UAVs to Monitor and Manage Sugarcane: Integrative Review

Abstract

Pilotless aircraft systems will reshape our critical thinking about agriculture. Furthermore, because they can drive a transformative precision and digital farming, we authoritatively review the contemporary academic literature on UAVs from every angle imaginable for remote sensing and on-field management, particularly for sugarcane. We focus our search on the period of 2016–2021 to refer to the broadest bibliometric collection, from the emergence of the term “UAV” in the typical literature on sugarcane to the latest year of complete publication. UAVs are capable of navigating throughout the field both autonomously and semi-autonomously at the control of an assistant operator. They prove useful to remotely capture the spatial-temporal variability with pinpoint accuracy. Thereby, they can enable the stakeholder to make early-stage decisions at the right time and place, whether for mapping, re-planting, or fertilizing areas producing feedstock for food and bioenergy. Most excitingly, they are flexible. Hence, we can strategically explore them to spray active ingredients and spread entomopathogenic bioagents (e.g., Cotesia flavipes and Thricrogramma spp.) onto the field wherever they need to be in order to suppress economically relevant pests (e.g., Diatraea saccharalis, Mahanarva fimbriolata, sugarcane mosaic virus, and weeds) more precisely and environmentally responsibly than what is possible with traditional approaches (without the need to heavily traffic and touch the object). Plainly, this means that insights into ramifications of our integrative review are timely. They will provide knowledge to progress the field’s prominence in operating flying machines to level up the cost-effectiveness of producing sugarcane towards solving the sector’s greatest challenges ahead, such as achieving food and energy security in order to thrive in an ever-challenging world.

Complementary Use of Ground-Based Proximal Sensing and Airborne/Spaceborne Remote Sensing Techniques in Precision Agriculture: A Systematic Review

“…Demand of an assistant operator to perform a flight [71] To reduce bias, the two first authors double-checked the findings of each of the six authors during the second phase of deciding paper eligibility. Any paper that mentioned a well-analysed and evidence-supported phrase that met the challenge or synergy criteria was eligible for synthesis.…”

“…Therefore, UAVs present a less costeffective option for high spectral resolution when compared to satellites [129]. According to [71], another challenge for UAVs is their dependence on payload. Equipping the UAV with multiple sensors is not recommended, as it reduces flight time and affects its balance mid-flight ( [81,86]).…”

“…For example, [125] recommended the actualization of more studies concerning the validation of low-cost sensors' results in different conditions. Moreover, according to [71,82], there is a need for the development of fully autonomous UAVs. Ref.…”

“…[79] also discussed the implementation of multiple coordinated UAVs in an individual field. Finally, the path optimization of UAVs, in order to monitor a whole field with adequate accuracy, is mentioned in [71,75].…”

UAV imagery data and machine learning: A driving merger for predictive analysis of qualitative yield in sugarcane

“…is a semi-perennial grassy crop. Such a crop offers the global agriculture and bioeconomy sector possibilities to fabricate food, fuel, and feed ( Barbosa Júnior et al., 2022a ). It is a world-leading source of sugar for human consumption.…”