A Multi-Isotope Approach (δ²H, δ¹⁸O, δ¹³C, δ¹⁵N) for Discriminating Raspberry Production Systems and Assessing...

The development of sustainable and climate-resilient food systems increasingly relies on robust analytical methodologies capable of integrating environmental, biochemical, and management-related signals. In this study, a multi-isotope framework based on δ²H, δ¹⁸O, δ¹³C, and δ¹⁵N was applied to assess its capacity to discriminate between contrasting raspberry production systems and to provide chemically grounded indicators of agroecosystem functioning. Raspberry fruits (Rubus idaeus L.; cultivars Opal and Delniwa) were collected during the 2024-2025 growing seasons from two distinct systems in Romania: an organic open-field system and a rainfed agroforestry system. Stable isotope ratio analysis revealed system-dependent isotopic patterns, with the strongest differentiation observed for δ¹⁵N. Nitrogen isotope composition (δ¹⁵N) provided the strongest discrimination, with enriched values in organic fruits (2.73-9.77‱) and depleted values in agroforestry fruits (-3.01 to 0.62‱), reflecting differences in nitrogen sources and cycling pathways. Hydrogen and oxygen isotopes (δ²H: -60.46 to -4.62‱; δ¹⁸O: -6.19 to 10.41‱) were consistent with hydroclimatic variability and evaporative fractionation processes associated with soil-plant-atmosphere interactions. Carbon isotopes (δ¹³C: -28.14 to -22.62‱) provided complementary insights into plant water-use conditions. Multivariate statistical analysis supported the separation between production systems, while short-term fertilisation effects were secondary to system-level controls. The results suggest that raspberry fruits preserve an integrated isotopic fingerprint of production environment and management practices. From an analytical chemistry perspective, this work highlights the relevance of multi-isotope approaches as transferable tools for food authentication, traceability, and sustainability assessment, contributing to the broader application of stable isotope techniques across complex biological systems.