Can Precision Agriculture Be Used in the Management of a Fe and Zn Biofortification Workflow in Organic Tomatoes (Lycopersicum esculentum L.)?

Abstract

It is expected that the population worldwide might exceed 9 billion by 2050, therefore it being imperative to increase food production. As such, the development of smart farming technology is an important key food production issue. In fact, through the use of UAVs (Unmanned Aerial Vehicles), it is possible to create normalized difference vegetation index (NDVI) maps, that can indicate factors, such as health and vegetation vigor. In this context, this study aimed to assess the state of three tomato varieties (beef heart, “chucha”, and apple) in the framework of a biofortification workflow with Fe and Zn, following an organic production mode. In a tomato experimental production field (GPS coordinates—39°41′48.517″ N; 8°35′45.524″ W), six foliar sprayings were carried out during the production cycle, with a mix of Zitrilon (15%) (0.40 and 1.20 kg·ha−1) and Maxiblend (1 and 4 kg·ha−1). NDVI was determined 7 days before the first foliar spraying and showed a maximum of 0.86 (on a scale from −1 to 1). After the 3rd foliar spraying, no changes were detected in the color of freshly harvest tomatoes (assessed through spectrophotometric colorimeter), but an increase of Fe and Zn content was found in the leaves, and of Zn in tomatoes themselves (except in “chucha” variety). The use of precision agriculture techniques in correlation with the other analyses is discussed.

Beyond Vegetation: A Review Unveiling Additional Insights into Agriculture and Forestry through the Application of Vegetation Indices

“…Agricultural management geared towards enhancing the yield quality in organic production [36,37] Detect phytochemicals in organic agriculture to facilitate the adherence to certification audits, ensuring the maintenance of safe pesticide thresholds in conventional agricultural practices [38][39][40] Increase the traceability of organic production [41] Disaster management Detect flood-affected areas [42] Identify areas affected by wildfires [43] Assess and monitor regional droughts [44] Rapid damage assessment post-disaster [45] Aid in monitoring and mapping wildfire damages and post-fire recovery [46] Microorganisms and yeasts Detect fungal infections in crops [47,48] Monitor the induction of plant defense mechanisms [49] Study the interaction of climate, topography, and soil properties with cropland [50] Identify the presence of infections in plants [51] Monitor microbial terroir and yeast-species richness within the vineyards [52] Differentiate yeasts according to their fermentative capacity and a decision-making resource for designation of origin (DO) regulators and viticulturists [53] Detect the presence of aggressive soil pathogens [54] Table 1. Cont.…”

“…One of the salient constraints in organic agriculture is weed proliferation, the management of which is crucial, yet challenging, for ensuring optimal yields. Through NDVI cluster analysis, the spatial and temporal heterogeneity of crops can be discerned in the early stages, thereby furnishing strategic insights for agricultural management geared towards enhancing the yield quality in organic production [36,37]. Furthermore, the incorporation of deleterious chemicals, particularly in the form of pesticides, in agricultural production poses substantial risks to consumers.…”