Climate variability constitutes a primary threat to fruit crop productivity. Specifically, severe volumetric water deficits, extreme thermal anomalies, and excessive solar irradiance disrupt essential physiological functions, directly reducing both total agricultural yield and the commercial quality of export-oriented fruit species. This systematic review analyzes the impact of these microclimatic stressors on crop physiology and evaluates how Internet of Things architectures optimize agricultural management. The methodology was structured using the PIOC framework in accordance with PRISMA 2020 guidelines to systematically retrieve and filter relevant scientific literature. The synthesized evidence demonstrates that prolonged exposure to these climatic extremes drastically reduces net photosynthesis and stomatal conductance. To counteract this physiological degradation, integrating distributed agro-environmental sensors, long-range communication networks, and machine learning algorithms can automate precision irrigation. This technological synergy significantly improves water-use efficiency, minimizes yield variability, and enables early prediction of physiological stress. Furthermore, these digital frameworks facilitate early productivity forecasting, the detection of tissue anomalies, and the dynamic adaptation of agronomic management across Mediterranean, semi-arid, and tropical microclimates. Ultimately, IoT-driven digitization strengthens agroecological resilience, promoting highly efficient and sustainable fruit cultivation under increasingly erratic global climate constraints.
Citation: Cinthia F. Chapoñan-Baldera, Julio A. Gutierrez-Ballona, José A. Vásquez-Coronel. The Internet of Things as a tool for smart monitoring of fruit crops: A systematic review of the literature[J]. AIMS Agriculture and Food, 2026, 11(4): 1059-1083. doi: 10.3934/agrfood.2026052
Climate variability constitutes a primary threat to fruit crop productivity. Specifically, severe volumetric water deficits, extreme thermal anomalies, and excessive solar irradiance disrupt essential physiological functions, directly reducing both total agricultural yield and the commercial quality of export-oriented fruit species. This systematic review analyzes the impact of these microclimatic stressors on crop physiology and evaluates how Internet of Things architectures optimize agricultural management. The methodology was structured using the PIOC framework in accordance with PRISMA 2020 guidelines to systematically retrieve and filter relevant scientific literature. The synthesized evidence demonstrates that prolonged exposure to these climatic extremes drastically reduces net photosynthesis and stomatal conductance. To counteract this physiological degradation, integrating distributed agro-environmental sensors, long-range communication networks, and machine learning algorithms can automate precision irrigation. This technological synergy significantly improves water-use efficiency, minimizes yield variability, and enables early prediction of physiological stress. Furthermore, these digital frameworks facilitate early productivity forecasting, the detection of tissue anomalies, and the dynamic adaptation of agronomic management across Mediterranean, semi-arid, and tropical microclimates. Ultimately, IoT-driven digitization strengthens agroecological resilience, promoting highly efficient and sustainable fruit cultivation under increasingly erratic global climate constraints.
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Figures(6) / Tables(6)
Cinthia F. Chapoñan-Baldera, Julio A. Gutierrez-Ballona, José A. Vásquez-Coronel. The Internet of Things as a tool for smart monitoring of fruit crops: A systematic review of the literature[J]. AIMS Agriculture and Food, 2026, 11(4): 1059-1083. doi: 10.3934/agrfood.2026052
PRISMA2020 flow diagram of the study selection process
Distribution of studies according to research questions
Impact of climate variability on agronomic indicators in fruit crops
Technological intervention flow in precision fruit growth
Increased yield with water and nutrient savings
Frequency distribution of fruits in the studies analyzed
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