning model development in food price forecasting in agrarian countries.
  • Closing the crop yield gap between organic and conventional farming systems in Kenya: Long-term trial research indicates agronomic viability
    Item type: Journal Article
    Bautze, David; Karanja, Edward; Musyoka, Martha; et al. (2024)
    Journal of Agriculture and Food Research
    The production gap between current and attainable yields is highest on Africa's smallholder farms, and some studies indicate that they might not benefit from the yield gains offered by conventional farming. Simultaneously, alternative farming systems like organic provide biodiversity and soil fertility advantages, but their ability to produce sufficient food is still under debate. Additionally, comparative data on the productivity of organic versus conventional in tropical regions are scarce or short-term. We investigated the crop productivity of organic and conventional farming systems using 15 years in two long-term systems comparison trials in Kenya. The trials were established in 2007 at two sites in the Central Highlands of Kenya. At each site, conventional and organic systems were compared at high input levels. The trial involved a three-year crop rotation cycle of maize, vegetables, legumes, and potatoes, repeated five times since its establishment. Management practices were kept similar in the first four rotations and revised in the fifth to improve systems representing best practices. Our results showed that while maize and baby corn had relatively low yield gaps (−13 to +12 %) between organic and conventional systems, cabbage, French beans, and potato had high yield gaps (−50 to −30 %). We attributed this to nutrient limitations and higher pest and disease damage. The yield gap could partially be closed by adopting best practices in the organic system, including system diversification and effective soil fertility, nutrient, and integrated pest management.
  • A comprehensive meta-analysis of nitrate leaching from wheat, rice, and maize cultivation on a global scale
    Item type: Journal Article
    Hina, Naila (2025)
    Journal of Agriculture and Food Research
    Cereal crops are a vital source of food for the global population, but their cultivation can also result in nitrate leaching into the soil and groundwater, posing potential environmental and health risks. This meta-analysis aimed to assess the global extent of nitrate leaching from the cultivation of wheat, rice, and maize, three major cereal crops grown worldwide. A comprehensive literature search was conducted to identify relevant studies that reported nitrate leaching. The findings indicate that overall nitrate leaching from cereal crops varies greatly but is significantly (p < 0.0001) higher for wheat-maize rotation compared to wheat and rice. Additionally, nitrate leaching losses were influenced by factors such as the rate, timing, and method of nitrogen fertilizer application, with higher mean leaching observed in wheat-maize rotations with organic fertilizer application (93.6 kg N ha−1) and from wheat when fertilizers were applied in a full dose (84.8 kg N ha−1). This meta-analysis highlights the importance of sustainable agriculture practices as optimum use of nitrogen fertilizers to reduce nitrate leaching and mitigate its potential environmental and health impacts. The results of this study can be used by policy makers and agriculture practitioners to inform decision-making and promote sustainable agriculture practices.
  • The genetic diversity and nutritional quality of proso millet (Panicum miliaceum) and its Philippine ecotype, the ancient grain “kabog millet”: A review
    Item type: Review Article
    Oñate Narciso, Joan; Nyström, Laura (2023)
    Journal of Agriculture and Food Research
    Background Climate change and biodiversity loss will push us to revolutionise and transform our existing food systems to feed the global population and provide sustainable nutrition. Alternative crops such as proso millet present a viable option to diversify our diet and contribute to food security. Proso millet (Panicum miliaceum L.) is nutritious but is not a widely popular food grain in developed countries. This review provides existing relevant information on the genetic diversity and nutritional properties of proso millet. This paper also presents additional current information on the “kabog millet”, an ancient grain from Cebu, Philippines, considered an ecotype of proso millet. The nutritional profiles of these ancient grains should be emphasised because farmers tend to abandon cultivation of these ancient grains in the absence of nutritional data. By understanding the nutritional profile of “kabog millet” and other ancient grains, the local diets could be redesigned to incorporate these crops for a more complete and balanced nutrition. Main conclusions Proso millet offers a resilient, nutritious crop in the face of climate change. Nutritional analyses of proso millet varieties and other minor crops are tools to encourage farmers and growers to cultivate them and for consumers to integrate these crops in the diet. Without nutritional studies, many minor crops will be overlooked and will soon be forgotten. The inclusion and consumption of ancient grains like “kabog millet” as staple food can help address the challenge of food insecurity by providing more balanced diets, and biodiversity loss by encouraging cultivation of overlooked and often forgotten plant varieties.
Publications 1 - 4 of 4