Full Spectrum Research Articles

Publishing a Research: Shared Experiences of Preservice Teachers as Novice Researchers in Research Journals

<p style="text-align: justify;">Publishing research is crucial and is of utmost significance. However, it is a daunting task for most researchers, especially if one is a beginner with very limited experience. The generalizability of much of the previously published research was limited to the negative aspects of the publishing process rather than the whole circumstances they had to face. Therefore, this article sought to explore the experiences of preservice teachers as novice researchers in publishing their research outputs in a research journal. This study employed a qualitative-phenomenological approach. Five major themes emerged from the interview with eight purposively selected former preservice teachers who had first-time encounters in publishing that the research investigates. These themes were encapsulated through the acronym “FLAME,” namely: (a) facing personal circumstances, (b) leveraging positive dispositions, (c) acknowledging dependency on research promoter, (d) meeting publishing standards, and (e) encountering poor physical and mental well-being. This article concludes that the journal publishing process is a multidimensional and enriching experience, providing the full spectrum of positive and negative experiences for novice researchers. This paper highlighted some implications that can be used as a guide to support novice researchers in the publication process.</p>

Effect of solar radiation and full spectrum artificial sun light drying on the drying characteristics, ultra-structural and textural properties of white radish (Raphanus sativus L.)

Traditional sun drying has long been employed as a method for preserving radishes (Raphanus sativus L.) However, it suffers from various uncertainties, including weather-related factors such as rain and cloudy days, the pressing issue of climatic change can lead to an impact on the traditional drying process and texture of radish. In this research, the full spectrum artificial sunlight drying (FSASLD) has been implemented to simulate the traditional open sun drying of white radish slices which helps to prevent hygienic issues and unstable climatic conditions. Water activity (Aw) was measured and observed to decrease from 0.89 to 0.60 under both drying methods, indicating the removal of moisture from radish cells. Mathematical modelling and color kinetics models were studied with respect to drying time. Texture Profile Analysis (TPA) was employed to assess hardness, and results showed an increase in hardness following both SD (1018.24 g to 1327.67 g) and FSASLD (1018.24 g to 1731.04 g) salt treated radish slices. These findings suggest that FSASLD can serve as a viable alternative to the conventional drying method and contributes to agricultural innovation and the food industry, reducing drying time significantly from 270 min to 200 min and minimizing the impact of adverse weather conditions and interference from animals and microorganisms.

Photocatalytic CO2 Reduction Using Homogeneous Carbon Dots with a Molecular Cobalt Catalyst.

A simple and precious-metal free photosystem for the reduction of aqueous CO2 to syngas (CO and H2) is reported consisting of carbon dots (CDs) as the sole light harvester together with a molecular cobalt bis(terpyridine) CO2 reduction co-catalyst. This homogeneous photocatalytic system operates in the presence of a sacrificial electron donor (triethanolamine) in DMSO/H2O solution at ambient temperature. The photocatalytic system exhibits an activity of 7.7 ± 0.2 mmolsyngas gCDs -1 (3.6 ± 0.2 mmolCO gCDs -1 and 4.1 ± 0.1 mmolH2 gCDs -1) after 24hours of full solar spectrum irradiation (AM 1.5G). Spectroscopic and electrochemical characterization supports that this photocatalytic performance is attributed to a favorable association between CDs and the molecular cobalt catalyst, which results in improved interfacial photoelectron transfer and catalytic mechanism. This work provides a scalable and inexpensive platform for the development of CO2 photoreduction systems using CDs.

High-Entropy Photothermal Materials.

High-entropy (HE) materials, celebrated for their extraordinary chemical and physical properties, have garnered increasing attention for their broad applications across diverse disciplines. The expansive compositional range of these materials allows for nuanced tuning of their properties and innovative structural designs. Recent advances have been centered on their versatile photothermal conversion capabilities, effective across the full solar spectrum (300-2500nm). The HE effect, coupled with hysteresis diffusion, imparts these materials with desirable thermal and chemical stability. These attributes position HE materials as a revolutionary alternative to traditional photothermal materials, signifying a transformative shift in photothermal technology. This review delivers a comprehensive summary of the current state of knowledge regarding HE photothermal materials, emphasizing the intricate relationship between their compositions, structures, light-absorbing mechanisms, and optical properties. Furthermore, the review outlines the notable advances in HE photothermal materials, emphasizing their contributions to areas, such as solar water evaporation, personal thermal management, solar thermoelectric generation, catalysis, and biomedical applications. The review culminates in presenting a roadmap that outlines prospective directions for future research in this burgeoning field, and also outlines fruitful ways to develop advanced HE photothermal materials and to expand their promising applications.

Full harmonic spectrum calculation of magnetic pressures in synchronous permanent magnet machines based on a new realistic partial analytical model: application to SVPWM and DPWM2

Purpose The purpose of this paper is to propose a new method that allows to compare the magnetic pressures of different pulse width modulation (PWM) strategies in a fast and efficient way. Design/methodology/approach The voltage harmonics are determined using the double Fourier integral. As for current harmonics and waveforms, a new generic model based on the Park transformation and a dq model of the machine was established taking saturation into consideration. The obtained analytical waveforms are then injected into a finite element software to compute magnetic pressures using nodal forces. Findings The overall proposed method allows to accelerate the calculations and the comparison of different PWM strategies and operating points as an analytical model is used to generate current waveforms. Originality/value While the analytical expressions of voltage harmonics are already provided in the literature for the space vector pulse width modulation, they had to be calculated for the discontinuous pulse width modulation. In this paper, the obtained expressions are provided. For current harmonics, different models based on a linear and a nonlinear model of the machine are presented in the referenced papers; however, these models are not generic and are limited to the second range of harmonics (two times the switching frequency). A new generic model is then established and used in this paper after being validated experimentally. And finally, the direct injection of analytical current waveforms in a finite element software to perform any magnetic computation is very efficient.

More yeast, more problems?: reevaluating the role of Malassezia in seborrheic dermatitis.

Seborrheic dermatitis (SD) is an inflammatory skin disorder and eczema subtype increasingly recognized to be associated with significant physical, psychosocial, and financial burden. The full spectrum of SD, including dandruff localized to the scalp, is estimated to affect half of the world's population. Despite such high prevalence, the exact etiopathogenesis of SD remains unclear. Historically, many researchers have theorized a central, causative role of Malassezia spp. based on prior studies including the proliferation of Malassezia yeast on lesional skin of some SD patients and empiric clinical response to antifungal therapy. However, upon closer examination, many of these findings have not been reproducible nor consistent. Emerging data from novel, targeted anti-inflammatory therapeutics, as well as evidence from genome-wide association studies and murine models, should prompt a reevaluation of the popular yeast-centered hypothesis. Here, through focused review of the literature, including laboratory studies, clinical trials, and expert consensus, we examine and synthesize the data arguing for and against a primary role for Malassezia in SD. We propose an expansion of SD pathogenesis and suggest reframing our view of SD to be based primarily on dysregulation of the host immune system and skin epidermal barrier, like other eczemas.

Bridging semantics and medical ontology in the definition of bruxism: An argument for a holistic definition.

The objective of this commentary is to advocate for a holistic, ontology-based definition of bruxism. The intention is to synthesise the best aspects of current definitions into a structured ontological model, thereby refining and enhancing a comprehensive understanding of the full spectrum of bruxism. The commentary elaborates on the process of integrating these insights into a hierarchical ontology that aligns with ontological principles. Not directly applicable as this is a commentary. The proposed ontology-based definition of bruxism aims to clarify communication within the medical community and advance research by enabling a comprehensive ontology-based classification of bruxism. By aligning with ontological principles, this approach aspires to act as a catalyst for further research, discussion and consensus in the field.

Constructing a Titanium Silicon Molecular Sieve-Based Z-Scheme Heterojunction with Enhanced Photocatalytic Activity.

Titanium silicon molecular sieve (TS-1) is an oxidation catalyst that possesses a long lifetime of charge transfer excited state, high Ti utilization efficiency, large specific surface area, and good adsorption property; therefore, TS-1 acts as a Ti-based photocatalyst candidate. In this work, TS-1 coupled Bi2MoO6 (TS-1/BMO) photocatalysts were fabricated via a facile hydrothermal route. Interestingly, the optimized TS-1/BMO-1.0 catalyst exhibited a decent photodegradation property toward tetracycline hydrochloride (85.49% in 120 min) under the irradiation of full spectrum light, which were 4.38 and 1.76 times compared to TS-1 and BMO, respectively. The enhanced photodegradation property of the TS-1/BMO-1.0 catalyst could be attributed to the reinforced light-harvesting capacity of the photocatalyst, high charge mobility, and suitable band structure for tetracycline hydrochloride degradation. In addition, the mechanism of photocatalytic degradation of tetracycline hydrochloride by the TS-1/BMO-1.0 catalyst was reasonably proposed based on the band structure, trapping, and ESR tests. This research provided feasible ideas for the design and construction of high-efficiency photocatalysts for contaminant degradation.

FOXG1 variants can be associated with milder phenotypes than congenital Rett syndrome with unassisted walking and language development.

Since 2008, FOXG1 haploinsufficiency has been linked to a severe neurodevelopmental phenotype resembling Rett syndrome but with earlier onset. Most patients are unable to sit, walk, or speak. For years, FOXG1 sequencing was only prescribed in such severe cases, limiting insight into the full clinical spectrum associated with this gene. Next-generation sequencing (NGS) now enables unbiased diagnostics. Through the European Reference Network for Rare Malformation Syndromes, Intellectual and Other Neurodevelopmental Disorders, we gathered data from patients with heterozygous FOXG1 variants presenting a mild phenotype, defined as able to speak and walk independently. We also reviewed data from three previously reported patients meeting our criteria. We identified five new patients with pathogenic FOXG1 missense variants, primarily in the forkhead domain, showing varying nonspecific intellectual disability and developmental delay. These features are not typical of congenital Rett syndrome and were rarely associated with microcephaly and epilepsy. Our findings are consistent with a previous genotype-phenotype analysis by Mitter et al. suggesting the delineation of five different FOXG1 genotype groups. Milder phenotypes were associated with missense variants in the forkhead domain. This information may facilitate prognostic assessments in children carrying a FOXG1 variant and improve the interpretation of new variants identified with genomic sequencing.

Variability in spectral absorption within cryptophyte phycobiliprotein types.

Cryptophytes are known to vary widely in coloration among species. These differences in color arise primarily from the presence of phycobiliprotein accessory pigments. There are nine defined cryptophyte phycobiliprotein (Cr-PBP) types, named for their wavelength of maximal absorbance. Because Cr-PBP type has traditionally been regarded as a categorical trait, there is a paucity of information about how spectral absorption characteristics of Cr-PBPs vary among species. We investigated variability in primary and secondary peak absorbance wavelengths and full width at half max (FWHM) values of spectra of Cr-PBPs extracted from 75 cryptophyte strains (55 species) grown under full spectrum irradiance. We show that there may be substantial differences in spectral shapes within Cr-PBP types, with Cr-Phycoerythrin (Cr-PE) 545 showing the greatest variability with two, possibly three, subtypes, while Cr-PE 566 spectra were the least variable, with only ±1 nm of variance around the mean absorbance maximum of 565 nm. We provide additional criteria for classification in cases where the wavelength of maximum absorbance alone is not definitive. Variations in spectral characteristics among strains containing the same presumed Cr-PBP type may indicate differing chromophore composition and/or the presence of more than one Cr-PBP in a single cryptophyte species.

ESPRAS Survey: National and European Societies for Plastic Surgeons.

The European Society of Plastic, Reconstructive and Aesthetic Surgery (ESPRAS) comprises 40 national societies across Europe. In addition to ESPRAS, there are 8 different European Plastic Surgery societies representing Plastic Surgeons in Europe. The 4th European Leadership Forum (ELF) of ESPRAS, held under the motto "Stronger together in Europe" in Munich in 2023, aimed to collect and disseminate information regarding the national member societies of ESPRAS and European societies for Plastic Surgeons. The purpose was to identify synergies and redundancies and promote improved cooperation and exchange to enhance coordinated decision-making at the European level. An online survey was conducted regarding the organisational structures, objectives and challenges of national and European societies for Plastic Surgeons in Europe. This survey was distributed to official representatives (Presidents, Vice Presidents and General Secretaries) and delegates of national and European societies at the ELF meeting. Missing information was completed using data obtained from the official websites of the respective European societies. Preliminary results were discussed during the 4th ELF meeting in Munich in March 2023. The ESPRAS survey included 22 national and 9 European Plastic Surgery societies representing more than 7000 Plastic Surgeons in Europe. Most national societies consist of less than 500 full members (median 182 members (interquartile range (IQR) 54-400); n=22). European societies, which covered the full spectrum or subspecialities, differed in membership types and congress cycles, with some requiring applications by individuals and others including national societies. The main purposes of the societies include research, representation against other disciplines, specialisation and education as well as more individual goals like patient care and policy regulation. This ESPRAS survey offers key insights into the structures, requirements and challenges of national and European societies for Plastic Surgeons, highlighting the relevance of ongoing close exchange between the societies to foster professional advancement and reduce redundancies. Future efforts of the ELF will continue to further explore strategies for enhancing collaboration and harmonisation within the European Plastic Surgery landscape.

Navigating fertility dilemmas across the lifespan in girls with Turner syndrome-a scoping review.

Girls with Turner syndrome (TS) lack a partial or complete sex chromosome, which causes an accelerated decline of their ovarian reserve. Girls have to deal with several dilemmas related to their fertility, while only a limited number of them are referred to a fertility specialist and counselled about options of family planning on time. This scoping review provides an update of the literature on fertility in girls with TS throughout their lifespan and aims to propose a clinical practice guideline on fertility in TS. Databases of PubMed, Embase, and Web of science were searched using the following key terms: Turner syndrome, fertility, puberty, pregnancy, sex-hormones, karyotype, fertility preservation, assisted reproductive techniques, and counselling, alongside relevant subject headings and synonymous terms. English language articles published since 2007 were critically reviewed. Pregnancies after using donated oocytes and data about girls with TS with Y-chromosomal content were excluded. This search identified 1269 studies of which 120 were extracted for the review. The prevalence of natural conception ranged from 15% to 48% in women with 45,X/46,XX, 1% to 3% in women with 45,X, and 4% to 9% in women with other TS karyotypes. When assessing a girl's fertility potential, it was crucial to determine the karyotype in two cell lines, because hidden mosaicism may exist. In addition to karyotype, assessment of anti-Müllerian hormone (AMH) played a significant role in estimating ovarian function. Girls with AMH above the detection limit were most likely to experience spontaneous thelarche, menarche, and ongoing ovarian function during the reproductive lifespan. Fertility preservation became more routine practice: vitrification of oocytes was reported in 58 girls with TS and a median of five oocytes were preserved per stimulation. Ovarian tissue cryopreservation has demonstrated the presence of follicles in approximately 30% of girls with TS, mostly in girls with mosaic-TS, spontaneous puberty, and AMH above the detection limit. Although girls and their parents appreciated receiving counselling on fertility in TS, only one in ten girls with TS received specialized counselling. Unfamiliarity with fertility preservation techniques or uncertainties regarding the eligibility of a girl for fertility preservation constituted barriers for healthcare professionals when discussing fertility with girls with TS. There currently is a high demand for fertility preservation techniques in girls with TS. A reliable prognostic model to determine which girls with TS might benefit from fertility preservation is lacking. Only a minority of these girls received comprehensive fertility counselling on the full spectrum of fertility, including uncertainties of fertility preservation, pregnancy risks, and alternatives, such as adoption. Fertility preservation could be a viable option for girls with TS. However, the question remains whether enough oocytes can be obtained for a realistic prospect of a live birth. It is important that girls and parents are empowered with the necessary information to make a well-informed decision.

Fetal diagnosis and management of pulmonary artery sling: Acase series.

Pulmonary artery sling is a rare congenital anomaly accounting for 2% of all patients with vascular anomalies that cause airway obstruction. In the normal heart, the left (LPA) and right (RPA) pulmonary arteries arise in the intrapericardial space. However, in the pulmonary artery sling, the LPA trunk arises in the extrapericardial space from the posterior aspect of the mid RPA and courses posterior to the trachea causing tracheal compression and, at times, bronchial compression. While a full spectrum of congenital cardiac pathology can be identified before birth, only a few case reports document the prenatal diagnosis of an Left pulmonary artery sling (LPAS). We retrospectively identified all cases of prenatal LPAS from three Canadian fetal cardiology centers (2015-2022). Using the 3-vessel-tracheal view via fetal echocardiography (FE), four fetuses from three pregnancies demonstrated abnormal origin of the LPA from RPA and echogenic trachea. In one of two affected monochorionic twins coronal imaging demonstrated a significant narrowing of the large airways consistent with significant airway obstruction. Prenatal detection of LPAS by FE is possible and should prompt an evaluation for airway obstruction in the coronal view. Investigating associated lesions and genetic testing are recommended for informed shared decision making.

Optical solitons for the dispersive concatenation model with power law of self-phase modulation: undetermined coefficients

AbstractThis paper recovers 1-soliton solutions to the dispersive concatenation model that comes with power law of self-phase modulation. The method of undetermined coefficients has made this retrieval possible. The parameter constraints are listed for the existence of the solitons. While a full spectrum of solitons is enumerated and exhibited, it is proved that dark 1-solitons exist only for Kerr law of nonlinear refractive index change.

Improving potato AGB estimation to mitigate phenological stage impacts through depth features from hyperspectral data

The accurate estimation of above ground biomass (AGB) is valuable in grasping the status of potato growth and assessing yield. Spectral analysis techniques play an important role in AGB estimation by virtue of its non-destructive and rapid advantages. However, the models constructed based on spectral features at the entire growth stages due to differences in phenological stages, such as vegetation indices (VIs) and locations at fixed wavelengths, can be not applicable to single growth stages. Therefore, the main objective of this study is to improve the applicability of the AGB estimation model to mitigate the impacts of phenological stages by mining depth features from hyperspectral data. The canopy hyperspectral and AGB data of potato tuber formation, tuber growth and starch accumulation stages were measured in 2017–2019. The acquired canopy hyperspectral reflectance was smoothed by Savitzky-Golay (SG) filter, and the green edge (GE), the red edge (RE), red edge chlorophyll index (CIred-edge), optimized soil adjusted vegetation index (OSAVI), green normalized difference vegetation index (GNDVI), and normalized difference vegetation index (NDVI) were extracted. The spectral changes were analyzed at different growth stages of each year. To obtain features in response to AGB changes, a new approach is proposed to analyze the hidden depth features between sensitive wavelengths by combining a successive projections algorithm (SPA) and a long-short-term memory network (LSTM). The AGB estimation models were constructed by partial least squares regression (PLSR) based on traditional VIs + GE + RE, full spectrum, sensitive wavelengths obtained by SPA, and depth features obtained by SPA-LSTM. The results showed that GE, RE and VIs alone explained only 24 %-36 % of the variation in AGB. The accuracy of estimating AGB at sensitive wavelengths obtained after SPA was higher (R2 = 0.70, RMSE = 406 kg/hm2, and NRMSE = 27.14 %) than that of conventional VIs + GE + RE (R2 = 0.51, RMSE = 536 kg/hm2, and NRMSE = 35.81 %) and full spectrum (R2 = 0.63, RMSE = 452 kg/hm2, and NRMSE = 30.19 %) in the three-year dataset. The depth features extracted by the SPA-LSTM method proposed in this study achieved the best AGB estimation (R2 = 0.82, RMSE = 318 kg/hm2, and NRMSE = 21.25 %). The applicability of the model was validated in different years and growth stages. The R2 of each year was in the range of 0.48–0.77, the RMSE was in the range of 290–367 kg/hm2, and the NRMSE was in the range of 16.69 %-25.81 %. The R2 of each growth stage within three year was in the range of 0.48–0.78, the RMSE was in the range of 184–386 kg/hm2, and the NRMSE was in the range of 14.91 %-29.45 %. The method proposed in this study mitigates the impacts of phenological stage and improves the robustness and accuracy of the AGB estimation model, which provides remote sensing technical support for realizing potato growth monitoring and yield assessment in the field.

Exploring Individual Variability in Drug-Induced Liver Injury (DILI) Responses through Metabolomic Analysis.

Drug-induced liver injury (DILI) is a serious adverse hepatic event presenting diagnostic and prognostic challenges. The clinical categorization of DILI into hepatocellular, cholestatic, or mixed phenotype is based on serum alanine aminotransferase (ALT) and alkaline phosphatase (ALP) values; however, this classification may not capture the full spectrum of DILI subtypes. With this aim, we explored the utility of assessing changes in the plasma metabolomic profiles of 79 DILI patients assessed by the RUCAM (Roussel Uclaf Causality Assessment Method) score to better characterize this condition and compare results obtained with the standard clinical characterization. Through the identification of various metabolites in the plasma (including free and conjugated bile acids and glycerophospholipids), and the integration of this information into predictive models, we were able to evaluate the extent of the hepatocellular or cholestatic phenotype and to assign a numeric value with the contribution of each specific DILI sub-phenotype into the patient's general condition. Additionally, our results showed that metabolomic analysis enabled the monitoring of DILI variability responses to the same drug, the transitions between sub-phenotypes during disease progression, and identified a spectrum of residual DILI metabolic features, which can be overlooked using standard clinical diagnosis during patient follow-up.

Recent Trends and Applications of Nanostructure-based Drug Delivery in Alleviating Chronic Obstructive Pulmonary Disease (COPD).

Chronic Obstructive Pulmonary Disease (COPD), a chronic lung disease that causes breathing difficulties and obstructs airflow from the lungs, has a significant global health burden and affects millions of people worldwide. The use of pharmaceuticals in COPD treatment is aimed to alleviate symptoms, improve lung function, prevent exacerbations, and enhance the overall quality of life for patients. Nanotechnology holds great promise to alleviate the burden of COPD. The main goal of this review is to present the full spectrum of therapeutics based on nanostructures for the treatment and management of COPD, including nanoparticles, polymeric nanoparticles, polymeric micelles, solid-lipid nanoparticles, liposomes, exosomes, nanoemulsions, nanosuspensions, and niosomes. Nanotechnology is just one of the many areas of research that may contribute to the development of more effective and personalized treatment modalities for COPD patients in the future. Future studies may be focused on enhancing the therapeutic effectiveness of nanocarriers by conducting extensive mechanistic investigations to translate current scientific knowledge for the effective management of COPD with little or no adverse effects.

Phenomenological Evaluation of an Undergraduate Clinical Needs Finding Skills Through a Virtual Reality Clinical Immersion Platform

AbstractClinical immersion programs have been widely used in higher education, particularly in biomedical engineering (BME) programs, to allow students to identify and evaluate the unmet clinical needs. However, due to limited space and extensive safety protocols required to enter hospitals, access for undergraduate students to shadow physicians is limited. BME students need to be trained to identify and evaluate unmet clinical needs through observation and experience to remain competitive in the medical device landscape. To be able to allow students to immerse themselves into clinical environments remotely and be able to visualize the full spectrum of healthcare workers and equipment that support a procedure beyond what is available through online video records, we have developed a virtual reality (VR) clinical immersion platform. The applicability and overall student satisfaction of using VR learning environments was investigated through a pilot undergraduate BME unmet clinical needs finding course in the spring of 2022. Pre- and post-course survey analyses revealed that the VR clinical immersion experiences did greatly increase immersion within a medical procedure, and students felt sensations of presence and embodiment. Given the results of this study, VR learning environments can provide a means for students to perform unmet clinical needs through virtual clinical immersion. However, these technologies to support environments should be readily accessible within the classroom.

An efficient Burrows–Wheeler transform-based aligner for short read mapping

Read mapping as the foundation of computational biology is a bottleneck task under the pressure of sequencing throughput explodes. In this work, we present an efficient Burrows–Wheeler transform-based aligner for next-generation sequencing (NGS) short read. Firstly, we propose a difference-aware classification strategy to assign specific reads to the computationally more economical search modes, and present some acceleration techniques, such as a seed pruning method based on the property of maximum coverage interval to reduce the redundant locating for candidate regions, redesigning LF calculation to support fast query. Then, we propose a heuristic verification to determine the best mapping from amounts of flanking sequences. Incorporated with low-distortion string embedding, most dissimilar sequences are filtered out cheaply, and the highly similar sequences left are just right for the wavefront alignment algorithm’s preference. We provide a full spectrum benchmark with different read lengths, the results show that our method is 1.3–1.4 times faster than state-of-the-art Burrows–Wheeler transform-based methods (including bowtie2, bwa-MEM, and hisat2) over 101bp reads and has a speedup with 1.5–13 times faster over 750bp to 1000bp reads; meanwhile, our method has comparable memory usage and accuracy. However, hash-based methods (including Strobealign, Minimap2, and Accel-Align) are significantly faster, in part because Burrows–Wheeler transform-based methods calculate on the compressed space. The source code is available: https://github.com/Lilu-guo/Effaln.

Machine learning in the classification of asian rust severity in soybean using hyperspectral sensor

Traditional monitoring of asian soybean rust severity is a time- and labor-intensive task, as it requires visual assessments by skilled professionals in the field. Thus, the use of remote sensing and machine learning (ML) techniques in data processing has emerged as an approach that can increase efficiency in disease monitoring, enabling faster, more accurate and time- and labor-saving evaluations. The aims of the study were: (i) to identify the spectral signature of different levels of Asian soybean rust severity; (ii) to identify the most accurate machine learning algorithm for classifying disease severity levels; (iii) which spectral input provides the highest classification accuracy for the algorithms; (iv) to determine a sample size of leaves that guarantees the best accuracy for the algorithms. A field experiment was carried out in the 2022/2023 harvest in a randomized block design with a 6x3 factorial scheme (ML algorithms x severity levels) and four replications. Disease severity levels assessed were: healthy leaves, 25 % severity, and 50 % severity. Leaf hyperspectral analysis was carried out over a wide range from 350 to 2500 nm. From this analysis, 28 spectral bands were extracted, seeking to distinguish the spectral signature for each severity level with the least input dataset. Data was subjected to machine learning analysis using Artificial Neural Network (ANN), REPTree (DT) and J48 decision trees, Random Forest (RF), and Support Vector Machine (SVM) algorithms, as well as a traditional classification method (Logistic Regression - LR). Two different input datasets were tested for each algorithm: the full spectrum (ALL) provided by the sensor and the 28 spectral bands (SB). Tests with different sample sizes were also conducted to investigate the algorithms' ability to detect severity levels with a reduced sample size. Our findings indicate differences between the spectral curves for the severity levels assessed, which makes it possible to differentiate between healthy plants with low and high severity using hyperspectral sensing. SVM was the most accurate algorithm for classifying severity levels by using all the spectral information as input. This algorithm also provided high classification accuracy when using smaller leaf samples. This study reveals that hyperspectral sensing and the use of ML algorithms provide an accurate classification of different levels of Asian rust severity, and can be powerful tools for a more efficient disease monitoring process.