Magenta Cherry or Eugenia (Syzygium paniculatum Gaertn) is an underutilized berry species with an interesting source of functional components. This study aimed to evaluate these berries’ morphometric, nutritional, and phytochemical characteristics at two ripening stages, CM: consumer maturity (CM) and OM: over-maturity. Morphometric analysis revealed size and weight parameters comparable to commercial berries such as blueberries. Fresh fruits were processed into pulverized material, and in this, a proximate analysis was evaluated, showing high moisture content (88.9%), dietary fiber (3.56%), and protein (0.63%), with negligible fat, indicating suitability for low-calorie diets. Phytochemical screening by HPLC identified gallic acid, chlorogenic acid, hydroxycinnamic acid, ferulic acid, quercetin, rutin, and condensed tannins. Ethanol extracts showed stronger bioactive profiles than aqueous extracts, with significant antioxidant capacity (up to 803.40 µmol _Trolox/g via Ferric Reducing Antioxidant Power (FRAP assay). Fourier-transform infrared spectroscopy (FTIR) and Raman spectroscopic analyses established structural transformations of hydroxyl, carbonyl, and aromatic groups associated with ripening. These changes were supported by observed variations in anthocyanin and flavonoid contents, both higher at the CM stage. A notable pigment loss in OM fruits could be attributed to pH changes, oxidative degradation, enzymatic activity loss, and biotic stressors. Antioxidant assays (DPPH, ABTS, and FRAP) confirmed higher radical scavenging activity in CM-stage berries. Elemental analysis identified minerals such as potassium, calcium, magnesium, iron, and zinc, although in moderate concentrations. In summary, Syzygium paniculatum Gaertn fruit demonstrates considerable potential as a source of natural antioxidants and bioactive compounds. These findings advocate for greater exploration and sustainable use of this native berry species in functional food systems.

Furrow irrigation is widely practiced in arid and semi-arid regions but suffers from low efficiency due to infiltration variability and water losses. This systematic review analysed 92 peer-reviewed studies (2017–2024) on short-cycle crops, identified through a reproducible search of five bibliographic databases (Scopus, Web of Science, IEEE Xplore, SpringerLink, ScienceDirect) supplemented by a manually directed search of publisher platforms, following Kitchenham & Charters’ protocol. Study quality was assessed narratively, based on validation against field data and comparison with established simulation software (SIRMOD, WinSRFR), rather than through a formal quality-appraisal tool. The narrative synthesis indicates that optimized irrigation techniques achieve efficiency gains ranging from 20% to over 50% relative to conventional practice, depending on crop, soil, and technology, addressing the two operational questions that determine furrow-irrigation performance: when to irrigate and how much water to apply. Advances were identified in coupled surface–subsurface modelling, soil moisture prediction, sensor-driven scheduling, and water–plant–atmosphere interaction. Persistent limitations include scarce field validation beyond single-furrow, single-season conditions, limited generalization across agroclimatic contexts, and interpretability challenges in machine learning (ML) models. Future research should prioritize embedding physical constraints into AI architectures, routine uncertainty quantification, multi-plot and multi-season validation, and pairing technological development with affordable hardware and farmer training to strengthen reproducibility and practical adoption in irrigation science.