Summary: A new proliferation of optical instruments that can be attached to towers over or within ecosystems, or ‘proximal’ remote sensing, enables a comprehensive characterization of terrestrial ecosystem structure, function, and fluxes of energy, water, and carbon. Proximal remote sensing can bridge the gap between individual plants, site‐level eddy‐covariance fluxes, and airborne and spaceborne remote sensing by providing continuous data at a high‐spatiotemporal resolution. Here, we review recent advances in proximal remote sensing for improving our mechanistic understanding of plant and ecosystem processes, model development, and validation of current and upcoming satellite missions. We provide current best practices for data availability and metadata for proximal remote sensing: spectral reflectance, solar‐induced fluorescence, thermal infrared radiation, microwave backscatter, and LiDAR. Our paper outlines the steps necessary for making these data streams more widespread, accessible, interoperable, and information‐rich, enabling us to address key ecological questions unanswerable from space‐based observations alone and, ultimately, to demonstrate the feasibility of these technologies to address critical questions in local and global ecology.

Introduction: Detecting and monitoring crop stress is crucial for ensuring sufficient and sustainable crop production. Recent advancements in unoccupied aerial vehicle (UAV) technology provide a promising approach to map key crop traits indicative of stress. While using single optical sensors mounted on UAVs could be sufficient to monitor crop status in a general sense, implementing multiple sensors that cover various spectral optical domains allow for a more precise characterization of the interactions between crops and biotic or abiotic stressors. Given the novelty of synergistic sensor technology for crop stress detection, standardized procedures outlining their optimal use are currently lacking. Materials and methods: This study explores the key aspects of acquiring high-quality multi-sensor data, including the importance of mission planning, sensor characteristics, and ancillary data. It also details essential data pre-processing steps like atmospheric correction and highlights best practices for data fusion and quality control. Results: Successful multi-sensor data acquisition depends on optimal timing, appropriate sensor calibration, and the use of ancillary data such as ground control points and weather station information. When fusing different sensor data it should be conducted at the level of physical units, with quality flags used to exclude unstable or biased measurements. The paper highlights the importance of using checklists, considering illumination conditions and conducting test flights for the detection of potential pitfalls. Conclusion: Multi-sensor campaigns require careful planning not to jeopardise the success of the campaigns. This paper provides practical information on how to combine different UAV-mounted optical sensors and discuss the proven scientific practices for image data acquisition and post-processing in the context of crop stress monitoring.

Karrikins (KARs) have been identified as molecules derived from plant material smoke, which have the capacity to enhance seed germination for a wide range of plant species. However, KARs were observed to not only impact seed germination but also observed to influence several biological processes. The plants defected in the KARs signaling pathway were observed to grow differently with several morphological changes. The observation of KARs as a growth regulator in plants leads to the search for an endogenous KAR-like molecule. Due to its simple genomic structure, Arabidopsis (Arabidopsis thaliana L.) helps to understand the signaling mechanism of KARs and phenotypic responses caused by them. However, different species have a different phenotypic response to KARs treatment. Therefore, in the current work, updated information about the KARs effect is presented. Results of research on agricultural and horticultural crops are summarized and compared with the findings of Arabidopsis studies. In this article, we suggested that KARs may be more important in coping with modern problems than one could imagine.

The present study aimed to evaluate fresh spent mushroom substrate (SMS) as a growing medium in soilless strawberry cv. ‘Honeoye’ production. Fresh SMS after commercial production of Agaricus bisporus, Lentinus edodes, and Pleurotus ostreatus was used as a peat substitute in 15 and 25% (v/v), for strawberry cultivation in an unheated plastic tunnel. In the experiment, seven different substrates were studied, including peat (100%) as control and six substrate combinations (prepared by mixing SMSs with peat). The study was carried out in a randomized complete block design in five replicates. The results indicated that the electrical conductivity (EC), pH, and nutrient content varied among the studied substrates. The experiment also demonstrated that the substrates significantly influenced strawberry yield, leaf area, and fresh and dry plant weights. However, no significant differences were observed for selected photosynthetic parameters (F_v/F_m, F_v/F₀, and PI_abs) and Normalized Difference Vegetation Index (NDVI) values among the evaluated substrates. Differences were recorded for the Photochemical Reflectance Index (PRI) and Modified Chlorophyll Absorption in Reflectance Index (MCARI) values. The present investigation revealed that fresh SMSs can be an effective and inexpensive peat substitute in 15 and 25% (v/v). Therefore, such easy and immediate utilisation of SMSs could overcome associated disposal problems.

Solar-induced chlorophyll fluorescence (SIF) is closely related to plant photosynthetic activity and has been used in different studies as a proxy for vegetation health status. However, in order to use SIF as a relevant indicator of plant physiological stress, it is necessary to accurately quantify the amount of light absorbed by the photosynthetic plant pigments, called the absorbed photosynthetically active radiation (APAR). The ratio between fluorescence emission and light absorption (i.e., SIF and APAR) is known as the fluorescence quantum efficiency (FQE). In this work, simultaneous measurements of SIF and reflected radiance were performed both at the leaf and canopy levels for Salvia farinacea and Datura stramonium plants. With the aim of disentangling the proportion of sunlit and shaded absorbed PAR, an ad hoc experimental setup was designed to provide a wide range of fraction vegetation cover (FVC) canopy settings. A linear spectral unmixing method was proposed to estimate the contribution of soil, sunlit, and shaded vegetation from the total reflectance spectrum measured at the canopy level. Later, the retrieved sunlit FVC (FVC_sunlit) was used to estimate the (dominant) green APAR flux, and this was combined with the integral of the spectrally resolved fluorescence to calculate the FQE. The results of this study demonstrated that under no-stress conditions and independently of the FVC, similar FQE values were observed when SIF was properly normalised by the green APAR flux. The results obtained showed that the reflectance spectra retrieved using a linear unmixing method had a maximum RMSE of less than 0.03 along the spectrum. The FVC_sunlit evaluation showed an RMSE of 14% with an R² of 0.84. Moreover, the FQE values obtained at the top of the canopy (TOC) were found statistically comparable to the reference values at the leaf level. These results support further efforts to improve the interpretation of fluorescence based on field spectroscopy and the further upscaling to imaging spectroscopy at airborne and satellite levels.