Rapid climatic fluctuations and increasing global resource pressures are driving the need for high‑precision, real‑time monitoring of agro‑environmental systems. Precision agriculture formulates this requirement as a complex measurement problem, where various physical, chemical, and biological parameters have to be detected with high sensitivity and selectivity. Addressing these critical aspects, this review examines quantum sensing and quantum-material-assisted sensing as an emerging framework that utilizes quantum phenomena, such as coherence, confinement, and correlated optical interactions, to enhance signal-to-noise ratio and detection resolution. Particular emphasis is placed on two‑dimensional (2D) quantum materials, including graphene, transition‑metal dichalcogenides, and MXenes, which offer tunable surface states, defect‑engineered selectivity, and strong light-matter coupling. When integrated with plasmonic and surface‑enhanced Raman scattering (SERS) architectures, these materials provide highly responsive transduction routes for detecting soil nutrients, water contaminants, gaseous species, and plant metabolites relevant to precision agriculture. It also discusses performance metrics sensitivity, drift stability, energy efficiency, and cost per sensing node alongside challenges of matrix effects, calibration, and long‑term durability. Strategies for field translation, including flexible sensor integration, scalable fabrication, and sustainable deployment, are analyzed to outline a roadmap for quantum‑enabled sensing in next‑generation agricultural and environmental monitoring.
Kaur et al. (Thu,) studied this question.