Accurate Sex Research Articles

Morphometric analysis of the hard palate in sex estimation among koreans using three-dimensional computed tomography

Accurate sex estimation is crucial for comprehensive analysis of the biological profiles of unidentified human skeletal remains. However, there is a notable lack of research specifically addressing the morphometrics of the hard palate. Therefore, this study aimed to derive discriminant equations using the hard palate and assess their applicability for sexing partial skeletal remains in a contemporary Korean population. Statistical analyses were performed for 24 measurements derived from three-dimensional models of the hard palate, generated using computed tomography scans of 301 individuals (156 males, 145 females). Descriptive statistics revealed significant sexual dimorphism in the mean comparison of hard palate sizes between Korean males and females, with males exhibiting larger palates across all measurements (p < 0.05). Discriminant function score equations were generated to aid in sex determination. Univariate analysis yielded an accuracy range of 57.8–75.1%, whereas the stepwise method achieved an accuracy of 80.7% with five selected variables: IF-PNS, GFL-GFR, IF-GFR, Pr-EcL, and Pr-EnR. The results of this metric analysis demonstrate the usefulness of the hard palate for sex estimation in the contemporary Korean population. These findings have potential implications for forensic investigations, archeological studies, and population-specific anatomical research.

Gene Drive and Symbiont Technologies for Control of Mosquito-Borne Diseases.

Mosquito-borne diseases, such as dengue and malaria, pose a significant burden to global health. Current control strategies with insecticides are only moderately effective. Scalable solutions are needed to reduce the transmission risk of these diseases. Symbionts and genome engineering-based mosquito control strategies have been proposed to address these problems. Bacterial, fungal, and viral symbionts affect mosquito reproduction, reduce mosquito lifespan, and block pathogen transmission. Field tests of endosymbiont Wolbachia-based methods have yielded promising results, but there are hurdles to overcome due to the large-scale rearing and accurate sex sorting required for Wolbachia-based suppression approaches and the ecological impediments to Wolbachia invasion in replacement approaches. Genome engineering-based methods, in which mosquitoes are genetically altered for the modification or suppression of wild populations, offer an additional approach for control of mosquito-borne diseases. In particular, the use of gene drive alleles that bias inheritance in their favor is a potentially powerful approach. Several drives are frequency dependent, potentially giving them broadly similar population dynamics to Wolbachia. However, public acceptance and the behavior of released drives in natural mosquito populations remain challenges. We summarize the latest developments and discuss the knowledge gaps in both symbiont- and gene drive-based methods.

Automated High-Throughput Biological Sex Identification from Archeological Human Dental Enamel Using Targeted Proteomics.

Biological sex is key information for archeological and forensic studies, which can be determined by proteomics. However, the lack of a standardized approach for fast and accurate sex identification currently limits the reach of proteomics applications. Here, we introduce a streamlined mass spectrometry (MS)-based workflow for the determination of biological sex using human dental enamel. Our approach builds on a minimally invasive sampling strategy by acid etching, a rapid online liquid chromatography (LC) gradient coupled to a high-resolution parallel reaction monitoring (PRM) assay allowing for a throughput of 200 samples per day (SPD) with high quantitative performance enabling confident identification of both males and females. Additionally, we developed a streamlined data analysis pipeline and integrated it into a Shiny interface for ease of use. The method was first developed and optimized using modern teeth and then validated in an independent set of deciduous teeth of known sex. Finally, the assay was successfully applied to archeological material, enabling the analysis of over 300 individuals. We demonstrate unprecedented performance and scalability, speeding up MS analysis by 10-fold compared to conventional proteomics-based sex identification methods. This work paves the way for large-scale archeological or forensic studies enabling the investigation of entire populations rather than focusing on individual high-profile specimens. Data are available via ProteomeXchange with the identifier PXD049326.

Deep learning in sex estimation from photographed human mandible using the Human Osteological Research Collection

Sex estimation is a necessary part of forensic and osteological analyses of skeletal human remains in the construction of a biological profile. Several skeletal traits are sexually dimorphic and used for skeletal sex estimation. The human mandible and morphological traits therein have been long used for sex estimation, but the validity of using the mandible in this purpose has become a concern. In this study, we examined the potential of artificial intelligence (AI) and especially deep learning (DL) to provide accurate sex estimations from the mandible. We used 193 modern South African mandibles from the Human Osteological Research Collection (HORC) in the Sefako Makgatho Health Sciences university with known sex to conduct our study. All mandibles were photographed from the same angle and the photographs were analyzed with an open-source DL software. The best-performing DL algorithm estimated the sex of males with 100% accuracy and females with 76.9% accuracy. However, further studies with a higher number of specimens could provide more reliable validity for using AI when building the biological profile from skeletal remains.

Automatic segmentation and classification of frontal sinuses for sex determination from CBCT scans using a two-stage anatomy-guided attention network

Sex determination is essential for identifying unidentified individuals, particularly in forensic contexts. Traditional methods for sex determination involve manual measurements of skeletal features on CBCT scans. However, these manual measurements are labor-intensive, time-consuming, and error-prone. The purpose of this study was to automatically and accurately determine sex on a CBCT scan using a two-stage anatomy-guided attention network (SDetNet). SDetNet consisted of a 2D frontal sinus segmentation network (FSNet) and a 3D anatomy-guided attention network (SDNet). FSNet segmented frontal sinus regions in the CBCT images and extracted regions of interest (ROIs) near them. Then, the ROIs were fed into SDNet to predict sex accurately. To improve sex determination performance, we proposed multi-channel inputs (MSIs) and an anatomy-guided attention module (AGAM), which encouraged SDetNet to learn differences in the anatomical context of the frontal sinus between males and females. SDetNet showed superior sex determination performance in the area under the receiver operating characteristic curve, accuracy, Brier score, and specificity compared with the other 3D CNNs. Moreover, the results of ablation studies showed a notable improvement in sex determination with the embedding of both MSI and AGAM. Consequently, SDetNet demonstrated automatic and accurate sex determination by learning the anatomical context information of the frontal sinus on CBCT scans.

Identification of Sex-Associated Genetic Markers in Pistacia lentiscus var. chia for Early Male Detection.

Pistacia lentiscus var. chia is a valuable crop for its high-added-value mastic, a resin with proven pharmaceutical and cosmeceutical properties harvested from the male tree trunk. To achieve the maximum economic benefits from the cultivation of male mastic trees, it is important to develop early sex diagnosis molecular tools for distinguishing the sex type. Thus far, the work on sex identification has focused on Pistacia vera with promising results; however, the low transferability rates of these markers in P. lentiscus necessitates the development of species-specific sex-linked markers for P. lentiscus var. chia. To our knowledge, this is the first report regarding: (i) the development of species-specific novel transcriptome-based markers for P. lentiscus var. chia and their assessment on male, female and monoecious individuals using PCR-HRM analysis, thus, introducing a cost-effective method for sex identification with high accuracy that can be applied with minimum infrastructure, (ii) the effective sex identification in mastic tree using a combination of different sex-linked ISSR and SCAR markers with 100% accuracy, and (iii) the impact evaluation of sex type on the genetic diversity of different P. lentiscus var. chia cultivars. The results of this study are expected to provide species-specific markers for accurate sex identification that could contribute to the selection process of male mastic trees at an early stage for mass propagation systems and to facilitate future breeding efforts related to sex-linked productivity and quality of mastic resin.

Sex identification of ducklings based on acoustic signals

Sex identification of ducklings is a critical step in the poultry farming industry, and accurate sex identification is beneficial for precise breeding and cost savings. In this study, a method for identifying the sex of ducklings based on acoustic signals was proposed. In the first step, duckling vocalizations were collected and an improved spectral subtraction method and high-pass filtering were applied to reduce the influence of noise. Then, duckling vocalizations were automatically detected by using a double-threshold endpoint detection method with three parameters: short-time energy (STE), short-time zero-crossing rate (ZCR), and duration (D). Following the extraction of Mel-Spectrogram features from duckling vocalizations, an improved Res2Net deep learning algorithm was used for sex classification. This algorithm was introduced with the Squeeze-and-Excitation (SE) attention mechanism and Ghost module to improve the bottleneck of Res2Net, thereby improving the model accuracy and reducing the number of parameters. The ablative experimental results showed that the introduction of the SE attention mechanism improved the model accuracy by 2.01%, while the Ghost module reduced the number of model parameters by 7.26M and the FLOPs by 0.85G. Moreover, this algorithm was compared with five state-of-the-art (SOTA) algorithms, and the results showed that the proposed algorithm has the best cost-effectiveness, with accuracy, recall, specificity, number of parameters, and FLOPs of 94.80%, 94.92%, 94.69%, 18.91M, and 3.46G, respectively. After that, the vocalization detection score and the average confidence strategy were used to predict the sex of individual ducklings, and the accuracy of the proposed model reached 96.67%. In conclusion, the method proposed in this study can effectively detect the sex of ducklings and serve as a reference for automated sex identification of ducklings.

Prediction of brain sex from EEG: using large-scale heterogeneous dataset for developing a highly accurate and interpretable ML model

This study presents a comprehensive examination of sex-related differences in resting-state electroencephalogram (EEG) data, leveraging two different types of machine learning models to predict an individual's sex. We utilized data from the Two Decades-Brainclinics Research Archive for Insights in Neurophysiology (TDBRAIN) EEG study, affirming that gender prediction can be attained with noteworthy accuracy. The best performing model achieved an accuracy of 85% and an ROC AUC of 89%, surpassing all prior benchmarks set using EEG data and rivaling the top-tier results derived from fMRI studies. A comparative analysis of LightGBM and Deep Convolutional Neural Network (DCNN) models revealed DCNN's superior performance, attributed to its ability to learn complex spatial-temporal patterns in the EEG data and handle large volumes of data effectively. Despite this, interpretability remained a challenge for the DCNN model. The LightGBM interpretability analysis revealed that the most important EEG features for accurate sex prediction were related to left fronto-central and parietal EEG connectivity. We also showed the role of both low (delta and theta) and high (beta and gamma) activity in the accurate sex prediction. These results, however, have to be approached with caution, because it was obtained from a dataset comprised largely of participants with various mental health conditions, which limits the generalizability of the results and necessitates further validation in future studies. . Overall, the study illuminates the potential of interpretable machine learning for sex prediction, alongside highlighting the importance of considering individual differences in prediction sex from brain activity.

Sex Estimation From Measurements of the Mastoid Triangle and Volume of the Mastoid Air Cell System Using Classical and Machine Learning Methods: A Comparative Analysis.

Previous studies on the sexual dimorphism of the mastoid triangle have typically focused on linear and area measurements. No studies in the literature have used mastoid air cell system volume measurements for direct anthropological or forensic sex determination. The aims of this study were to investigate the applicability of mastoid air cell system volume measurements and mastoid triangle measurements separately and combined for sex estimation, and to determine the accuracy of sex estimation rates using machine learning algorithms and discriminant function analysis of these data. On 200 computed tomography images, the distances constituting the edges of the mastoid triangle were measured, and the area was calculated using these measurements. A region-growing algorithm was used to determine the volume of the mastoid air cell system. The univariate sex determination accuracy was calculated for all parameters. Stepwise discriminant function analysis was performed for sex estimation. Multiple machine learning methods have also been used. All measurements of the mastoid triangle and volumes of the mastoid air cell system were higher in males than in females. The accurate sex estimation rate was determined to be 79.5% using stepwise discriminant function analysis and 88.5% using machine learning methods.

Cephalometric radiograph-based approach for sex determination using maxillary sinus index in Surabaya, Indonesia

Accurate sex determination is a critical aspect of individual identification in various fields, including anthropology, forensic science, and archaeology. Various parameters from the skull, mandible, pelvis, and long bones are commonly utilized for this purpose. Recently, the potential of the maxillary sinus as a sex-discriminatory parameter has been studied by Khaitan et al. through the analysis of lateral cephalometric radiography. This study aimed to evaluate the feasibility of implementing the sex determination formula devised by Khaitan et al. for the adult population of Surabaya, Indonesia. For this purpose, 130 digital cephalometric radiographs of outpatients in the DHDC Dental Office in Surabaya, Indonesia, were assessed. The maxillary sinus height and width were measured to derive the maxillary sinus index (MSI) and calculate the discriminant score (D) for sex identification. This study revealed that the maxillary sinus’s average height in males was 37.111+5.13 mm, while in females, it was 34.538+4.36 mm. Males had an average maxillary sinus width of 44.152+4.11 mm, while in females it was of 38.849+3.33 mm. The MSI values for males (1.204±0.14) were higher than for females (1.135±0.10). The discriminant scores showed notable variations between males and females, with an 86% success rate for females and 27.8% for males. The present study provides evidence that the Khaitan formula can serve as a valuable complementary approach for sex determination in females. Sex determination based on the MSI is thought to be a population-dependent parameter in forensic sciences and requires careful interpretation in its application.

Accurate sex prediction of cisgender and transgender individuals without brain size bias

The increasing use of machine learning approaches on neuroimaging data comes with the important concern of confounding variables which might lead to biased predictions and in turn spurious conclusions about the relationship between the features and the target. A prominent example is the brain size difference between women and men. This difference in total intracranial volume (TIV) can cause bias when employing machine learning approaches for the investigation of sex differences in brain morphology. A TIV-biased model will not capture qualitative sex differences in brain organization but rather learn to classify an individual’s sex based on brain size differences, thus leading to spurious and misleading conclusions, for example when comparing brain morphology between cisgender- and transgender individuals. In this study, TIV bias in sex classification models applied to cis- and transgender individuals was systematically investigated by controlling for TIV either through featurewise confound removal or by matching the training samples for TIV. Our results provide strong evidence that models not biased by TIV can classify the sex of both cis- and transgender individuals with high accuracy, highlighting the importance of appropriate modeling to avoid bias in automated decision making.

Sexing of cattle embryos using RNA-sequencing data or polymerase chain reaction based on a complete sequence of cattle chromosome Y.

When necessary, RNA-sequencing data or polymerase chain reaction (PCR) assays can be used to determine the presence of the chromosome Y (ChrY) in samples. This information allows for biological variation due to sexual dimorphism to be studied. A prime example is when researchers conduct RNA-sequencing of single embryos, or conceptuses, prior to the development of gonads. A recent publication of a complete sequence of the ChrY has removed limitations for the development of these procedures in cattle, otherwise imposed by the absence of a ChrY in the reference genome. Using the sequence of the cattle ChrY and transcriptome data, we conducted a systematic search for genes in the ChrY that are exclusively expressed in male tissues. The genes ENSBIXG00000029763, ENSBIXG00000029774, ENSBIXG00000029788, and ENSBIXG00000029892 were consistently expressed across male tissues and lowly expressed or absent in female samples. We observed that the cumulative values of counts per million were 2688-fold greater in males than the equivalent values in female samples. Thus, we deemed these genes suitable for the sexing of samples using RNA-sequencing data. We successfully used this set of genes to infer the sex of 22 cattle blastocysts (8 females and 14 males). Additionally, the completed sequence of the cattle ChrY has segments in the male-specific region that are not repeated. We designed a pair of oligonucleotides that targets one of these non-repeated regions in the male-specific sequence of the ChrY. Using this pair of oligonucleotides, in a multiplexed PCR assay with oligonucleotides that anneal to an autosome chromosome, we accurately identified the sex of cattle blastocysts. We developed efficient procedures for the sexing of samples in cattle using either transcriptome data or their DNA. The procedures using RNA-sequencing will greatly benefit researchers who work with samples limited in cell numbers which are only sufficient to produce transcriptome data. The oligonucleotides used for the accurate sexing of samples using PCR are transferable to other cattle tissue samples.

A Review of Key Techniques for in Ovo Sexing of Chicken Eggs

The identification of chicken sex before hatching is an important problem in large-scale breeding applications in the poultry industry. This paper systematically reviews the key techniques for in ovo sexing of chicken eggs before hatching and presents recent research on molecular-based, spectral-based, acoustic-based, morphology-based, and volatile organic compound (VOC)-based technologies. Molecular-based methods are standard techniques for accurate sexing but require perforations by skilled technicians in certified laboratories to extract egg contents. Spectral-based techniques show great potential as noninvasive methods but require complex data processing and modeling. Acoustic-based techniques are sensitive to environmental noise. Morphology-based studies on the outer shape of the eggshell and distribution of blood vessels provide novel methods for in ovo sexing of chicken eggs. However, they face challenges such as the color, thickness, and smoothness of the eggshell. VOC profiling of chicken eggs allows sexing in the early stages of incubation; however, the VOC composition may be influenced by species or feed, and more research is required to explore potential applications. In addition, recent breakthroughs on in ovo chicken egg sexing are discussed. Physiological changes in chicken eggs during the whole incubation period have been well studied using metabolism and phenotype tools to enhance mechanism recognition. Furthermore, various sensing techniques, from the X-ray to terahertz range, and deep learning algorithms have been employed for data acquisition, processing, mining, and modeling to capture and analyze key features. Finally, commercialization and practical applications are discussed. This study provides a reference for in ovo sexing of chicken eggs before hatching in the poultry industry.

Sexual dimorphism in Louisiana pine snakes (Pituophis ruthveni).

The Louisiana pine snake, Pituophis ruthveni, is a cryptic, federally threatened snake species with several fragmented populations in Louisiana and Texas, USA. There are currently four captive breeding populations in zoos in the USA; however, little scientific data exists on their life history and anatomy. Accurate sex determination and identification of normal reproductive anatomy are an essential part of a veterinary exam and conservation programs. The authors had encountered various cases of sex misidentification in this species that were attributed to lack of lubrication of the sexing probes and enlarged musk glands. Anecdotal observation led to a hypothesis of sexual dimorphism based on body and tail shape. To test this hypothesis, we measured body length, tail length and width, and body to tail taper angle in 15 P. ruthveni (9 males and 6 females). We also obtained tail radiographs of all animals to document the presence of mineralized hemipenes. Significant dimorphism was identified in relative tail length, width, and taper angle; females consistently exhibited a more acute taper angle. Contrary to previous studies in other Pituophis species, a male-biased sexual size dimorphism was not identified. Mineralized hemipenes were confirmed in all males (a newly described trait in this species), and we found that the lateral view was consistently more reliable for identification of hemipenes compared to the ventrodorsal view. This information contributes to the scientific community's understanding of this species and is of use to biologists and veterinarians working towardconservation of this threatened species.

Evaluation of primers targeting chromo helicase DNA-binding gene (CHD) for molecular sexing identification in four bird families

&lt;p&gt;&lt;span class="fontstyle0"&gt;Objective: &lt;/span&gt;&lt;/p&gt;&lt;p&gt;&lt;span class="fontstyle2"&gt;Sex determination of birds is crucial role in breeding and conservation purposes. Genomic approaches by using basis of bird sex polymorphism are accepted to generate an accurate sexing procedure. The PCR method is commonly used and known to provide accurate test results in determining the sex of birds, but its successes is strongly influenced by the compatibility of the primers used with the DNA template. This study aimed to determine the potential use of CHD1LF/CHD1LR targeting CHD gene fragment in 4 species from Phasianidae, Psittacidae, Estrildidae, and Passeridae families.&lt;/span&gt;&lt;/p&gt;&lt;p&gt;&lt;span class="fontstyle2"&gt;&lt;br /&gt;&lt;/span&gt;&lt;span class="fontstyle0"&gt;Method: &lt;/span&gt;&lt;/p&gt;&lt;p&gt;&lt;span class="fontstyle2"&gt;Blood samples (n= 30) from representatives of species in 4 families above were collected for DNA isolation, then PCR test was performed using CHD1LF/CHD1LR primers. The PCR results obtained were compared with positive controls, necropsy examination and information from bird sellers.&lt;/span&gt;&lt;/p&gt;&lt;p&gt;&lt;span class="fontstyle2"&gt;&lt;br /&gt;&lt;/span&gt;&lt;span class="fontstyle0"&gt;Result: &lt;/span&gt;&lt;/p&gt;&lt;p&gt;&lt;span class="fontstyle2"&gt;The results showed that the primer CHD1LF/CHD1LR could be used in Phasianidae,&lt;br /&gt;Psittacidae, Estrildidae, and Passeridae families. The PCR product was confirmed to be same as well as the positive control and necropsy results. It is demonstrated that male birds showed a single band (474 bp), while double bands (474 and 319 bp) were observed in female birds. Different accuracies were observed during this study between molecular approach and manual sexing by bird seller i.e:&lt;br /&gt;sparrows (46%) and finches (50%), while the accuracy of parakeets was 75%, and quails 80%.&lt;/span&gt;&lt;/p&gt;&lt;p&gt;&lt;span class="fontstyle2"&gt;&lt;br /&gt;&lt;/span&gt;&lt;span class="fontstyle0"&gt;Conclusions: &lt;/span&gt;&lt;/p&gt;&lt;p&gt;&lt;span class="fontstyle2"&gt;Primer CHD1LF/CHD1LR can be used to determine the sex of birds from the families&lt;br /&gt;Phasianidae, Psittacidae, Estrildidae, and Passeridae. Our study showed that molecular-based method is valuable and able to reduce error rate to 100% in bird sexing procedures.&lt;/span&gt; &lt;br /&gt;&lt;br /&gt;&lt;/p&gt;&lt;p&gt; &lt;/p&gt;

IDENTIFICATION OF SEX FROM PALATAL BONES USING MULTI-SLICE COMPUTED TOMOGRAPHY SCAN IN A SAMPLE OF ADULT EGYPTIAN POPULATION

Background: Identification is the cornerstone in forensic medicine. Accurate sex identification from fragmented bones is a challenging medicolegal task. The hard palate is a well-protected part in the skull base with sexually dimorphic characters.

Human Sexuality Education for Counseling Students, An Ethical Imperative: A Special Commentary

Human sexuality is a profound and multifaceted component of the human condition that is universally experienced. As such, it is an inevitability that issues related to human sexuality will come up in counseling settings; however, there is a lack of medically accurate sex education in K-12 schools. Additionally, there is no requirement, except for in three states, for students in mental health counseling programs to complete a course on human sexuality. While human sexuality is not a specific competency outlined by CACREP or ACA, it is universally experienced by all clients and counselors. This special commentary highlights the ethical need for counselors and counselor educators to be prepared to best serve their clients, and most importantly do no harm.

A Comparison of Feathers and Oral Swab Samples as DNA Sources for Molecular Sexing in Companion Birds.

The early age determinism of the sex in case of monomorphic birds is very important, because most companion birds have no distinct sexual dimorphic traits. Molecular genetic sexing was proved to be one of the most accurate sex determinations in monomorphic birds. The aim of this study was to compare the results obtained by PCR performed on isolate genomic DNA from paired samples of feathers and oral swabs collected from the same individuals. Samples of oral swabs (n = 101) and feathers (n = 74) were collected from 101 companion birds from four different species (Columba livia domestica, Psittacula krameri, Neophema splendida and Agapornis spp.). The PCR was performed for the amplification of the CHD1W and CHD1Z genes in females and the CHD1Z gene in males. The overall PCR success rate of sex determination was significantly higher from oral swabs than from feathers. The PCR success rate from oral swabs was higher in juveniles and from feathers was significantly higher in adults. The similarity between the oral swab and feathers was obtained in 78.38% of the birds. Oral swabs proved to be a more reliable sample for genetic sex determination in the species tested in this study.

Determining sex in golden eagle (Aquila chrysaetos) nestlings

Incorporating sex ratios of nestlings into population viability studies increases knowledge of overall health of endangered populations. Currently, a reliable non-invasive method to identify the sex of golden eagle nestlings is not available; however, claims are commonly made based on morphology. Ten biometric measurements from 43 Scottish golden eagles aged 2–7.5 weeks were assessed to see if sex could actually be determined using this non-invasive methodology. Sex was confirmed via molecular analysis of blood samples. Discrete and principal component analyses of the different biometrics could not correctly determine individual nestling sex. Therefore, despite being more invasive, molecular sexing remains the recommended tool of choice for accurate sex identification of Scottish golden eagle nestlings younger than 7.5 weeks of age. This has important implications for golden eagle field studies where empirical morphological measurements are frequently and typically taken, but we have shown are not reliable in determining the sex of such young nestlings.

Evaluating the importance of accurate sex ratios on egg deposition targets and conservation limit compliance for Atlantic salmon (Salmo salarL.) in the River Tamar, south‐west England

AbstractEffective management of Atlantic salmon requires a suite of metrics that are fed into stock assessment models to assess stock compliance within individual rivers in relation to estimated conservation limits. Key among metrics required to assess compliance are the number of adult female spawners within each adult sea age class and their corresponding egg deposition rates. Owing to the current need to conserve salmon stocks, adult sex ratios used to calculate egg deposition estimates often depend on data derived from historic lethal sampling. Using non‐invasive sampling and an accurate genetic sex test, we determined the proportion of female fish in two adult life history stages (one sea winter and two sea winter) of Atlantic salmon from the River Tamar, an Environment Agency (England) Monitored River. Our results suggested that phenotypic‐based sexing of Tamar salmon was unreliable, especially for early run fish and that the proportion of female salmon has been under‐estimated, thereby leading to consistent under‐estimation of egg deposition rates.