Climate change increases extreme whether events such as floods, hailstorms, or storms, which can affect agriculture, causing damages and economic loss within the agro-food sector. Optical remote sensing data have been successfully used in damage detections. Cloud conditions limit their potential, especially while monitoring floods or storms that are usually related to cloudy situations. Conversely, data from the Polarimetric Synthetic Aperture Radar (PolSAR) are operational in all-weather conditions and are sensitive to the geometrical properties of crops. Apple orchards play a key role in the Italian agriculture sector, presenting a cultivation system that is very sensitive to high-wind events. In this work, the H-α-A polarimetric decomposition technique was adopted to map damaged apple orchards with reference to a stormy event that had occurred in the study area (NW Italy) on 12 August 2020. The results showed that damaged orchards have higher H (entropy) and α (alpha angle) values compared with undamaged ones taken as reference (Mann–Whitney one-tailed test U = 14,514, p < 0.001; U = 16604, p < 0.001 for H and α, respectively). By contrast, A (anisotropy) values were significantly lower for damaged orchards (Mann–Whitney one-tailed test U = 8616, p < 0.001). Based on this evidence, the authors generated a map of potentially storm-damaged orchards, assigning a probability value to each of them. This map is intended to support local funding restoration policies by insurance companies and local administrations.

Plant wearable devices have the potential to transform horticultural practices by enabling continuous, noninvasive monitoring of plant health and environmental conditions in real-time and at a localized scale. Their flexible, lightweight designs and seamless conformability allow placement near delicate plant organs or within their microclimate, overcoming limitations that rigid sensors encounter when interfacing with soft and dynamic plant tissues. However, as wearable plant technology advances in precision horticulture, the issue of electronic waste (e-waste) becomes increasingly critical, especially when numerous devices are required for comprehensive, field-wide data collection. This underscores the pressing need for sustainable and biocompatible alternatives. Although recent efforts have focused on developing biodegradable devices and eco-friendly fabrication processes for horticultural applications, progress has been moderate. This Perspective reviews the current and future potential of sustainable plant wearable technologies, showcasing existing implementations and exploring the challenges and feasible pathways toward enhancing sustainability while acknowledging the complexity and multifaceted nature of true sustainability.

Precision horticulture demands affordable and versatile platforms to test a variety of sensors. However, current solutions are often costly, complex, and limited in scope, hindering widespread adoption. Here, we present a modular and practical sensor system designed for the integration and evaluation of printed impedimetric sensors. The platform includes an impedance analyzer, two 16-channel multiplexers, and a Raspberry Pi. Using the developed data acquisition system, we fully characterized the electrical impedance spectroscopy response of an ammonia gas sensor and three humidity sensors over a frequency range from 500 Hz to 10 MHz. The chemiresistive ammonia sensor, tested in a controlled laboratory environment using a gas exposure setup, showed optimal operation at 4 kHz, demonstrating high sensitivity in impedance magnitude measurements. In contrast, the paper-based humidity sensors were evaluated directly on plants under field conditions, where analysis of phase angle ($\Theta$) and impedance magnitude ($\Omega$) identified optimal measurement points. At lower frequencies (below $10^{4}$ Hz), both parameters showed strong correlations with relative humidity, with correlation coefficients of $0.52 \pm 0.03$ and $-0.54 \pm 0.02$, respectively. These results indicate a capacitive response to moisture absorption and good reproducibility between devices. Beyond $10^{5}$ Hz, the correlation weakened, indicating a transition in sensor response mechanisms. Our results demonstrate the effectiveness of the platform in both laboratory and field environments, providing a robust and cost-effective tool to evaluate impedimetric sensors. By enabling rapid and accurate assessments, this system advances agricultural technology for more efficient, sustainable precision horticulture.