This paper presents the design, implementation, and evaluation of a fuzzy logic-based adaptive lighting strategy for Phaseolus vulgaris cultivation. The objective of this study was to integrate an image-derived plant growth indicator obtained through projected leaf-area estimation into an adaptive pulse-width modulation framework. The proposed system used two input variables: the error between the desired and measured Photosynthetic Photon Flux Density (PPFD) and the estimated projected leaf area. PPFD was indirectly estimated from illuminance measurements acquired using a BH1750 sensor (ROHM Semiconductor, Kyoto, Japan) Mostrar más líneas connected to an Arduino Uno microcontroller, while projected leaf area was obtained from RGB images captured with an Intel RealSense D435 camera and processed in MATLAB R2021a. The fuzzy inference system was implemented using the Mamdani approach and the Fuzzy Logic Designer application. The experimental results showed that the system regulated the PWM signal within a range of 17.00% to 87.85%, corresponding to a power range of 13.65 W to 34.58 W. The projected leaf-area indicator increased from 284.94 cm² to 392.57 cm² during the 21-day evaluation period, representing a relative increase of 37.77%. These findings provide preliminary evidence supporting the integration of image-derived projected leaf-area information, illuminance sensing, and fuzzy logic for adaptive lighting regulation in controlled-environment cultivation systems.

Water stress is a critical limiting factor in horticultural crop productivity. This study presents a non-invasive approach for detecting water stress in jalapeño pepper (Capsicum annuum L. var. Huichol) through visible–near-infrared (VIS-NIR) imaging-based quantification of the foliar vascular network under controlled conditions. Nine plants were subjected to three irrigation regimes (100%, 50%, and 0% of daily water loss) and monitored over 13 days, acquiring VIS-NIR and LWIR images under light and darkness conditions. Using a digital image processing pipeline, foliar vascular networks were segmented from VIS-NIR images, and the vascular proportion index ($R_v$) was computed. A factorial ANOVA revealed significant main effects for irrigation treatment ($F$ = 11.01, $p$ < 0.001), illumination ($F$ = 13.01, $p$ < 0.001), and spectral modality ($F$ = 422.77, $p$ < 0.001), with the spectral band accounting for the highest variance (${\eta }_p^2$ = 0.079). The VIS-NIR + Light configuration produced the clearest treatment discrimination, with significant pairwise differences between 50% WL and both 100% WL ($MD$ = 0.025, $p$ < 0.0001) and 0% WL ($MD$ = 0.020, $p$ = 0.0001). This VIS-NIR-based technique offers a practical, scalable alternative for real-time monitoring of plant water status in horticultural systems.