Does testosterone underly the interplay between male traits and territorial behavior in neotropical poison frogs?

The ability of individual animals to defend a territory as well as various phenotypic and behavioral traits may be targets of sexual selection used by males to evaluate their competitors or by females to choose males. A frequent question in animal behavior is whether male traits and characteristics of their territory are correlated and what are the mechanisms that may mediate such associations when they exist. Because hormones link phenotype to behavior, by studying the role of testosterone in territoriality one may come closer to understanding the mechanisms mediating correlations or lack thereof between characteristics of territories and of males. We evaluated whether variation in characteristics of territories (size and quality) are correlated with variation in morphology, coloration, testosterone, heterozygosity, and calls in two species of poison frogs. The Amazonian frog Allobates aff. trilineatus exhibits male care and defends territories only during the breeding season, while the endangered frog Oophaga lehmanni displays maternal care and defends territories throughout the year. We found that morphological traits (body length, weight, thigh size), call activity, and testosterone levels correlated with size and various indicators of quality of the territory. However, the direction of these correlations (whether positive or negative) and which specific morphological, acoustic traits or testosterone level variables covaried depended on the species. Our findings highlight an endocrine pathway as part of the physiological machinery that may underlie the interplay between male traits and territorial behavior. We were able to identify some male traits related to territory attributes, but whether females choose males based on these traits requires further research.

Cypermethrin exposure: Implications for growth, phenotypic attributes, and biochemical responses in monosex tilapia (Oreochromis niloticus).

The present study was conducted to evaluate the effects of exposure to sublethal concentrations of cypermethrin on growth, phenotypic traits, and metabolic and antioxidant enzymes activities of monosex tilapia (Oreochromis niloticus). The median lethal concentration (LC50) of cypermethrin was initially ascertained to be 0.04 ppm after 12 h of exposure to three concentrations (0.04, 0.20, and 1.0 ppm) via the Probit analysis method. The sublethal exposures were obtained for 3 months at 0.0016, 0.008, and 0.04 ppm of cypermethrin. The growth performance, phenotypic traits, and enzymatic activity were analyzed. The research findings revealed a notable impact of cypermethrin on the growth performance of monosex tilapia, with a significant (p < 0.05) decrease in weight observed as the concentration increased. The experiment documented a significant change (p < 0.05) in the phenotypic traits of standard length, total length, tail length, trunk length, eye diameter, body area, and color patterns, but not dressing percentage. Furthermore, it was observed that the activities of amylase and protease in both the intestine and muscle decreased significantly (p < 0.05) with increasing concentrations of cypermethrin, except for amylase in the muscle, where no significant change was noted (p > 0.05). The results also demonstrated significant reductions (p < 0.05) in the activity of metabolic enzymes, specifically superoxide dismutase and catalase, following exposure to sublethal levels of cypermethrin. The study suggested that sublethal exposure of pyrethroid alters the growth, phenotypic traits, metabolic enzymes activities, and immunity of monosex tilapia.

Characterization of phenotypic traits associated with anthracnose resistance in selected common bean (Phaseolus vulgaris L.) breeding material.

Anthracnose caused by Colletotrichum lindemuthianum is the major common bean disease worldwide causing complete yield loss under favourable disease conditions. This study aimed to determine phenotypic traits associated with anthracnose resistance for future use in breeding programmes. Twenty-two common bean varieties (CBVs) were selected basing on susceptibility to anthracnose, advanced breeding lines, improved variety resembling advanced breeding lines and the farmer variety widely grown in Tanzania. Selected varieties were planted in anthracnose hotspot fields and the same CBVs were planted in a screen house to validate resistance to anthracnose. Anthracnose infection score, leaf length, leaf width, length of fifth internode, length of petiole, plant vigour, canopy height and canopy width were recorded. Data on number of plants emerging; days to flowering; days to maturity; plant stands at harvest; and grain yield were also collected and analysed using R software. Phenotypic traits evaluated differed significantly among genotypes, environment and genotype by environment interaction. Seventy-five percent of phenotypic traits evaluated were positively correlated to anthracnose resistance. Highly-strong correlations to anthracnose were observed on number of days to maturity, plant stands at harvest, plant vigour and grain yield. Leaf length, leaf width, length of fifth internode, length of petiole and number of stands emerging were strongly correlated to anthracnose resistance. Additive main effects and multiplicative interaction analysis (AMMI) revealed highest contribution of environment on anthracnose infection-58.9% and grain yield -84.9% compared to genotype effects on anthracnose infection -32.7% and grain yield-15.7%. Based on these results, four traits - plant vigour, number of days to maturity, number of plant stands at harvest and grain yield - are recommended for selecting anthracnose-resistant varieties. NUA 48, NUA 64 and RWR 2154 were superior varieties, resistant to anthracnose and high yielding, while Sweet Violet and VTT 923-23-10 were most stable varieties across environments. Further on-farm research is suggested to assess their performance and identify traits preferred by farmers.

Demographic patterns of walleye (Sander vitreus) reproductive success in a Wisconsin population.

Harvest in walleye Sander vitreus fisheries is size-selective and could influence phenotypic traits of spawners; however, contributions of individual spawners to recruitment are unknown. We used parentage analyses using single nucleotide polymorphisms to test whether parental traits were related to the probability of offspring survival in Escanaba Lake, Wisconsin. From 2017 to 2020, 1339 adults and 1138 juveniles were genotyped and 66% of the offspring were assigned to at least one parent. Logistic regression indicated the probability of reproductive success (survival of age-0 to first fall) was positively (but weakly) related to total length and growth rate in females, but not age. No traits analyzed were related to reproductive success for males. Our analysis identified the model with the predictors' growth rate and year for females and the models with year and age and year for males as the most likely models to explain variation in reproductive success. Our findings indicate that interannual variation (i.e., environmental conditions) likely plays a key role in determining the probability of reproductive success in this population and provide limited support that female age, length, and growth rate influence recruitment.

Characterization of Lithuanian Tomato Varieties and Hybrids Using Phenotypic Traits and Molecular Markers.

The aim of this study was to evaluate phenotypic traits and genetic diversity of the 13 tomato (Solanum lycopersicum L.) varieties and 6 hybrids developed at the Institute of Horticulture Lithuanian Research Centre for Agriculture and Forestry (LRCAF IH). For the molecular characterisation, seven previously published microsatellite markers (SSR) were used. A24 and 26 alleles were detected in tomato varieties and hybrids, respectively. Based on the polymorphism information content (PIC) value, the most informative SSR primers for varieties were TMS52, TGS0007, LEMDDNa and Tom236-237, and the most informative SSR primers for hybrids were SSR248 and TMS52. In UPGMA cluster analysis, tomato varieties are grouped in some cases due to genetic relationships, as the same cluster cultivars 'Viltis' (the parent of cv. 'Laukiai') and 'Ausriai' (the progeny of cv. 'Jurgiai') are present. The grouping of all hybrids in the dendrogram is related to the parental forms, and it shows the usefulness of molecular markers for tomato breeding, as they can be used to trace the origin of hybrids and, eventually, varieties accurately. The knowledge about the genetic background of Lithuanian tomato cultivars will help plan targeted crosses in tomato breeding programs.

Advanced deep learning models for phenotypic trait extraction and cultivar classification in lychee using photon-counting micro-CT imaging.

Introduction: In contemporary agronomic research, the focus has increasingly shifted towards non-destructive imaging and precise phenotypic characterization. A photon-counting micro-CT system has been developed, which is capable of imaging lychee fruit at the micrometer level and capturing a full energy spectrum, thanks to its advanced photon-counting detectors. Methods: For automatic measurement of phenotypic traits, seven CNN-based deep learning models including AttentionUNet, DeeplabV3+, SegNet, TransUNet, UNet, UNet++, and UNet3+ were developed. Machine learning techniques tailored for small-sample training were employed to identify key characteristics of various lychee species. Results: These models demonstrate outstanding performance with Dice, Recall, and Precision indices predominantly ranging between 0.90 and 0.99. The Mean Intersection over Union (MIoU) consistently falls between 0.88 and 0.98. This approach served both as a feature selection process and a means of classification, significantly enhancing the study's ability to discern and categorize distinct lychee varieties. Discussion: This research not only contributes to the advancement of non-destructive plant analysis but also opens new avenues for exploring the intricate phenotypic variations within plant species.

The diversity of endophytic fungi in Tartary buckwheat (Fagopyrum tataricum) and its correlation with flavonoids and phenotypic traits.

Tartary buckwheat (Fagopyrum tataricum) is a significant medicinal crop, with flavonoids serving as a crucial measure of its quality. Presently, the artificial cultivation of Tartary buckwheat yields low results, and the quality varies across different origins. Therefore, it is imperative to identify an effective method to enhance the yield and quality of buckwheat. Endophytic fungi reside within plants and form a mutually beneficial symbiotic relationship, aiding plants in nutrient absorption, promoting host growth, and improving secondary metabolites akin to the host. In this study, high-throughput sequencing technology was employed to assess the diversity of endophytic fungi in Tartary buckwheat. Subsequently, a correlation analysis was performed between fungi and metabolites, revealing potential increases in flavonoid content due to endophytic fungi such as Bipolaris, Hymenula, and Colletotrichum. Additionally, a correlation analysis between fungi and phenotypic traits unveiled the potential influence of endophytic fungi such as Bipolaris, Buckleyzyma, and Trichosporon on the phenotypic traits of Tartary buckwheat. Notably, the endophytic fungi of the Bipolaris genus exhibited the potential to elevate the content of Tartary buckwheat metabolites and enhance crop growth. Consequently, this study successfully identified the resources of endophytic fungi in Tartary buckwheat, explored potential functional endophytic fungi, and laid a scientific foundation for future implementation of biological fertilizers in improving the quality and growth of Tartary buckwheat.

Humidity modifies species-specific and age-dependent heat stress effects in an insect host-parasitoid interaction.

Climate change is projected to increase the frequency and intensity of extreme heat events, and may increase humidity levels, leading to coupled thermal and hydric stress. However, how humidity modulates the impacts of heat stress on species and their interactions is currently unknown. Using an insect host-parasitoid interaction: the Indian meal moth, Plodia interpunctella, and its endoparasitoid wasp, Venturia canescens, we investigated how humidity interacted with heat stress duration, applied at different host developmental stages, to affect life history traits. Hosts parasitized as 4th instar larvae and unparasitized hosts were maintained in high- (60.8% RH) or low-humidity (32.5% RH) at constant 28°C. They were then exposed to a 38°C thermal stress with a duration of 0 (no heat stress), 6 or 72 h in either the 4th or 5th host instar. Neither humidity nor heat stress duration affected emergence of unparasitized hosts, but increasing heat stress duration during the 4th instar decreased parasitoid emergence irrespective of humidity. When applied during the 5th instar, increasing heat duration decreased parasitoid emergence under low humidity, but no effect of heat stress was found under high humidity. Moreover, experiencing longer heat stress in the 4th instar increased host larval development time and decreased body size under high humidity, but this effect differed under low humidity; increasing heat duration in the 5th instar decreased parasitoid body sizes only under low humidity. Larval stage and heat stress duration directly affected parasitized host survival time, with a concomitant indirect reduction of parasitoid sizes. We show that humidity modifies key life history responses of hosts and parasitoids to heat stress in species-specific ways, highlighting the potential importance of humidity in regulating host-parasitoid interactions and their population dynamics. Finally, we emphasize that interactions between environmental stressors need to be considered in climate change research.

Computable species descriptions and nanopublications: applying ontology-based technologies to dung beetles (Coleoptera, Scarabaeinae).

Background: Taxonomy has long struggled with analysing vast amounts of phenotypic data due to computational and accessibility challenges. Ontology-based technologies provide a framework for modelling semantic phenotypes that are understandable by computers and compliant with FAIR principles. In this paper, we explore the use of Phenoscript, an emerging language designed for creating semantic phenotypes, to produce computable species descriptions. Our case study centers on the application of this approach to dung beetles (Coleoptera, Scarabaeinae). New information: We illustrate the effectiveness of Phenoscript for creating semantic phenotypes. We also demonstrate the ability of the Phenospy python package to automatically translate Phenoscript descriptions into natural language (NL), which eliminates the need for writing traditional NL descriptions. We introduce a computational pipeline that streamlines the generation of semantic descriptions and their conversion to NL. To demonstrate the power of the semantic approach, we apply simple semantic queries to the generated phenotypic descriptions. This paper addresses the current challenges in crafting semantic species descriptions and outlines the path towards future improvements. Furthermore, we discuss the promising integration of semantic phenotypes and nanopublications, as emerging methods for sharing scientific information. Overall, our study highlights the pivotal role of ontology-based technologies in modernising taxonomy and aligning it with the evolving landscape of big data analysis and FAIR principles.

Complex nitrogen sources from agro-industrial byproducts: impact on production, multi-stress tolerance, virulence, and quality of Beauveria bassiana blastospores.

We investigated the impact of various complex organic nitrogen sources on the submerged liquid fermentation of Beauveria bassiana, a versatile entomopathogenic fungus known for producing hydrophilic yeast-like single cells called blastospores. Specifically, we examined yeast extract, autolyzed yeast, inactive yeast, cottonseed flour, corn bran, and corn gluten meal as nitrogen compounds with different carbon-to-nitrogen (C:N) ratios. Our comprehensive analysis encompassed blastospore production, tolerance to abiotic stresses, shelf stability after drying, and virulence against mealworm larvae, crucial attributes for developing effective blastospore-based biopesticides. Notably, cottonseed flour emerged as the optimal nitrogen source, yielding up to 2.5 × 109 blastospores/mL within 3 days in a bioreactor. These blastospores exhibited the highest tolerance to heat stress and UV-B radiation exposure. The endogenous C:N ratio in blastospore composition was also impacted by nitrogen sources. Bioassays with mealworm larvae demonstrated that blastospores from cottonseed flour were the most virulent, achieving faster lethality (lower LT50) and requiring a lower inoculum (LC50). Importantly, blastospores produced with cottonseed flour displayed extended viability during storage, surpassing the retention of viability compared to those from autolyzed yeast over 180 days at 4°C. Despite differences in storage viability, both nitrogen sources conferred similar long-term blastospore bioactivity against mealworms. In summary, this research advances our understanding of the crucial impact of complex organic nitrogen selection on the phenotypic traits of blastospores in association with their intracellular C:N ratio, contributing to the production of ecologically fit, shelf-stable, and virulent propagules for effective pest biocontrol programs. IMPORTANCE: Biological control through entomopathogenic fungi provides essential ecological services in the integrated management of agricultural pests. In the context of submerged liquid fermentation, the nutritional composition significantly influences the ecological fitness, virulence and quality of these fungi. This study specifically explores the impact of various complex organic nitrogen sources derived from agro-industrial byproducts on the submerged liquid fermentation of Beauveria bassiana, a versatile entomopathogenic fungus known for producing hydrophilic yeast-like blastospores. Notably, manipulating the nitrogen source during submerged cultivation can influence the quality, fitness, and performance of blastospores. This research identifies cottonseed flour as the optimal low-cost nitrogen source, contributing to increased production yields, enhanced multi-stress tolerance, heightened virulence with extended shelf life and long-term bioactivity. These findings deepen our understanding of the critical role of nitrogen compound selection in liquid media formulation, facilitating the production of ecologically fit and virulent blastospores for more effective pest biocontrol programs.

Transcriptomic and metabolomic profiling reveals molecular regulatory network involved in flower development and phenotypic changes in two Lonicera macranthoides varieties.

Due to the medicinal importance of the flowers of Xianglei type (XL) Lonicera macranthoides, it is important to understand the molecular mechanisms that underlie their development. In this study, we elucidated the transcriptomic and metabolomic mechanisms that underlie the flower development mechanism of two L. macranthoides varieties. In this study, 3435 common differentially expressed unigenes (DEGs) and 1138 metabolites were identified. These common DEGs were mainly enriched in plant hormone signal transduction pathways. Metabolomic analysis showed that amino acids were the main metabolites of differential accumulation in wild-type (WT) L. macranthoides, whereas in XL, they were flavonoids and phenylalanine metabolites. Genes and transcription factors (TFs), such as MYB340, histone deacetylase 1 (HDT1), small auxin-up RNA 32 (SAUR32), auxin response factor 6 (ARF6), PIN-LIKES 7 (PILS7), and WRKY6, likely drive metabolite accumulation. Plant hormone signals, especially auxin signals, and various TFs induce downstream flower organ recognition genes, resulting in a differentiation of the two L. macranthoides varieties in terms of their developmental trajectories. In addition, photoperiodic, autonomous, and plant hormone pathways jointly regulated the L. macranthoides corolla opening. SAUR32, Arabidopsis response regulator 9 (ARR9), Gibberellin receptor (GID1B), and Constans-like 10 (COL10) were closely related to the unfolding of the L. macranthoides corolla. These findings offer valuable understanding of the flower growth process of L. macranthoides and the excellent XL phenotypes at the molecular level. Supplementary Information: The online version contains supplementary material available at 10.1007/s13205-024-04019-1.

Research on terahertz image analysis of thin-shell seeds based on semantic segmentation.

Assessing crop seed phenotypic traits is essential for breeding innovations and germplasm enhancement. However, the tough outer layers of thin-shelled seeds present significant challenges for traditional methods aimed at the rapid assessment of their internal structures and quality attributes. This study explores the potential of combining terahertz (THz) time-domain spectroscopy and imaging with semantic segmentation models for the rapid and non-destructive examination of these traits. A total of 120 watermelon seed samples from three distinct varieties, were curated in this study, facilitating a comprehensive analysis of both their outer layers and inner kernels. Utilizing a transmission imaging modality, THz spectral images were acquired and subsequently reconstructed employing a correlation coefficient method. Deep learning-based SegNet and DeepLab V3+ models were employed for automatic tissue segmentation. Our research revealed that DeepLab V3+ significantly surpassed SegNet in both speed and accuracy. Specifically, DeepLab V3+ achieved a pixel accuracy of 96.69 % and an intersection over the union of 91.3 % for the outer layer, with the inner kernel results closely following. These results underscore the proficiency of DeepLab V3+ in distinguishing between the seed coat and kernel, thereby furnishing precise phenotypic trait analyses for seeds with thin shells. Moreover, this study accentuates the instrumental role of deep learning technologies in advancing agricultural research and practices.

Diversity of Artemisia argyi germplasm resources based on agronomic and leaf phenotypic traits / 中国中药杂志

In this study, in order to evaluate the phenotypic diversity of Artemisia argyi germplasm resources and improve its efficiency of cultivation and breeding, 100 accessions of A. argyi germplasm resources from 58 regions in China were collected, 20 agronomic traits and leaf phenotypic traits were observed and described. The data were used for phenotypic diversity analysis, correlation analysis, principal component analysis and cluster analysis. The result showed that the genetic diversity index of 20 traits ranged from 0.82 to 4.37, among which the largest was the base depth and the smallest was the leaf width; the coefficient of variation of the 12 quantitative traits ranged from 10.55% to 41.47%. the highest coefficient of variation was the height of dead leaves, and the smallest was the content of chlorophyll, except for the angle of branches, all the quantitative characters tended to be normal distribution. The correlation analysis showed that 28 pairs of traits had significant correlation(P<0.01), and 13 pairs had significant correlation(P<0.05). According to principal component analysis, 20 traits were simplified into 9 principal components, and the cumulative contribution rate was 73.414%, nine traits including plant height, dead leaves heigh, stem diameter, symmetry of leave base, stipule, leaf tip shape, depth of the first pair of lobes, depth of the second pair of lobes and leaf yield were selected as key indexes for evaluating agronomic traits and leaf phenotypic traits of A.argyi germplasm resources. With cluster analysis, 100 accessions of A.argyi were classified into 3 groups, the groupⅠincluded the dwarf plants with thick stem and large leaf, the groupⅡincluded high plants with wide leaf and high yield, the group Ⅲ included dwarf plants with thin stem and flat bottom shape of leaf, which could provide the basis for cultivation identification and variety breeding of A.argyi germplasm resources.

Variation and correlation analysis on phenotypic traits of Scutellaria baicalensis from different strains / 中国中药杂志

To research the differences and correlation between Scutellaria baicalensis about phenotypic traits of different strains, 10 aboveground traits and 6 root traits of S. baicalensis in two-year-transplanted plants from 14 different strains were compared respectively, and the SPSS 17.0 statistical software was used for data analysis. It showed that phenotypic traits variation of different S. baicalensis strains was rich and the F value ranged from 3.169 to 71.58. The difference was significant between each other and germplasm 15 performs the most outstanding characters. Correlation analysis showed that there existed a significant correlation between the characters except for lateral root number, root diameter and length. The correlation coefficient between the fresh weight of root and the reed head diameter was up to 0.877. Principal component analysis showed that the average of overall yield per plant and root diameter could be used as the comprehensive reference index for germplasm evaluation. The differences and correlations in phenotypic traits of different S. baicalensis strains, provide theoretical basis for distinguishing germplasm and breeding good varieties of S. baicalensis.