Assessment Of Diversity Research Articles

Assessment of phenotypic diversity and morphometry of indigenous chickens in Kabwe District, Zambia

This study characterized Zambian indigenous chickens' phenotypes and morphometric traits in Kabwe District, Zambia, to create a base for breeding program development. To achieve this, 206 hens and 228 cocks we sampled in Kabwe district. Each sampled chicken was phenotyped for 4 qualitative traits: ear lobe color, shank color, comb type, and eye color. Individual linear body measurements were recorded from each chicken using a tailor's tape in centimeters, which included body length (BL), chest circumference (CC), corpus length (CL), keel length (KL), shank circumference (SC), shank length (SL), thigh circumference (TC), and thigh length (TL). The findings showed that the predominant phenotypes were single comb type (98.91%), orange eyes (80.44%), white shanks (33.70%), and red-white earlobe color (50%). The average body weight was 1698.24 g, which showed a significant positive correlation (p<0.05) with all linear body measurements. For both sexes, body weight correlated positively with all linear measurements, except in males where body length showed a nonsignificant negative correlation. A stepwise regression analysis indicated that chest circumference, keel length, body length, shank circumference, thigh circumference, and corpus length (CL) are significant predictors of body weight (R² = 76.90%, P < 0.05). Additionally, the CHAID data mining algorithm identified keel length as the primary predictor of body weight, with corpus length and thigh length also contributing, achieving an R² of 61.20%. These findings provide valuable insights for instituting chicken breeding programs aimed at enhancing productivity and selection decisions.

Assessment of diversity and genetic differentiation in polycross-derived populations of Thymus daenensis using ISSR and SCoT markers

Assessment of diversity and genetic differentiation in polycross-derived populations of Thymus daenensis using ISSR and SCoT markers

The Genomic SSR Millets Database (GSMDB): enhancing genetic resources for sustainable agriculture.

The global population surge demands increased food production and nutrient-rich options to combat rising food insecurity. Climate-resilient crops are vital, with millets emerging as superfoods due to nutritional richness and stress tolerance. Given limited genomic information, a comprehensive genetic resource is crucial to advance millet research. Whole-genome sequencing provides an unprecedented opportunity, and molecular genetic methodologies, particularly simple sequence repeats (SSRs), play a pivotal role in DNA fingerprinting, constructing linkage maps, and conducting population genetic studies. SSRs are composed of repetitive DNA sequences where one to six nucleotides are repeated in tandem and distributed throughout the genome. Different millet species exhibit genomic variations attributed to the presence of SSRs. While SSRs have been identified in a few millet species, the existing information only covers some of the sequenced genomes. Moreover, there is an absence of complete gene annotation and visualization features for SSRs. Addressing this disparity and leveraging the de-novo millet genome assembly available from the NCBI, we have developed the Genomic SSR Millets Database (GSMDB; https://bioinfo.icgeb.res.in/gsmdb/). This open-access repository provides a web-based tool offering search functionalities and comprehensive details on 6.747645 million SSRs mined from the genomic sequences of seven millet species. The database, featuring unrestricted public access and JBrowse visualization, is a pioneering resource for the research community dedicated to advancing millet cultivars and related species. GSMDB holds immense potential to support myriad studies, including genetic diversity assessments, genetic mapping, marker-assisted selection, and comparative population investigations aiming to facilitate the millet breeding programs geared toward ensuring global food security. Database URL: https://bioinfo.icgeb.res.in/gsmdb/.

Airborne DNA: State of the art - Established methods and missing pieces in the molecular genetic detection of airborne microorganisms, viruses and plant particles.

Bioaerosol is composed of different particles, originating from organisms, or their fragments with different origin, shape, and size. Sampling, analysing, identification and describing this airborne diversity has been carried out for over 100 years, and more recently the use of molecular genetic tools has been implemented. However, up to now there are no established protocols or standards for detecting airborne diversity of bacteria, fungi, viruses, pollen, and plant particles. In this review we evaluated commonalities of methods used in molecular genetic based studies in the last 23 years, to give an overview of applicable methods as well as knowledge gaps in diversity assessment. Various sampling techniques show different levels of effectiveness in detecting airborne particles based on their DNA. The storage and processing of samples, as well as DNA processing, influences the outcome of sampling campaigns. Moreover, the decisions on barcode selection, method of analysis, reference database as well as negative and positive controls may severely impact the results obtained. To date, the chain of decisions, methodological biases and error propagation have hindered DNA based molecular sequencing from offering a holistic picture of the airborne biodiversity. Reviewing the available studies, revealed a great diversity in used methodology and many publications didn't state all used methods in detail, making comparisons with other studies difficult or impossible. To overcome these limitations and ensure genuine comparability across studies, it is crucial to standardize protocols. Publications need to include all necessary information to enable comparison among different studies and to evaluate how methodological choices can impacts the results. Besides standardization, implementing of automatic tools and combining of different analytical techniques, such as real-time evaluation combined with sampling and molecular genetic analysis, could assist in achieving the goal of accurately assessing the actual airborne biodiversity.

Extent and patterns of morphological and molecular genetic diversity and population structure of Nigerian Taro cultivars.

Genetic diversity is crucial for conservation efforts as well as breeding programs targeted at the development of improved varieties. Taro, a climate-resilient crop, plays a vital role in the nutritional and economic livelihoods of many households in Nigeria, but its yield is very low due to inadequate genetic improvement efforts. A diversity assessment of Nigerian taro is therefore required to create a premise for its improvement in yield, quality and disease tolerance. In this study, the genetic diversity and population structure of 490 taro cultivars comprising two main gene pools: Dasheen (215) and Eddoe (275), collected from farmers and marketers across seven states in Nigeria was assessed using 3047 Diversity Array Technology single nucleotide polymorphism (DArT-SNP) markers. A subset of 114 taro cultivars, comprising 30 Dasheens and 84 Eddoes were further phenotyped using 24 agro-morphological descriptors. Both phenotypic and molecular characterization revealed higher genetic diversity among the Eddoes than Dasheens. Estimates of gene flow (Nm = 0.353) revealed intermixing of cultivars among the States of collection, with the highest gene flow occurring between cultivars from Anambra and Ondo states and the lowest between Anambra and Kwara states. Population structure and Ward's minimum variance hierarchical cluster based on DArT-SNPs identified four groups, one comprising Dasheen and three comprising Eddoe cultivars. Hierarchical clustering based on phenotypic traits delineated three clusters. Variation between gene pools (49%) was higher than within gene pools (32%). Variation among States of collection was high (41%), while variation among individuals within gene pools (18%) and States of collection (19%) was relatively low. Correlation between phenotypic and genotypic diversity assessments was low (r = 0.01), indicating that both approaches were necessary for assessing genetic diversity in taro. However, genotypic assessment provided better information about genetic diversity of the taro cultivars. This is the first study that represented germplasm collection across the major taro growing regions of Nigeria. The findings from this study based on agro-morphological characterization and DArT-SNP genotyping are critical for genetic characterization, conservation and breeding of taro in Nigeria, mainly initiating hybridization between the two genepools after careful assessment of ploidy levels of the accessions collected in this study. This will facilitate in developing improved taro varieties with desirable traits, such as higher yield, better disease resistance, and improved nutritional quality.

Genetic and phytochemical evaluation of M2 generation mutants of fenugreek (Trigonella foenum-graecum L.) induced by gamma rays and Ethyl Methane Sulphonate (EMS).

Fenugreek (Trigonella foenum-graecum L.) is highly esteemed for its therapeutic properties and is widely used in traditional medicine and modern pharmacology. Enhancing its genetic traits and phytochemical profile, particularly its trigonelline content, can significantly increase its medicinal and agricultural value. This study aims to investigate the effects of gamma rays and Ethyl Methane Sulphonate (EMS) as mutagenic agents on the genetic and phytochemical characteristics of the M2 generation of fenugreek, focusing on genetic diversity and desirable trait enhancement. To achieve this, various concentrations of EMS and gamma rays were administered to fenugreek seeds, and 27 traits were assessed in the resulting M2 generation. These traits were analyzed for variance, mean values, and correlations. The genetic diversity of 23 M2 offspring was investigated using nine Start Codon Targeted (SCoT) markers. The genetic diversity assessment involved Principal Coordinate Analysis (PCoA) and cluster analysis, utilizing the Dice similarity coefficients and the Unweighted Pair Group Method with Arithmetic Mean (UPGMA). A Bayesian model provided deeper insights into the genetic structure. Results revealed that lower doses of gamma rays (100Gy) and EMS (0.2%) positively impacted specific traits. In comparison, higher doses (200Gy and 0.4% EMS) increased seed trigonelline content to 0.71mg/g dry weight. Among the SCoT markers, SCoT-9 was the most efficient, segregating the populations into three clusters. The first three principal components in the PCoA explained 20% of the total variance, leading to seven subgroup populations distinction. These findings underscore the potential of induced mutagenesis in enhancing desirable traits in fenugreek.

Investigation on possibility of mangrove regeneration: a case study from Indian Sundarbans.

Mangroves serve as biotic fences of estuarine belts consisting of salt-tolerant plants that grow in intertidal zones and can be regenerated naturally as well as artificially. Mangrove regeneration refers to the process of restoring or rebuilding mangrove ecosystems that have been already degraded, damaged, or lost from their native place through the monitoring of geomorphological, taxonomical, pedological, and ecological aspects. The primary objective of this study was based on the remote sensing application through several important health monitoring indices over the minute part of Indian Sundarbans to prove the possibility of mangrove regeneration. Change detection analysis in the indices proves that there was possible growth and development in mangrove colonization over the same. The secondary objective is to comprehend the association of field-related study with the remotely sensed data on species diversity assessment over the same where the native species are Avicennia marina (Peyara Bain), Avicennia officinalis (Jat Bain), Avicennia alba (Kalo Bain), Aegialitis rotundifolia (Tora), Acanthus ilicifolius (Horgoj Kanta), Bruguiera gymnorrhiza (Kankra), Ceriops tagal (Goran), and Aegiceras corniculatum (Khalisi). The latter objective is associated with the tertiary one that unveils the correlation between several physico-chemical properties of soil samples taken from the field with the species accommodation.Textural classes are grouped between clay and silty clay that helps to get the foundation of hard wood-basedspecies (Avicennia type) specifically with the salinity ranges between 200 ppt (Site 2) and 633 ppt (Site 1)approximately which presents that the zone is highly saline zone as specifically Avicennia species can sustain highsalinity. Importance Value Index (IVI) and species diversity indices have been run to support whether the zone is diversified or not.Equilibrium between deforestation and regeneration through mangrove plantation has to be attained in the nearfuture as deforestation for the livelihood purposes exists, so this newly born island locally named Dorabagdamangrove patch, upper part (Gopalganj) of Kaikhali village, would be the best experimental study site on mangroveregeneration.

Indirect Treatment Comparisons in Healthcare Decision Making: A Targeted Review of Regulatory Approval, Reimbursement, and Pricing Recommendations Globally for Oncology Drugs in 2021-2023.

Indirect treatment comparisons (ITCs) evaluate novel treatments compared to appropriate comparators when direct evidence is unavailable or infeasible. The objective of this study was to highlight the prevalence of different ITC methods in oncology drug submissions and to provide insights into how ITCs have been used in recent regulatory approval, reimbursement recommendations, or pricing decisions across various regions and diverse assessment frameworks. A targeted literature review was conducted to identify assessment documents for oncology drug submissions that included ITCs. This included hand searches of the websites of four regulatory bodies and four health technology assessment (HTA) agencies with varying assessment frameworks across North America, Europe, and Asia-Pacific. A total of 185 documents were included for synthesis. Documents were retrieved from all four HTA agencies and the European Medicines Agency (EMA), the only regulatory body with eligible records. Within these, 188 unique submissions included a total of 306 supporting ITCs of various methods. Authorities more frequently favored anchored or population-adjusted ITC techniques for their effectiveness in data adjustment and bias mitigation. Furthermore, ITCs in orphan drug submissions more frequently led to positive decisions compared to non-orphan submissions. This review highlights the crucial role and widespread use of ITCs in global healthcare decision-making, particularly when direct evidence is lacking, and in the discernment of market-specific clinical benefits. This work contributes to bolstering the credibility and recognition of ITCs across regulatory and HTA agencies of diverse regions and assessment frameworks.

Assessment of floristic diversity and traditional knowledge from the selected mountainous valleys of district Gilgit, Gilgit-Baltistan, Pakistan

Assessment of floristic diversity and traditional knowledge from the selected mountainous valleys of district Gilgit, Gilgit-Baltistan, Pakistan

Settlement patterns and temporal successions of coral reef cryptic communities affect diversity assessments using autonomous reef monitoring structures (ARMS)

Autonomous Reef Monitoring Structures (ARMS) are used worldwide to assess cryptic diversity, especially on coral reefs. They were developed as standardised tools, yet conditions of deployment, such as immersion duration and/or deployment and retrieval seasons, vary among studies. Here we studied temporal and seasonal variability in coral reef cryptic communities sampled with 15 ARMS on a single coral reef slope site at Reunion Island, Southwest Indian Ocean. Settlement patterns and temporal succession of Eukaryote communities were investigated across three immersion times (6 months, 1 year, 2 years), two immersion seasons (hot vs. cool) and three fractions (500–2000 μm, 106–500 μm, sessile) using two genetic markers (18S, COI). Both markers detected different taxa with different resolutions, but broadly similar patterns of community composition and structure. While OTU diversity of communities did not change with immersion time and season, these parameters significantly affected community structure and composition. Our results showed a decrease of the similarity of ARMS communities with duration of immersion, and a strong temporal turnover of species with only a small proportion of the diversity persisting over time. The small proportion of OTUs assigned at phylum level highlights the uniqueness of the Mascarene cryptobiome.

Chatgpt Assisted Teachers in Improving Formative Assessment

In recent years, the application of artificial intelligence technology in education has received widespread attention, but its specific utility and challenges in formative assessment remain underexplored. This research paper investigates the value of ChatGPT in aiding teachers with exam design and providing student feedback. Through comprehensive interviews, the study analyses the actual effectiveness and challenges of using ChatGPT to enhance teaching efficiency and optimize student feedback. The findings indicate that ChatGPT offers significant advantages in generating diverse assessment questions and personalized feedback. However, teachers must validate and edit the AI-generated content to ensure its accuracy and relevance. Based on these insights, the paper provides several key recommendations: validating AI-generated content, enhancing teacher training, and maintaining teachers' professional independence. These steps are essential to optimize the quality and efficiency of educational assessments. This research aims to contribute to the better integration of AI technologies in education by addressing both their potential and their limitations comprehensively.

Assessment of genetic diversity and heterotic alignment of CIMMYT and IITA maize inbred lines adapted to sub‐Saharan Africa

AbstractDespite the breeding efforts by many institutions, maize (Zea mays L.) productivity in sub‐Saharan Africa is still low. A limited number of productive maize hybrids have been developed partly due to a lack of knowledge on the diversity and heterotic relationship of the germplasm, especially in public breeding programs. Understanding the extent of diversity, structure, and heterotic grouping of available maize germplasm originating from different breeding programs is important to enhance long‐term genetic gain in hybrid maize breeding programs by optimizing heterotic pools using modern breeding tools. Information about the genetic structure of the available germplasm could help breeders design effective breeding strategies to improve yield. This study was conducted to determine the genetic diversity, population structure, and heterotic alignment among 187 elite maize inbred lines from the IITA (International Institute of Tropical Agriculture) and CIMMYT (International Maize and Wheat Improvement Center) maize breeding programs. The inbred lines were genotyped with 9857 Diversity Array Technology sequencing based single nucleotide polymorphism markers. Hierarchical clustering revealed three major groups, with some subgroups consistent with the selection history, and pedigree of the inbred lines. Three broad groups were detected: two consisting of CIMMYT lines and a mixed group consisting of both CIMMYT and IITA inbred lines. The STRUCTURE analysis revealed six subpopulations (fixation index value = 0.58), which depicts a moderate genetic diversity among the materials. Population 2 comprises the highest number of genotypes (102) from both programs. More than 89% of the elite lines had homozygosity exceeding 95%, with the remaining lines requiring further inbreeding through repeated self‐pollination. There was inconsistency in the predetermined heterotic groups' alignment between CIMMYT and IITA elite inbred lines. Analysis of molecular variance revealed that 96% of the total variation was accounted for by differences within groups, with the remaining 4% representing the variation between groups. This suggests that the two programs can benefit from germplasm exchange for the improvement of maize productivity.

Genetic diversity assessment of cucumber landraces using molecular signatures

Genetic profiling of the biodiversity in cultivated crop plants is necessary to preserve important genes and utilize them in a breeding program. Cucumber is used as a model plant to study various characteristics of Cucurbitaceae. Its adaptation to a wide range of climatic conditions suggested analyzing the landraces. The present study was conducted to evaluate the differences, at the genetic level, among landraces spanning five continents. DNA extracted from fifty-six landraces selected from USDA germplasm bank to cover a global representative sample of world cucumber landraces was used for polymerase chain reaction using twenty-eight polymorphic expressed sequence tags simple sequence repeat (EST-SSR) markers. Twenty-eight EST-SSR markers covering all seven chromosomes yielded 98 bands with an average of 3.42 bands per marker. Polymorphic information content ranged from 0.00 (EC35) to 0.74 (EC17) with an average of 0.34. Six clusters provided an appropriate summary of the variation among the landraces, with the two largest groups including 32 (Asiatic) and 17 (European and American) landraces, respectively. Four small groups, three with two members, and one with one member (PI 525155-Egypt) were dissimilar to the two main groups. Landraces from the same region were often clustered together. Genetic similarity of the landraces was revealed by marker banding patterns. The locations of genetic diversity for cucumber landraces can be identified from this study.

Ecological Assessment of Phytoplankton Diversity and Water Quality to Ensure the Sustainability of the Ecosystem in Lake Maybalyk, Astana, Kazakhstan

Microalgae in planktonic communities are the main producers of biomass in lake ecosystems; however, their stability is influenced by many environmental factors. This study aims to assess the ecological state of Lake Maybalyk, located in Astana (Kazakhstan), based on the study of the taxonomic diversity and structure of phytoplankton, zooplankton, and the physico-chemical properties of the water. From 2019 to 2021, samples were taken for phytoplankton analysis, hydrochemical analysis of the water, zooplankton, and saprobiological analysis of the algocenosis. The study also investigated the main morphometric parameters of the lake, as well as the composition of hydrobionts, such as zooplankton, zoobenthos, and ichthyofauna. The analysis of phytoplankton revealed the presence of 97 species and intraspecific taxa of microalgae, with 71 types of microalgal indicators indicating water saprobity. The planktonic algoflora in Lake Maybalyk is predominantly composed of diatoms (Bacillariophyta) and green algae (Chlorophyta), which play a vital role in oxygen production and the food chain within the reservoir. Based on the Pantle–Buck saprobity index (2.15–2.5), the water quality in Lake Maybalyk is classified as moderately polluted. The assessment of the water quality, considering the number and composition of indicator phytoplankton species, places Lake Maybalyk in class III (β-mesosaprobic). The hydrochemical indicators align with the hydrobiological indicators, confirming the water quality as class III. The trophic status of the reservoir, during the study period, can be described as average. The obtained data on both the hydrobiological and hydrochemical indicators correlate, suggesting satisfactory water quality and the ability of the reservoir to purify itself. This study contributes to the sustainable management of water resources, by providing essential data on the ecological state of Lake Maybalyk. The results underscore the importance of continuous biomonitoring, with microalgae as indicators of water quality, which is crucial for developing effective ecosystem conservation strategies.

A Case Study: Implementation of Innovative Educational Strategies on Teaching Nuclear Chemistry at the College of Engineering Laguna State Polytechnic University – Sta. Cruz Campus

The outcome of the evaluation shows the level of students’ consistency with the expected learning outcomes and identifies the weaknesses that are present in them for training rationale. As a result, the data highlight the necessity of the creation of certain instructional techniques that would help the students confront the challenges that arise due to nuclear chemistry. Probably this would improve the understanding p of nuclear structure and properties when jigsaw and practical strategies are used to teach. A noticeable growth of homogeneity between subjects around the engineering specialization spectrum provides an idea of what works best. High marks achieved early may indicate deficits within the domain while progressing uniformly points towards learning needs being unaddressed. Learners’ interests and the perception of their knowledge may be enhanced by employing diverse tasking and assessment strategies within the instructional applications. Nuclear chemistry may remain a challenging science that does not motivate students to learn or retain information if its delivery does not change. The action plan is part of follow-up activities like conducting active learning through group work and experiments. Such procedures are reasonable as they provide and support evidence of understanding through feedback. Adjust the existing curriculum as a pedagogical strategy for generating credible new information supported by practical benefits. Impart additional learning and teaching in a way that assists challenged or struggling learners in adapting. Be open and discuss positive outcomes so that students become more self-assured and confident. As the above recommendations and action plans were also suggested by them, it is expected that engineering students who adopt nuclear chemistry will have their education experiences enhanced. This strategic approach does more than solve the challenges noted but also employs the resources and opportunities available to promote understanding of the subject. It is also expected that these strategies will be subjected to constant evaluation to improve their effectiveness and the students’ addresses.

A survey on the occurrence of papaya ringspot virus-P (PRSV-P) in Malaysia and genetic diversity assessment of the coat protein region.

Papaya ringspot virus (PRSV) is a plant virus transmitted by aphids that has spread throughout many countries, including Malaysia, causing yield losses and economic impacts to the papaya industry worldwide. PRSV infection in papaya-distinctive ring-shaped patterns on papaya leaves resulted in stunted growth and reduced fruit quality. Management strategies such as the use of resistant varieties, cultural practices, and vector control are employed to mitigate the spread of PRSV. However, the evolution of new virus strains and the uncertainties posed by climate change pose ongoing challenges for the management of PRSV worldwide. Therefore, in this present study, we aim to confirm the presence of PRSV in symptomatic papaya leaves, to depict the current status of PRSV in Malaysia. Using reverse-transcription PCR (RT-PCR) targeting PRSV partial nuclear inclusion b protein (NIb) and coat protein (CP), 13 out of 40 papaya leaves collected were found positive for the PRSV strain-P (PRSV-P). Nucleotide analysis revealed a high similarity with strains from Taiwan and India, showing 96.83%, 97.03%, and 97.03% identity with the Taiwan strains (DQ340771, AY027810) and the India strain (KJ755852), respectively. Compared to the CP gene of Malaysian isolates reported in 2016 (EU082207), several nonsynonymous mutations have been discovered suggesting genetic diversity within the PRSV population in Malaysia. Overall, this study confirms the current circulation of PRSV infection in Malaysia since it was first identified in Johore in 1991. The re-occurrence of PRSV-P in this study highlights the need for continuous monitoring and targeted management strategies to prevent the further spread of PRSV-P in Malaysia.

AI in Soil Health Monitoring: A Data-Driven Approach

Abstract: The sustainability of ecosystems and agricultural productivity depend on healthy soil. However, conventional techniques for evaluating soil health are sometimes time-consuming, labor-intensive, and restricted in their geographic reach. New opportunities for scalable, real-time soil health monitoring have been made possible by recent developments in artificial intelligence (AI) and data-driven methodologies. This study examines a thorough AI-powered system for tracking soil health, emphasizing methods for data collection, processing, and predictive modeling. AI models can provide precise forecasts of soil characteristics, health indicators, and possible crop yields by combining data from multiple sources, such as remote sensing, soil sensors, and historical data. This study offers a comprehensive analysis of recent AI applications in soil health monitoring and suggests a reliable, scalable approach intended to incorporate diverse data sources, guaranteeing precise and effective soil health assessment.

Assessment of the dark diversity's ability to predict the absence of Zygoptera (Odonata) species sensitive to anthropogenic disturbance in human-altered Amazonian ecosystems.

Estimates of dark diversity, species that belong to a given species pool but are not present locally, can help to understand how environmental conditions influence species distribution. However, it remains uncertain whether dark diversity can predict the absence of indicator species in preserved environments after environmental changes. We explored the sensitivity of dark diversity (the set of species absent from a particular area), in detecting the absence of Zygoptera (Odonata) indicative of preserved forest environments in altered habitats, and the influence of sample coverage on the detected patterns. We sampled 98 streams in the Amazon region, where the dark diversity of Zygoptera was estimated based on probabilistic species co-occurrence patterns using the Beals index, encompassing 16 species in the Santarém/Belterra region and 23 species in the Paragominas region. The mean total richness of observed Zygoptera species in Paragominas, 42.7 species, and Santarém/Belterra, 25.93 species, was higher than the estimated mean dark diversity for the two study sites, which were 12.32 and 12.20 species, respectively. The dark diversity was not effective in detecting the absence of forest-indicator Zygoptera in human-altered streams and exhibited a positive relationship between Zygoptera dark diversity and species common to different environments concerning environmental integrity only in Paragominas, but not in Santarém. We found that there is a possibility that observed values of dark diversity may occasionally be subject to sampling coverage biases. In this regard, we suggest considering sampling coverage alongside field-collected biological datasets to assess whether it is related to dark diversity.

An efficient Q-learning integrated multi-objective hyper-heuristic approach for hybrid flow shop scheduling problems with lot streaming

Efficient scheduling in flow shop environments with lot streaming remains a critical challenge in various industrial settings, necessitating innovative approaches to optimize production processes. This study investigates a hybrid flow shop scheduling problem dominant in real-world printed circuit board assembly shops. A novel multi-objective hyper-heuristic combining Q-learning, i.e., two-stage improved spider monkey optimization (TS-ISMO), is tailored to address the complexities of the flow shop scheduling problems. The proposed method aims to simultaneously optimize conflicting objectives such as minimizing makespan, total energy consumption, and total tardiness time while incorporating lot streaming considerations. For multi-objective hyper-heuristic techniques, the algorithm dynamically selects and adapts a diverse set of low-level heuristics to explore the solution space comprehensively and strike a balance among competing objectives. The proposed TS-ISMO algorithm incorporates several significant features aimed at enhancing its performance. These features encompass hybrid heuristics for solution initialization, a contribution value method for comprehensive convergence and diversity assessment, diverse evolutionary state judgments to promote the algorithm’s balance between exploration and exploitation capabilities, and a Q-learning strategy for self-adaptive parameter tuning. The integration of Q-learning facilitates intelligent parameter control, enabling the algorithm to autonomously adjust its behavior based on past experiences and evolution dynamics. This adaptive mechanism enhances convergence speed and solution quality by effectively guiding the search process toward promising regions of the solution space. Extensive computational experiments are conducted on benchmark instances of hybrid flow shop scheduling problems with lot streaming to evaluate the performance of the proposed algorithm. Comparative analyses against state-of-the-art approaches demonstrate its superior solution quality and computational efficiency.

Development and Application of Microsatellite Markers for Genetic Diversity Assessment and Construction of a Core Collection of Myrciaria dubia (Kunth) McVaugh Germplasm from the Peruvian Amazon

The Amazonian shrub Myrciaria dubia (camu-camu) produces vitamin C-rich fruits of growing commercial interest. However, sustainable utilization requires assessment and protection of the genetic diversity of the available germplasm. This study aimed to develop and apply microsatellite markers to assess genetic diversity and construct a core collection of M. dubia germplasm from the Peruvian Amazon. Sixteen polymorphic microsatellite loci were developed using an enrichment approach. The evaluation of 336 genotypes from 43 accessions of the germplasm bank, originating from eight river basins, was conducted using these newly developed markers. Genetic diversity parameters, including observed and expected heterozygosity, were calculated. Analysis of molecular variance (AMOVA) was performed to assess the distribution of genetic variation within and among accessions and river basins. Bayesian clustering analysis was employed to infer population structure. A core collection was constructed to maximize allelic richness. High genetic diversity was observed, with heterozygosity values ranging from 0.468 to 0.644 (observed) and 0.684 to 0.817 (expected) at the river basin level. AMOVA indicated significant genetic variation within (73–86%) compared to among (14–27%) accessions and river basins. Bayesian clustering detected ten genetic clusters, with several degrees of admixture among river basins, except for the genetically homogeneous Putumayo River basin. A core collection comprising 84 plant genotypes (25% of the full collection) was established, representing 90.82% of the overall allelic diversity. These results have important implications for M. dubia conservation strategies and breeding programs, in demonstrating a need for genetic connectivity between populations but preserving unique genetic resources in isolated basins. These results validate the expected levels of diversity and population subdivision in a crop and stress the need to secure genetically diverse germplasms, underscoring the importance of thorough genetic characterization for ex situ germplasm management.