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The avocado cv. Hass requires a suitable rootstock for optimal development under water stress. This study evaluated the performance of two avocado rootstocks (ANRR88 and ANGI52) grafted onto cv. Hass under four water stress conditions, 50% and 25% deficit, and 50% and 25% excess during the nursery stage. Plant height, leaf area (LA), dry matter (DM), and Carbon (OC) content in the roots, stems, and leaves were measured. Root traits were evaluated using digital imaging, and three vegetation indices (NDVI, CI RE , and MTCI) were used to quantify stress. The results showed that genotype significantly influenced the response to water stress. ANRR88 exhibited adaptation to moderate to high water deficits. ANGI52 adapted better to both water deficit and excess, and showed greater root exploration. LA and DM reductions of up to 60% were observed in ANRR88, suggesting a higher sensitivity to extreme changes in water availability. More than 90% of the total OC accumulation was observed in the stem and roots. The NDVI and the MTCI quantified the presence and levels of stress applied, and the 720 nm band provided high precision and speed for detecting stress. These insights are crucial for selecting rootstocks that ensure optimal performance under varying water availability, enhancing productivity and sustainability.

Spectral signatures allow the characterization of a surface from the reflected or emitted energy along the electromagnetic spectrum. This type of measurement has several potential applications in precision agriculture. However, capturing the spectral signatures of plants requires specialized instruments, either in the field or the laboratory. The cost of these instruments is high, so their incorporation in crop monitoring tasks is not massive, given the low investment in agricultural technology. This paper presents a low-cost clamp to capture spectral leaf signatures in the laboratory and the field. The clamp can be 3D printed using PLA (polylactic acid); it allows the connection of 2 optical fibers: one for a spectrometer and one for a light source. It is designed for ease of use and holds a leave firmly without causing damage, allowing data to be collected with less disturbance. The article compares signatures captured directly using a fiber and the proposed clamp; noise reduction across the spectrum is achieved with the clamp., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

Cutaneous leishmaniasis (CL) is a neglected disease caused by an intracellular parasite of the Leishmania genus. CL lacks tools that allow its understanding and treatment follow-up. This article presents the use of metrical and optical tools for the analysis of the temporal evolution of treated skin ulcers caused by CL in an animal model. Leishmania braziliensis and L. panamensis were experimentally inoculated in golden hamsters, which were treated with experimental and commercial drugs. The temporal evolution was monitored by means of ulcers' surface areas, as well as absorption and scattering optical parameters. Ulcers' surface areas were obtained via photogrammetry, which is a procedure that allowed for 3D modeling of the ulcer using specialized software. Optical parameters were obtained from a spectroscopy study, representing the cutaneous tissue's biological components. A one-way ANOVA analysis was conducted to identify relationships between both the ulcers' areas and optical parameters. As a result, ulcers' surface areas were found to be related to the following optical parameters: epidermis thickness, collagen, keratinocytes, volume-fraction of blood, and oxygen saturation. This study is a proof of concept that shows that optical parameters could be associated with metrical ones, giving a more reliable concept during the assessment of a skin ulcer's healing.

Cutaneous leishmaniasis (CL) is a parasitic disease that produces chronic skin ulcers. Although it has a worldwide presence, it is a neglected disease that still requires novel tools for its management. In order to study the use of optical tools in CL, this article presents a preliminary study of the correlation between CL histopathological and optical parameters. Optical parameters correspond to absorption and scattering coefficients obtained from diffuse reflectance spectra of treated CL in golden hamsters. Independently, histopathological data were collected from the same hamsters. As a result, after Spearman correlation and the Kruskal-Wallis test, inverse correlation was found between absorption/scattering optical parameters and inflammatory histopathological values, such as the scattering parameter related to the diameter of fibroblasts with the histopathological parameters of fibrosis, polymorphonuclear neutrophils, lymphocytes, plasmocytes, hyperplasia, and Leishmania , and the absorption parameter oxygen saturation showed a relation with the granulation tissue histopathological parameter. These correlations agree with the expected behavior of tissue composition during the healing process in CL. The results correspond to a proof of concept that shows that optical diffuse reflectance-based tools and methods could be considered as an alternative to assist in CL diagnosis and treatment follow-up.

Background: Two-dimensional gel electrophoresis (2-DGE) is a commonly used tool for proteomic analysis. This gel-based technique separates proteins in a sample according to their isoelectric point and molecular weight. 2-DGE images often present anomalies due to the acquisition process, such as: diffuse and overlapping spots, and background noise. This study proposes a joint pre-processing framework that combines the capabilities of nonlinear filtering, background correction and image normalization techniques for pre-processing 2-DGE images. Among the most important, joint nonlinear diffusion filtering, adaptive piecewise histogram equalization and multilevel thresholding were evaluated using both synthetic data and real 2-DGE images., Results: An improvement of up to 46% in spot detection efficiency was achieved for synthetic data using the proposed framework compared to implementing a single technique of either normalization, background correction or filtering. Additionally, the proposed framework increased the detection of low abundance spots by 20% for synthetic data compared to a normalization technique, and increased the background estimation by 67% compared to a background correction technique. In terms of real data, the joint pre-processing framework reduced the false positives up to 93%., Conclusions: The proposed joint pre-processing framework outperforms results achieved with a single approach. The best structure was obtained with the ordered combination of adaptive piecewise histogram equalization for image normalization, geometric nonlinear diffusion (GNDF) for filtering, and multilevel thresholding for background correction.

Cutaneous leishmaniasis (CL) is a neglected tropical disease that requires novel tools for its understanding, diagnosis, and treatment follow-up. In the cases of other cutaneous pathologies, such as cancer or cutaneous ulcers due to diabetes, optical diffuse reflectance-based tools and methods are widely used for the investigation of those illnesses. These types of tools and methods offer the possibility to develop portable diagnosis and treatment follow-up systems. In this article, we propose the use of a three-layer diffuse reflectance model for the study of the formation of cutaneous ulcers caused by CL. The proposed model together with an inverse-modeling procedure were used in the evaluation of diffuse-reflectance spectral signatures acquired from cutaneous ulcers formed in the dorsal area of 21 golden hamsters inoculated with Leishmanisis braziliensis. As result, the quantification of the model's variables related to the main biological parameters of skin were obtained, such as: diameter and volumetric fraction of keratinocytes, collagen; volumetric fraction of hemoglobin, and oxygen saturation. Those parameters show statistically significant differences among the different stages of the CL ulcer formation. We found that these differences are coherent with histopathological manifestations reported in the literature for the main phases of CL formation.