Forthcoming Articles

International Journal of Agricultural Resources, Governance and Ecology

International Journal of Agricultural Resources, Governance and Ecology (IJARGE)

Forthcoming articles have been peer-reviewed and accepted for publication but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Therefore, the content conforms to our standards but the presentation (e.g. typesetting and proof-reading) is not necessarily up to the Inderscience standard. Additionally, titles, authors, abstracts and keywords may change before publication. Articles will not be published until the final proofs are validated by their authors.

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International Journal of Agricultural Resources, Governance and Ecology (2 papers in press)

Regular Issues

  • Crop diversification and farm productivity in sub-Saharan Africa: insights from household-level evidence in Ghana   Order a copy of this article
    by Ebenezer Kondo, Freda Asem, Yaw Osei-Asare, Akwasi Mensah-Bonsu 
    Abstract: Agricultural production systems in sub-Saharan Africa face the challenges of increasing productivity while maintaining resilience to climate variability, market uncertainty, and resource constraints. The crop diversification-productivity nexus remains ambiguous and insufficiently understood. This paper utilised the wave 3 cross-sectional dataset of the Ghana Socio-economic Panel Survey (GSPS) to examine the effect of crop diversification on productivity of farm households in Ghana. After accounting for other exogenous covariates and addressing potential endogeneity using the 3SLS regression model, the findings showed that an additional unit of diversified crops cultivated by a farm household increased total output by approximately 11%. The seemingly unrelated regression model was estimated to check for robustness. It is recommended that extension delivery messages be reformed to include the productivity-increasing effect of diversified crop production among smallholder farm households.
    Keywords: crop diversification; productivity; endogeneity; Ghana.
    DOI: 10.1504/IJARGE.2026.10080545
     
  • Plant foliar disease detection using deep learning   Order a copy of this article
    by Shailender Singh, T.V. Vijay Kumar 
    Abstract: For a nations financial stability, especially in overpopulated countries, farming is essential. Past agricultural revolutions have increased yield, yet modern agriculture faces challenges such as declining soil fertility, inefficient irrigation, and plant foliar diseases. Among these, timely identification of plant diseases is critical, and machine learning, especially deep learning, offers an effective means to achieve it. Accordingly, the study carried out in this paper evaluates four MobileNet architectures (V1, V2, V3 small, and V3 large) of convolutional neural network for detecting foliar diseases in apple, cherry, grape, peach, and strawberry leaves from the PlantVillage dataset. This study aims to use lighter variants of MobileNets for plant foliar disease detection and compare their performance in terms of classification-based metrics and system level metrics, in order to ascertain whether thinner models of MobileNets can outperform their original counterparts. Experimental-based comparisons showed that MobileNet-V2 performed comparatively better, making it a promising model for crop disease detection.
    Keywords: agriculture; plant foliar disease detection; artificial intelligence; machine learning; deep learning; DL.
    DOI: 10.1504/IJARGE.2026.10082023
     

 

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