Early water stress detection is important for water use yield and sustainability. Traditional methods using the Internet of Things (IoT), such as soil moisture sensors, usually do not provide timely alerts, causing inefficient water use and, in some cases, crop damage. This research presents an innovative early water stress detection method in lettuce plants using Thermal Infrared (TIR) and RGB images in a controlled lab setting. The proposed method integrates advanced image processing techniques, including background elimination via Hue-Saturation- Value (HSV) thresholds, wavelet denoising for thermal image enhancement, RGB-TIR fusion using Principal Component Analysis (PCA), and Gaussian Mixture Model (GMM) clustering to segment stress regions. The leaves stressed areas annotated in the RGB image through yellow pseudo-coloring. This approach is predicated on the fact that when stomata close, transpiration decreases, which causes an increase in the temperature of the affected area. Experimental results reveal that this new approach can detect water stress up to 84 h earlier than conventional soil humidity sensors. Also, a comparative analysis was conducted where key components of the proposed hybrid framework were omitted. The results show inconsistent and inaccurate stress detection when excluding wavelet denoising and PCA fusion. A comparative analysis of image processing performed on a single- board computer (SBC) and through cloud computing over 5 G showed that SBC was 8.27% faster than cloud computing over a 5 G connection. The proposed method offers a more timely and accurate identification of water stress and promises significant benefits in improving crop yield and reducing water usage in indoor farming.

Although it has been recognized that soil structure formation affects soil organic carbon (SOC) sequestration, experimental data elucidating the relation between mechanical properties of soil structure and soil organic matter (SOM) stability are lacking. This study assesses the link between aggregate stability and SOM stability in lowland and hilly land soils of Central Europe. Overall, 39 topsoil samples were taken. Besides determining basic properties and nutrient availability, stability of soil aggregates was quantified using wet sieving (WS) and rainfall simulation (RS) procedures. The samples were analyzed by thermogravimetry and differential scanning calorimetry (TG-DSC). Besides significant correlations with basic soil properties and contents of selected nutrients, the aggregate stability data were linked to thermal processes, such as water desorption and SOM degradation. The RS values were significantly correlated (r > 0.7, p < 0.001) with the rate of water desorption (T < 200 degrees C) and SOM degradation (200 - 570 degrees C). Observed correlation pattern, with multiple maxima, suggests that aggregate stability is supported by clay and several SOM fractions, each showing different thermal stability. Significant correlations observed bellow 200 degrees C indicate that properties controlling soil specific surface area (SOM and clay) are important also for the aggregate stability. The 78 % of the variance observed in aggregate stability testing was explained by multilinear regression using weight loss rates recorded at selected temperatures (80, 130, 248, 401 and 455 degrees C) as predictors. We observed different relations between exothermic energy values, soil aggregate stability and thermal stability of SOM (SOC). Exothermic heat flux normalized with respect to SOC mass (energy density) indicates presence of stable organic fraction, as it showed correlation also with clay, which has positive effect on SOC stabilization. This is in line with the positive correlation between SOC energy density and aggregate stability. On contrary, normalizing the heat with respect to SOM mass indicates the content of labile organic components, as the correlations with clay or aggregate stability were insignificant. The TG-DSC data revealed that hilly land soils are depleted in fresh organic material, which is due to their genesis and the erosion intensified by tillage.

Bio-based polymers are a promising material with which to tackle the use of disposable and non-degradable plastics in agriculture, such as mulching films. However, their poor mechanical properties and the high cost of biomaterials have hindered their widespread application. Hence, in this study, we improved polysaccharide-based films and enriched them with plant nutrients to make them suitable for mulching and fertilizing. Films were produced combining sodium carboxymethyl cellulose (CMC), chitosan (CS), and sodium alginate (SA) at different weight ratios with glycerol and CaCl2 as a plasticizer and crosslinker, respectively, and enriched with ammonium phosphate monobasic (NH4H2PO4). A polysaccharide weight ratio of 1:1 generated a film with a more crosslinked structure and a lower expanded network than that featuring the 17:3 ratio, whereas CaCl2 increased the films' water resistance, thermal stability, and strength characteristics, slowing the release rates of NH4+ and PO43-. Thus, composition and crosslinking proved crucial to obtaining promising films for soil mulching.

Poly(lactic acid) fiberwebs and multi-ply assemblies of nettle woven reinforcement are used to develop a series of nettle/PLA biocomposites with different reinforcement orientations. The tensile strength, flexural strength, impact strength, and thermal properties of the biocomposites are found to improve by piling nettle fabrics and are also found to depend strongly on the piling architecture and the test direction. It is possible to obtain a biocomposite with higher degrees of isotropy and enhanced mechanical properties by using cross-ply laminates. The threelayered woven fabric reinforced PLA biocomposite with a reinforcement orientation 0 degrees/45 degrees/90 degrees shows the best results among all the biocomposites developed in this study. The tensile strength, Young's (tensile) modulus, flexural strength, impact strength, storage modulus, and loss modulus of the biocomposite are found as 55.25 MPa, 6.30 GPa, 85.83 MPa, 63.74 J/m(2), 10.08 GPa, and 0.75 GPa, respectively. In this biocomposite, a fair adhesion between matrix and reinforcement is noticed, and this is justified by retardation of crack propagation as well as by substantial energy dissipation. The thermal stability of the biocomposite does not get effected much, but the percent crystallinity increases by 25.84%. The degradation kinetics and the activation energy of the biocomposite are determined through a differential fitting of Arrhenius model. The soil burial test reveals 15.06% of weight loss and 50.56% strength loss for this biocomposite just after 20 days of burial under soil.

Vegetation affects the water balance in the root zone, leading to changes in pore water pressure in the soil. Despite the tendency of numerical models to overlook the vegetation impact on the soil surface, this study concentrates on creating a unique boundary condition to model the intricate interactions among soil, vegetation, and the atmosphere by considering hydraulic hysteresis. Hence, a boundary condition is integrated into Code_Bright, a finite element program designed for conducting thermo-hydraulic-mechanical simulations, enabling the computation of energy and water balance equations. The canopy resistance formulation is refined through links with solar radiation, vapor pressure deficit, and saturation degree. The model also incorporates a bounding surface approach to capture the hysteretic patterns in soil-water retention curves. The model performance is assessed by monitoring data of a full-scale slope under atmospheric forces for nearly three years. The outcomes demonstrate that the model can reasonably predict the vegetation cover impact on the thermal behavior of slopes. The slope response to rainfall infiltration and its interaction with the atmosphere demonstrated that vegetation plays a significant role in thermo-hydraulic variables. Daily temperature fluctuations are notably intense at shallow depths, particularly within the root zone, while diminishing at greater depths. Due to the incidence angles of solar radiation, the model accurately predicts higher temperatures on south-facing slopes compared to north-facing slopes. In high temperatures and low rainfall durations, the influence of the vegetation layer to develop dryer soil conditions is also more substantial than the slope orientation.