Balancing Chemical Pesticides and Organic Fertilizers in Garlic Production: A Review of Correlations, Trade-offs, Sustainability, and the Need for ML-Based Decision Support

Abstract

The Garlic (Allium sativum L.) is a highly valuable horticultural crop
with high value, nutritional, medicinal and commercial value which is
increasingly depending on synthetic pesticides and conventional
nutritional feeds to its increasing production systems. There is some
evidence available indicating that the risk of residues, pest resistance,
soil degradation, and ecological stress associated with high rates of
chemical pesticide use might be decreased through the alternative
employment of organic manure and integrated nutrient
administration, which are not fully utilized or applied equally even
where they have the potential to grow soil organic carbon and
nutrient-use efficiency, crop-resilience and bulb-quality. The literature
review will be summarized regarding the agronomy of garlic, pest and
disease infestations, crop-health monitoring, yield response, and
sustainability measurement as the literature attempts to comprehend
the relationship that exists between chemical pesticides and the
organic fertilizers in a production system. It dwells on correlations
between intensity of inputs and pest attack and the health and yield
and quality of the plants; agronomic, economic and ecological trade
offs between the different input regimes; the suitability of
sustainability indicators of soil organic carbon and bioefficiency ratio
and residue burden and input-use efficiency. As observed in the
review, another major gap in the current literature is that there were
no coherent and garlic-specific machine learning-based decision
support systems capable of processing input data at the field level, soil
condition, pest stress, and agro-climatic factors, and transforming
them into recommendations applicable to a specific site. This review
offers a model of sustainable garlic intensification, and sensible advice
to the researcher, extension systems, and agricultural policy by
integrating piecemeal evidence and determining the significance of
forecasting, information-based advisory instruments.