Effect of photoperiod on sexual activity of boar

The main objective of this study was to assess the effect of photoperiod on sexual activity of three breeds of boars: Swedish Landrace (n=34), Large White (n=38), and Duroc (n=32). Boar sexual activity was analysed based on the libido index and intensity of ejaculation. The libido index was calculated as the ratio between the duration of ejaculation and time of preparation until ejaculation. The intensity of ejaculation was the volume of ejaculate (mL) secreted in the unit of time (min). The effect of photoperiod was analysed as the effect of duration of daylight ( lt 12 h and >12 h) within photoperiod intervals (increasing and decreasing). Impact assessment was carried out by applying the General Linear Model procedure. Libido and intensity of ejaculation varied under the impact of photoperiod and the breed of boars. With the increase in age, the boar libido weakened, while the volume of ejaculate and intensity of ejaculation increased. Boars manifested better libido when the daylight lasted longer than 12 h in both photoperiod intervals. Different from libido, the volume of ejaculate and intensity of ejaculation were highest when the daylight was shorter than 12 h, but only in the decreasing photoperiod interval. Swedish Landrace boars manifested best libido, while in the production of sperm the Duroc boars were inferior compared with Swedish Landrace and Large White. The phenotypic relationship among libido, ejaculate volume, and ejaculation intensity ranges from very low to high; however, the coefficients were positive, which indicates the possibility of simultaneous improvement of these traits

Placenta is Capable of Protecting the Male Fetus from Exposure to Environmental Bisphenol A

Embryo-fetal exposure to bisphenol A (BPA) could be related to poor male reproductive parameters in rodents, but this concept has not been convincingly confirmed in humans. We investigated the association of environmental BPA exposure of pregnant women with selected endocrine and anthropometric parameters of male newborns. We analyzed plasma BPA from pregnant mothers, umbilical cord, and placental tissues (n = 117/each group) by liquid chromatography and mass spectrometry. LH, FSH, AMH, TGF beta 2, inhibin B, and selected sex steroids were measured in cord plasma. The infant anthropometric parameters included anogenital distance, stretched penile length, head circumference, birthweight, and length. The median BPA concentrations in maternal and umbilical cord plasma, and in placental tissue were 19.0, 8.0, and 22.2 nmol/L, respectively, the levels thus being over twofold lower in the fetal circulation than in the mother or placenta. The BPA concentrations measured were 100-1000-fold lower than those demonstrated in animal experiments to have endocrine disrupting effects. Multivariable regression analysis indicated no significant correlations between the maternal/fetal/placental BPA concentrations and any of the hormone levels or anthropometric parameter measured. Plasma concentrations of BPA confirmed both maternal, placenta, and fetal exposure to environmental BPA, but the concentrations were orders of magnitude lower than those with documented endocrine disrupting activity. Moreover, the maternal/fetal concentration gradient as well as the lack of correlations of BPA levels with any major endocrine or anthropometric parameters measured in the newborns suggest a protective role for the placenta in reducing fetal exposure to the environmental BPA

Lipidomic analysis of plasma samples from women with polycystic ovary syndrome

Abstract Polycystic ovary syndrome (PCOS) is a common disorder affecting between 5 and 18 % of females of reproductive age and can be diagnosed based on a combination of clinical, ultrasound and biochemical features, none of which on its own is diagnostic. A lipidomic approach using liquid chromatography coupled with accurate mass high-resolution mass-spectrometry (LCHRMS) was used to investigate if there were any differences in plasma lipidomic profiles in women with PCOS compared with control women at different stages of menstrual cycle. Plasma samples from 40 women with PCOS and 40 controls aged between 18 and 40 years were analysed in combination with multivariate statistical analyses. Multivariate data analysis (LASSO regression and OPLSDA) of the sample lipidomics datasets showed a weak prediction model for PCOS versus control samples from the follicular and mid-cycle phases of the menstrual cycle, but a stronger model (specificity 85 % and sensitivity 95 %) for PCOS versus the luteal phase menstrual cycle controls. The PCOS vs luteal phase model showed increased levels of plasma triglycerides and sphingomyelins and decreased levels of lysophosphatidylcholines and phosphatidylethanolamines in PCOS women compared with controls. Lipid biomarkers of PCOS were tentatively identified which may be useful in distinguishing PCOS from controls especially when performed during the menstrual cycle luteal phase

Polycystic ovary syndrome

The document attached has been archived with permission from the editor of the Medical Journal of Australia. An external link to the publisher’s copy is included.Polycystic ovary syndrome (PCOS) affects 5-20% of women of reproductive age worldwide. The condition is characterized by hyperandrogenism, ovulatory dysfunction and polycystic ovarian morphology (PCOM) - with excessive androgen production by the ovaries being a key feature of PCOS. Metabolic dysfunction characterized by insulin resistance and compensatory hyperinsulinaemia is evident in the vast majority of affected individuals. PCOS increases the risk for type 2 diabetes mellitus, gestational diabetes and other pregnancy-related complications, venous thromboembolism, cerebrovascular and cardiovascular events and endometrial cancer. PCOS is a diagnosis of exclusion, based primarily on the presence of hyperandrogenism, ovulatory dysfunction and PCOM. Treatment should be tailored to the complaints and needs of the patient and involves targeting metabolic abnormalities through lifestyle changes, medication and potentially surgery for the prevention and management of excess weight, androgen suppression and/or blockade, endometrial protection, reproductive therapy and the detection and treatment of psychological features. This Primer summarizes the current state of knowledge regarding the epidemiology, mechanisms and pathophysiology, diagnosis, screening and prevention, management and future investigational directions of the disorder.Robert J Norman, Ruijin Wu and Marcin T Stankiewic

How can dairies maximize their profits and properly remunerate their dairy farmers?

ABSTRACT The current pricing process of raw milk in Brazil discourages producers from improving milk composition, which affects both yield and quality of dairy products. Furthermore, small and medium-sized dairies face great difficulties when it comes to planning production. Thus, a linear programming model was developed to price the raw milk and determine the optimal mix (combination of quantities) of dairy products that maximizes total contribution margin (TCM) under daily scenarios of high (January) and low (July) raw milk supplies (summer and winter, respectively) by comparing optimal solutions with actual results. The TCM of optimal and actual mixes were higher in January due to the greater availability of raw material. Packaging was a limiting factor in the production of cheese in optimal mixes. The relationship between unit contribution margin (UCM) and the required amount of raw materials per product unit and resource availability is crucial to defining the mix of dairy products and TCM of the dairy. Casein and raw milk volume showed shadow prices. Under both scenarios, the calculated prices of raw milk were higher than the prices charged by the dairy and were higher in January. The proposed model remunerates the producers based on the quantity and quality of raw milk. The dairy can maximize its TCM by better planning its mix of products with the use of linear programming

Decision support modeling for milk valorization

The research presented in this thesis concerns decision problems in practice that require structured, precise, scientific studies to provide strong, reliable answers. An opportunity to contribute to both practice and science emerged in 2008 when two large, Dutch dairy companies merged, creating FrieslandCampina (FC), which was the fourth largest dairy company in the world at that time. In 2009, a new Milk Valorization & Allocation (MVA) department was created at the corporate level to optimally utilize raw milk (the main raw material) in all business units. The main goal of this research was the development and application of decision support models to help MVA attain its mission of “getting more out of milk.” The dairy processing industry is a specific and challenging research field. This is related to the fact that the raw milk is transformed into thousands of end products via highly interrelated production processes. These processes are affected by uncertainties related to supply, processing capacities, and demand. Attaining high profitability requires a central, integral planning process that facilitates the optimal allocation of raw milk to a large range of products. Optimal allocation of raw milk is achieved when it is successfully allocated to the most profitable end products and all important constraints are taken into account. This process is defined as milk valorization. Contribution to the improvement of milk valorization in the dairy industry was the main objective of this thesis. We approached the problem from a Logistics Management perspective. We focused on decisions supporting the optimal flow of raw materials to end products, from farmers to consumer markets. With the use of Operations Research techniques, we developed quantitative models and frameworks to improve the mid-term milk valorization process. As the first step towards the improvement of milk valorization we developed a mid-term Dairy Valorization Model (DVM). The model creates optimal plans for the allocation of milk, and the production of end products and byproducts. It captures the dynamics of dairy production and incorporates all relevant elements and constraints. The following elements were indicated as important and included in the DVM: recipes based on raw milk composition (dry matter, fat, and protein content); seasonality of raw milk composition and supply; a complete dairy product portfolio; by-product utilization; network of supply regions and production locations; by-product and raw milk transportation; and changes in sale prices. Including all relevant elements assures DVM comprehensiveness. This important aspect achieves truly integral valorization of milk. Furthermore, the developed DVM also fosters understanding of complex, underlying production processes. Moreover, by means of additional analysis we have also shown that the seasonality of raw milk components (dry matter, fat and protein) plays an important role in the valorization process. It considerably affects decisions regarding milk allocation to end products (up to 50% difference in production volumes of clustered end products) and company profit (up to 4% difference in monthly profit). Given the complexity of the dairy system, the development of a high class valorization model required a gradual approach. The developed DVM focuses on the valorization of milk-based end products (main milk products). The production of those products, however, results in large volumes of byproducts.In the second step of this research we investigated the effect of whey valorization (byproduct of cheese) on the valorization of main milk products, as well as the added value of integral valorization (simultaneous valorization of both main and byproducts). We developed a new Integral Dairy Valorization model (IDVM) to allow for an integral milk valorization. We also developed a three-step evaluation approach to compare results of stepwise valorization (in which whey valorization only follows after main milk products valorization) and integral valorization. The results show that the explicit valorization of whey flows leads to significant economic gains for FC. Profit obtained from post processing of whey byproducts amounts to circa 20% of the total profit. Furthermore, the effect of integrating both valorization processes is currently small (on average 0.0089% increase in monthly profit). There is, however, a potential in the integration of two processes. In case demand for, and sale prices of, whey-based products, sale prices of milk powders or processing capacity for whey increases, the gain from the integration can be considerably larger (up to 1200% stronger effect in comparison to the current situation). We have also shown that currently whey products are not profitable enough to drive the production of milk products that are the source of the whey by-product. In the next step we focused on the accuracy of solutions obtained with the DVM. Because the DVM is a deterministic model, uncertainties present in input are not incorporated, and as such the stability of valorization plans is affected. Stability of plans is often referred as to the ‘robustness’ of plans: the degree to which the optimal solution might change if realization of certain input parameters turn out to be different than the forecasted values. The robustness is important, because the valorization plans that are initially indicated as optimal can easily become sub-optimal or costly. Therefore, the overall goal of the third study was to develop a framework for robustness evaluation of valorization plans obtained with deterministic models. We developed a five-step framework comprised of the following: (1) definition of Key Performance Indicators (KPIs), (2) selection of relevant input parameters, (3) definition of scenarios, (4) evaluation of robustness, and (5) extraction of conclusions. The output from Step 4 of the framework is multidimensional, and thus to arrive at the final robustness degree, a number of decisions must be made a priori: acceptable KPIs limits (robustness bounds); evaluation time (month or year); evaluation depth (parameter or element); and the grouping approach of KPIs. The results show that depending on the selection of these aspects different conclusions regarding robustness of valorization plans are obtained, (average robustness degree varied from 48% to 92%), and thus the final conclusions regarding the robustness degree of plans is affected. The overall robustness degree of valorization plans (at FC) obtained with the DVM was 90% and was indicated by FC as sufficiently high to attain successful milk valorization. The calculated robustness degrees also identified the parameters with the greatest effect on robustness (composition and supply of milk). The effectiveness of valorization models is mainly linked to the optimality, feasibility and robustness of obtained plans. However, even if these three aspects are satisfied, the success of the valorization process is still very much dependent on the performance level of actors and units that are involved in the process. Given the fact that processing units (factories) are the most important units in the supply chain of a processing company, because they can easily affect the value of each ton of raw milk used in the production process, the last study investigated the performance of processing units. We developed two Data Envelopment Analysis models for performance measurement and improvement, and applied it to the case study of TNT Express. The models allowed us to identify: inefficient units (30%); parts of efficiency levels (of inefficient units) that result from either management practices (85%) or a favorable external environment (15%); potential reductions in consumed input resources that allow for the same output levels (17% less labor and subcontractors could be used); and role models that can be treated as master units in efficient use of certain inputs and thus should play leading roles in setting benchmarks. We concluded that in order to successfully valorize raw materials, companies should: develop their own valorization model, possess a comprehensible overview of the complete production system; and have access to necessary input data. Furthermore, there is a potential in integrating main product and by-product valorization processes. The added value, however, depends on the information on market and production capacities of by-products and related to them main products. To ensure that possible future integration of both valorizations processes occurs correctly, companies should investigate future market developments and the possibility of increasing production capacity. Moreover, we have also shown that robustness of solutions obtained with deterministic valorization models can be sufficiently high to obtain reliable plans. This means that it is not always necessary to implement complex modeling techniques (such as stochastic programming). To ensure accurate solutions, companies should also focus on improving forecast accuracies of parameters affecting the robustness. The robustness degree should also be regularly assessed with the developed framework. Finally, managers should also focus on performance levels of processing units. A DEA model should be developed to identify inefficient factories and provide new insights to improve performance. In order to properly valorize milk or other food resources to its maximum an integral point of view should be chosen. Operations Research techniques should be used because the complexity of many processing industries makes applying practical rules of thumb insufficient and often inadequate. The models and frameworks developed in this thesis provide new perspective on and new insights into the complex problem of milk valorizations. We have shown that analyses of results obtained with the developed methods can answer many managerial questions, and thus support the decision making process within a company. This improves overall raw material valorization, creates more value for companies, and leads to more sustainable dairy chains

Effect of storage conditions on selected characteristics of eggs derived from green-legged partridge hens

Celem pracy było porównanie wybranych cech jaj pochodzących od kur rasy Zielononóżka kuropatwiana w zależności od czasu i temperatury ich przechowywania. Materiałem doświadczalnym były jaja uzyskane od 50-tygodniowych kur tej rasy. Badania przeprowadzono na próbie 60 jaj, podzielonych losowo na trzy grupy doświadczalne. Grupę pierwszą oceniano jako jaja świeże, drugą grupę stanowiły jaja przechowywane w chłodziarce w temperaturze 6 °C przez 20 dni, a trzecią grupę jaja przechowywane przez 20 dni w temperaturze 24 °C. Oceniano jaja w całości, a następnie po ich wybiciu na szklaną płytkę. Przechowywanie jaj przez 20 dni w temperaturze 24 °C znacznie zintensyfikowało procesy ich starzenia się. Zwiększone parowanie wody z treści jaj w tej temperaturze wpłynęło na zwiększenie wysokości komory powietrznej, istotne zmniejszenie masy jaj (z 32,55 do 27,93 g), zmniejszenie zawartości białka ogólnego (z 32,55 do 27,93 g) oraz obniżenie jednostek Hougha (JH) białka i wzrost zasadowości białka. Zaobserwowano istotnie większą (p ≤ 0,05) masę żółtka w jajach przechowywanych przez 20 dni w temperaturze 24 °C w porównaniu z masą żółtka jaj przechowywanych w temperaturze 6 °C, co było spowodowane przenikaniem wody z białka. Jednocześnie zaobserwowano istotne (p ≤ 0,01) zwiększenie indeksu żółtka oraz nieznaczny wzrost wartości pH – z 6,01 do 6,62. Temperatura 24 °C i wydłużony czas przechowywania jaj wywarły niekorzystny wpływ na dynamikę zmian zachodzących w ocenianych jajach, co przyczyniło się do utraty ich świeżości.The objective of the research study was to compare some selected characteristics of eggs derived from hens of the Green-legged Partridge species depending on the time and temperature of storage. The experimental material comprised the eggs derived from 50 weeks old hens of this species. A sample of 60 eggs were analyzed; the eggs were divided randomly into three experimental groups. The eggs in the first group were assessed as fresh eggs, the eggs in the second group were stored in a refrigerator at a temperature of 6 °C for 20 days, and the eggs in the third group were stored at a temperature of 24 °C for 20 days. At first, the whole eggs were assessed; next, the eggs were spilled onto a glass plate and, then, assessed. The storing of eggs for 20 days at a temperature of 24 °C significantly intensified the processes of their ageing. An increased evaporation of water from the eggs caused the height of air cell to increase, the weight of eggs to significantly decrease (from 32.55 to 27.93 g), the content of total white to decrease (from 32.55 to 27.93 g), the IH of white to drop, and the alkalinity of white to grow. Significantly (p ≤ 0.05) greater yolk weight was observed in the eggs stored for 20 days at 24 °C than in the eggs stored at 6 °C, which was due to penetration of water from the albumen. At the same time, it was reported a significant increase (p ≤ 0,01) in the yolk index and a slight increase in the value of pH from 6.01 to 6.62. The temperature of 24 °C and the extended time of storing the eggs negatively affected the dynamics of changes occurring in the eggs assessed and this fact caused that the eggs lost their freshness

A framework for measuring efficiency levels: the case of express depots

The efficiency and effectiveness in any distribution network is largely determined by the performance of depots in such a network. The purpose of this study is to develop a methodological framework to evaluate the performance of distribution centers of express companies. The framework is based on Data Envelopment Analysis and was validated on a set of 44 depots of a large express service provider situated in the United Kingdom. The analysis revealed that 31 depots out of 44 are efficient. Furthermore, statistical analyses identified four factors influencing the efficiency scores of express transportation depots