Actual Milk Research Articles

Hybridization-driven synchronous regeneration of biosensing interfaces for Listeria monocytogenes based on recognition of fullerol to single- and double-stranded DNA

A novel sensitive and reusable electrochemical biosensor for Listeria monocytegenes DNA has been constructed based on the recognition of water-soluble hydroxylated fullerene (fullerol) to single- and double-stranded DNA. First, the fullerol was electrodeposited on glassy carbon electrode (GCE), acting as a matrix for non-covalent adsorption of single-stranded probe DNA. Upon hybridization with the target DNA, the double helix structure was formed and desorbed from the electrode surface, driving synchronous regeneration of the biosensing interfaces. The biosensor showed a probe DNA loading density of 144 pmol∙cm−2 with the hybridization efficiency of 72.2%. The biosensor is applicable for the analysis of target DNA in actual milk samples with recoveries between 101.0% and 104.0%. This sensing platform provides a simple method for the construction of sensitive and reusable biosensor to monitor Listeria monocytogenes-related food pollution.

Deep eutectic solvent-functionalized amorphous UiO-66 for efficient extraction and ultrasensitive analysis of perfluoroalkyl substances in infant milk powder

In this study, a convenient and effective method for determination of perfluoroalkyl substances (PFASs) in infant formula was developed based on a novel dispersive solid-phase extraction using deep eutectic solvent-functionalized amorphous UiO-66 (DES/aUiO-66) as sorbent. The synthesis of materials could be achieved without the use of complex and environmentally unfriendly procedures. Parameters were systematically investigated to establish a simple, fast, and efficient green pretreatment method. The method demonstrated high sensitivity, good precision, a detection limit of 0.330–0.529 ng·kg−1, and low matrix effects (< 12.8%). The mechanism for this material was elucidated by ab initio molecular dynamics (AIMD) simulations and quantum chemistry calculations. The presence of massive pore structures and collectively synergistic binding sites facilitated affinity adsorption toward PFASs. Finally, this method was applied to the monitoring of PFASs in 10 actual milk powder samples. This groundbreaking approach opens new possibilities for the advancement of analytical techniques and food safety monitoring.

Relationships Between Partial Milk Yield and Actual Milk Yield According to Parity in Buffaloes

In this study, the relationships between 100-day of partial milk yield and 270-day of additive and total milk yield of buffaloes according to different parity were investigated. A total of 697 lactation records belonging to 135 heads of buffalo and seven lactations were used in the material. The relationships between the animals' 100-day partial milk yield for 270-day and total milk yield were analyzed for seven lactations. In the study, 100-day milk yield was taken as an independent variable, 270-day and total milk yields as dependent variables, and possible relationships were determined according to simple and multiple linear regression analysis methods. The average lactation period was 256.74 ± 2.61 days, the average 270-day additive milk yield was 2078 ± 65.26 litres and the average total milk yield was 1831 ± 89.57 litres. The daily average milk yields were 7.69 ± 0.11 and 7.08 ± 0.07 liters for 270-day and 100-day respectively. The correlation coefficients were calculated for each parity and calculated as 0.901 (p &amp;lt; 0.01) between the 100-day and 270-day additive yield for the general group. The simple and multiple linear regression equations were shown as [V270 = 470.72 + 1.737 V100 (R2 = 80.2%)], [V270 = 966.23 + 0.645 V100 + 0.001V1002 (R2 = 82.4%)] for the groups. As the parity of lactation increased, it was seen that the determination coefficients were increased. Finally, predicting the total lactation yield by using 100-day of partial milk yield has the highest accuracy.

Milking Temperament and Its Association with Test-Day Milk Yield in Bulgarian Murrah Buffaloes.

The goal of this research was to evaluate milking temperament and its relationship with test-day milk (TDMY0) yield in Bulgarian Murrah buffaloes. This study involved 90 buffalo cows reared under a tie-stall production system which were milked twice a day with a milking pipeline. The behavioral responses of the buffaloes were reported during preparation for milking and during actual milking. The average temperament score during preparation for milking was 1.83, and 1.93 during milking itself. The most common reaction was leg lifting (18.9%), followed by cows moving on the stall bed (10%), definite kicking (9.9%), and 13.3% managing to remove the milking cluster during milking. The frequency of buffaloes showing adverse reactions (scores 4 and 5) increased considerably during milking compared to preparation for milking. Repeated scoring of temperament during the same lactation did not show a significant difference in the frequency of temperament assessments both in preparation for milking and during milking. The minimal difference may be due to the accuracy of the assessment or a momentary change in the condition of the animals during the two scorings. Cows with the most unwanted milking behavior (scores 5 and 4) had the highest LS means for TDMY, 8.18 kg and 7.65 kg, respectively. The reasons for these buffaloes remaining until later lactations was their high milk yield and the injection of oxytocin before milking, which helps them to be fully milked.

Использование геномной оценки в совершенствовании продуктивных качеств коров голштинской породы

Abstract. Purpose of the study is analysis of productive and reproductive qualities of the Holstein cattle of the Tyumen region in comparison with the leading American enterprises using genomic selection. Materials and methods. Zootechnical, statistical and economic methods were used. As part of the work, the tasks were solved to consider the growth and development of replacement young animals; the main indicators of reproduction of heifers and cows of the main herd were analyzed; the milk productivity of cows and first-calf heifers was estimated according to the primary accounting data; a zootechnical assessment of sires used in the economy was carried out; the results of the genomic assessment were compared with the actual milk production. The scientific novelty of the work lies in the fact that genotyping was carried out in the conditions of a large industrial complex, because the use of genomic evaluation was not widely used in farms in the Russian Federation. Research results. The indicators of the intensity of growth of replacement young animals grown in the conditions of the Evika-Agro enterprise correspond to the world standards of the breed, and in some cases exceed them. The intensity of growing heifers allows for earlier insemination, which also contributes to early calving - 98% of animals calve up to 25 months of age. Estimates of milk production are largely consistent with those of advanced farms in the United States. “Evika-Agro” LLC uses outstanding sires from the world’s gene pool to improve economically useful traits, thereby accelerating the rate of selection. Analysis of the genomic assessment showed a significant discrepancy between the genetic basis of milk production and the actual level of milk production. This is most noticeable in the lifetime earnings index ($ 682) and the average increase in milk per lactation (916.2 kg) between the worst and best heifers in the sample.

Sustainable fodder production and optimization of cow feeding rations in the ar-id climate of southern Ukraine

In the south of Ukraine, which traditionally belongs to the zone of risky land use due to frequent droughts and the last 10–15 years of steadily progressing global warming, the production of rye silage as a basic feed ingredient is gaining the status of an excellent insurance fund, which is essential in the region's feed production, as it will help to remedy the situation with the shortage of juicy fodder. Optimisation of dairy cow feeding rations during lactation in southern Ukraine involves the use of traditional dietary ingredients (corn silage, alfalfa haylage) and innovative ones (rye silage, wet beer pellets), which is mainly due to climate change in recent years. The research used commonly available methods: zootechnical (setting up experiments, developing feed rations, assessing dairy cattle productivity, milk quality, reproduction rates); biological (morphological and biochemical composition of blood); statistical (biometric processing of data) and economic analysis of the research. Thus, in terms of actual milk yield, amount of milk fat and milk protein for 305 days of lactation, cows of all experimental groups outperformed analogues of the control group (milk yield for 305 days of lactation was 7898.0 l; amount of milk fat and protein – 278.7 and 245.1 kg, respectively) by 1.2–3.3 %, by the amount of milk fat – by 5.1–16.9 % and by the amount of milk protein – by 3.4–10.9 % for 305 days of lactation. It was found that the diets of dairy cows of the experimental groups, which included rye silage in different amounts and wet beer pellets, had a positive effect on reducing the duration of the service period, and hence the duration of the intercalation period by 5.5–27.0 days in animals of the I–IV experimental groups compared to cows of the control group. There was a tendency to increase the content of carotene in the blood serum of animals of the II experimental group by 39.5 %, as well as a significant difference of 72.7 % (P &lt; 0.05) and 81,3% (P &lt; 0.01), respectively, in cows of the III and IV experimental groups compared to the same indicator of the control group, which was 209.6 μg/100 ml.

Low-cost and highly sensitive colorimetric and visual detection of amikacin in milk using melamine functionalized gold nanoparticles.

This study developed a rapid, low-cost and highly sensitive analytical method using melamine functionalized gold nanoparticles (MA-Au NPs) as a colorimetric sensor to detect amikacin in milk. The MA-Au NPs were synthesized using a self-assembly process and analyzed using absorption spectroscopy, transmission electron microscopy (TEM), and Fourier transform infrared (FT-IR) spectroscopy. The MA-Au NPs exhibited a distinct surface plasmon resonance (SPR) absorption peak at 520 nm and demonstrated excellent spherical dispersion. The reaction parameters were optimized, with a Au NP concentration of 2.0 × 10-7 mol L-1, MA concentration of 1.0 × 10-6 mol L-1, pH of 4.0, and reaction time of 15 minutes. In the optimization experiment, the effects of unmodified Au NPs and MA-Au NPs as colorimetric sensors for amikacin determination were compared. As a specific amount of amikacin was added to the Au NP solution, the reaction solution showed a visible change from wine red to purple and then to blue gray; a red-shift in the absorption spectrum of the solutions was observed, which could also be analyzed using the A640/A520 value, and the color changes were recorded using smartphones for visual detection through RGB (red-green-blue) data image analysis, which made the detection easy and fast. As a result, two approaches were devised using visible absorption spectra and smartphones. A linear correlation was established between the A640/A520 value and the concentration of amikacin in the range of 4.0 to 16.0 × 10-8 mol L-1. The minimal limit of detection (LOD) for absorption spectrum analysis was 3.75 × 10-9 mol L-1, whereas for smartphone analysis, it was 6.0 × 10-8 mol L-1. The recoveries ranged from 103.09% to 104.51%, while the relative standard deviations (RSDs) ranged from 3.76% to 4.25%. The proposed method was used to detect actual milk samples. The results showed that the method is simple, selective, and practical.

Development of fluorescent GO-AgNPs-Eu3+ nanoparticles based paper visual sensor for foodborne spores detection

Foodborne spores are ubiquitous with extremely strong resistance, and pose a serious threat to food safety and human health. Therefore, rapid, sensitive, and selective detection of spores are crucial. In this study, a fluorescent probe was developed based on lanthanide ion (Eu3+)-labeled nano-silver-modified graphene oxide (GO-AgNPs-Eu3+) for the detection of 2,6-dipicolinic acid (DPA), a biomarker unique to spores, to allow quantitative spores detection. The GO-AgNPs-Eu3+ nano-fluorescent probe was loaded onto a polyvinylidene fluoride microfiltration membrane, and a smartphone-assisted portable GO-AgNPs-Eu3+ nanoparticles-based paper visual sensor was designed for rapid on-site quantitative and real-time online detection of spores. The results indicated that the developed probe achieved equilibrium binding with DPA within 5 min, and enhanced fluorescence emission through antenna effect. The fluorescence detection presented a good linear relationship in the DPA concentration range of 0–45 μM, with a DPA detection limit of 4.62 nM and spore detection limit of 104 cfu/mL. The developed sensor showed a change in fluorescence from blue to red with increasing DPA concentration, and this color change was quantitatively detected through smartphone RGB variations, with a detection limit of 13.1 μM for DPA and 6.3 cfu/mL for Bacillus subtilis spores. Subsequently, the sensitivity and selectivity of the developed sensor were verified using actual milk and water samples spiked with B. subtilis spores. The results of this study provided objective technological support for rapid detection of spores, which is important for reducing the occurrence of foodborne diseases and improving food safety.

Updating test-day milk yield factors for use in genetic evaluations and dairy production systems: a comprehensive review.

Various methods have been proposed to estimate daily yield from partial yields, primarily to deal with unequal milking intervals. This paper offers an exhaustive review of daily milk yields, the foundation of lactation records. Seminal advancements in the late 20th century concentrated on two main adjustment metrics: additive additive correction factors (ACF) and multiplicative correction factors (MCF). An ACF model provides additive adjustments to two times AM or PM milk yield, which then becomes the estimated daily yields, whereas an MCF is a ratio of daily yield to the yield from a single milking. Recent studies highlight the potential of alternative approaches, such as exponential regression and other nonlinear models. Biologically, milk secretion rates are not linear throughout the entire milking interval, influenced by the internal mammary gland pressure. Consequently, nonlinear models are appealing for estimating daily milk yields as well. MCFs and ACFs are typically determined for discrete milking interval classes. Nonetheless, large discrete intervals can introduce systematic biases. A universal solution for deriving continuous correction factors has been proposed, ensuring reduced bias and enhanced daily milk yield estimation accuracy. When leveraging test-day milk yields for genetic evaluations in dairy cattle, two predominant statistical models are employed: lactation and test-day yield models. A lactation model capitalizes on the high heritability of total lactation yields, aligning closely with dairy producers' needs because the total amount of milk production in a lactation directly determines farm revenue. However, a lactation yield model without harnessing all test-day records may ignore vital data about the shapes of lactation curves needed for informed breeding decisions. In contrast, a test-day model emphasizes individual test-day data, accommodating various intervals and recording plans and allowing the estimation of environmental effects on specific test days. In the United States, the patenting of test-day models in 1993 used to restrict the use of test-day models to regional and unofficial evaluations by the patent holders. Estimated test-day milk yields have been used as if they were accurate depictions of actual milk yields, neglecting possible estimation errors. Its potential consequences on subsequent genetic evaluations have not been sufficiently addressed. Moving forward, there are still numerous questions and challenges in this domain.

Enhancing Sustainable Dairy Industry Growth through Cold-Supply-Chain-Integrated Production Forecasting

Cold supply chains (CSCs) are critical for preserving the quality and safety of perishable products like milk, which plays a vital role in the daily lives of a vast population, especially in countries like India. This research centers on sustainable milk production in Northern India, with priorities of ensuring efficiency and waste reduction within the cold supply chain. Leveraging data from a prominent North India-based dairy company, Company ‘X’, an ARIMA model is applied for predicting monthly milk production trends. Utilizing the Statistical Package for the Social Sciences (IBM SPSS STATISTICS 20) software, the study forecasts Company ‘X’s monthly milk production and identifies four distinct ARIMA models based on the autocorrelation function (ACF) and the partial autocorrelation function (PACF). By comparing predicted and actual milk production values (April–October 2021), sustainability metrics are integrated into ARIMA forecasts. Implications for the dairy sector’s sustainability and alignment with the Sustainable Development Goals (SDGs) are assessed through error terms such as R squared (R2) and mean absolute percentage error (MAPE). The study promotes sustainable milk production practices in Northern India’s dairy sector, resonating with the SDGs to optimize demand–supply dynamics and foster a more environmentally conscious dairy industry.

PSVII-27 Effect of Pre-And Postpartum Supplementation of 25-Hydroxyvitamin D 3 on Lactational Performance of Holstein Cows

Abstract Vitamin D supports several physiological functions, from mineral homeostasis to immune activity. The aim of this study was to provide 25-hydroxyvitamin D3 [25(OH)D3] to late gestation and early lactation dairy cows and evaluate the impact on lactational performance. Holstein cows (n = 100) that finished their first or greater lactation were enrolled in a randomized block design with a 2x2 factorial arrangement of treatments (n = 25 cows per treatment group). Prepartum treatments were 0 or 3 mg of 25(OH)D3 per cow daily from 28 d before expected calving until calving. Postpartum treatments were 0 or 1.5 mg of 25(OH)D3 per cow daily from calving until 63 d after calving. Treatments were top-dressed at feed delivery using a cornmeal carrier. The 25(OH)D3 source was Hy· D100. Prepartum [30 IU/kg body weight (BW)] and lactation (40 IU/kg BW) rations also provided a basal amount of cholecalciferol fed to NASEM 2021 recommendations. Dry cows were fed individually, and group housed in a bedded pack. Lactating cows were fed individually, group housed in a freestall, milked 3x/d, and milk sampled 6x/wk. Data were analyzed by ANOVA with repeated measures using the MIXED procedure of SAS (v. 9.4). The model contained fixed effects [prepartum treatment (PRE), postpartum treatment (POST; removed for prepartum data) week, and their interactions] and a random effect (block). Prepartum dry matter intake (DMI) averaged 16.3 kg/d and 2.04% of BW, was not affected by prepartum treatment (P ≥ 0.89) and was decreased closer to calving (P ≤ 0.01). As expected, week after calving affected (P ≤ 0.05) lactational performance. Postpartum DMI was greater for cows fed 3-1.5 mg than those fed 0 to 1.5 mg (Table 1). Colostrum yield and quality were not affected by prepartum treatment (P ≥ 0.91) and averaged 5.7 kg with an IgG content of 75.6 g/L. Actual milk yield was not affected by prepartum or postpartum treatments. Interestingly, there was a carryover effect of prepartum treatment on yield of 4% fat-corrected milk (FCM) and energy-corrected milk (ECM). Cows fed 3 mg during late gestation produced more than those fed 0 mg. Postpartum treatment did not affect component-corrected milk yield. Providing additional vitamin D in the form of 25(OH)D3 to late gestation cows improved lactational performance by increasing intake and the yield of component-corrected milk.

A novel electrochemical sensor based on dual-functional MMIP-CuMOFs for both target recognition and signal reporting and its application for sensing bisphenol A in milk

In this work, novel magnetic molecularly imprinted CuMOFs (MMIP-CuMOFs) were synthesized and applied to construct an electrochemical bisphenol A sensor. The constructed sensor used an electrode modified with reduced graphene oxide (RGO/GCE) as the sensing platform to improve its stability and sensitivity. The Fe3O4 nanoparticles in magnetic MOFs simplified the preparation process. Moreover, the combination of CuMOFs and molecular imprinting methodology was beneficial for improving the detection specificity, and the electroactive copper hexacyanoferrate generated by the reaction of Cu2+ in CuMOFs with potassium ferricyanide was used as the signal probe. The sensor showed a good linear relationship in the range of 0.5 to 500 nmol/L, with a low detection limit of 0.18 nmol/L. In addition, the sensor had good selectivity, repeatability (RSD = 2.59 %), and a good recovery rate for actual milk sample detection (99.8–102.49 %). This technique holds great promise for the detection of detrimental substances in food.

Effect of acetic acid addition to rice straw pre-treated with urea on performance of dairy ewes.

This experiment was carried out to study the effect of acetic acid addition to rice straws that had been already treated with urea on chemical composition, digestibility, nutritive value, and productive performance of ewes. Thirty ewes with an initial body weight of 44 ± 0.41 kg were chosen 7 days after parturition and divided into 3 groups (10 of each) for 3 months. Each group was assigned randomly to receive one of the three experimental rations composed of concentrate feed mixture and untreated rice straw as a control group (G1), urea-treated rice straw (G2), and urea-acetic acid-treated rice straw (G3). Digestibility coefficients and nutritive value were determined using fifteen mature rams andblood samples were obtained at the end of the collecting period. Findings indicated that the crude protein of rice straw was increased, and crude fiber content was decreased by either urea or urea-acetic acid rations(i.e., G2 and G3). Digestibility of most nutrients was increased (P < 0.05) for animals fed either G2 or G3 rations. There were no significant differences in nutritive value astotal digestible nutrients (TDN) among tested groups; however, digestible crude protein(DCP) increased (P < 0.05) for G2 and G3 rations. Plasma total protein, AST, creatinine, and urea were increased (P < 0.05) by feeding on G2 or G3 ration; however, plasma ALT was not affected. The average daily intake ofdry matter (DM), TDN, and DCP was higher for G2 and G3 rations. Actual milk yield, fat-corrected milk(FCM), percentages of fat, and total solids and constituents yield were increased (P < 0.05) by feeding on treated rice straw rations (i.e.,G2 and G3); however, the percentages of protein, lactose, solids not fat, and ash were not affected. In the 1st month after parturition, the changes in ewes body weight were less (P < 0.05) when they fed on G2 and G3 rations than the control one(G1)). Dams' production and offspring performance were improved (P < 0.05) by feeding on G2 and G3 rations. Feed conversion as kg DMI/kg FCM, kg TDN/kg FCM, and economic efficiency was improved for G2 and G3. Inconcluded, adding acetic acid to urea-treated rice straw may improve the performance of ewes fed on it and increase their milk production and profitability. The same trend was observed with (G2) which received urea-treated rice straw ration.

Türkiye’de Herdbook Sistemine Kayıtlı Esmer, Simental ve Siyah Alaca Sığır Irkları ile Melezlerine ait Süt Verimi Özellikleri Üzerine bir Araştırma

This study was conducted to examine the milk yield traits of Holstein Friesian (HF), Brown Swiss (BS), and Simmental (SM) breeds, as well as their crossbreeds raised in enterprises registered in the herdbook system in Türkiye. With this study, the performances of cattle breeds and their crossbreeds widely raised in Türkiye were compared in terms of milk yield characteristics based on agricultural regions of Türkiye. The data used in the study included the completed lactation records of 22 331 heads of cattle for the years 2000-2014. The GLM ANOVA method was used in the statistical analysis of the effects of breed, genotype, and region on traits related to milk yield. Across the herd, the mean and standard deviation values were determined as 7551±2771 kg for lactation actual milk yield (AMY), 4.2±1.8 for total lactation number (TLN), and 382.9±9.2 days for lactation period (LP). The effects of genotypes and regions were found to be significant or very significant (p&amp;lt;0.05 or p&amp;lt;0.001) for all three studied traits, region x genotype interaction was found to be very significant for AMY and TLN (p&amp;lt;0.001), and not significant for LP (p=0.184). As a result, it was revealed that the interaction effects of genotype, region, and genotype x region should be taken into account in determining the milk yield traits of cultured breed and crossbreed cows that are widely raised in Türkiye. Accordingly, it was concluded that the interaction findings should be evaluated in determining the breed preferences by the regions.

Study of Non-Genetic Factors Affecting Dairy Cow's Milk Production and the Development of Correction Factors for Selection of FH Cattle in Indonesia

The purpose of this study is to identify the non-genetic variables that have a substantial impact on the milk output per lactation of FH dairy cows at BBPTUHPT Baturraden and to construct variables' correction factors. The National Dairy Cow and Forage Breeding Center (BBPTUHPT) of Baturraden provided the secondary data for the study, which included 1,942 unique records of the amount of milk produced per lactation by 1,015 FH dairy cows born between 2000 and 2014 (a total of 1,015 lactation records). Milk output per lactation, the number of milking days (100–600), the age at calving (575–2,993 days), the lactation phase (lactation 1-6), and the season of birth were among the studied variables. The F test was used to examine the impact of non-genetic factors on the amount of milk cows produce per lactation (ANOVA). The impact of season on milk output per lactation was examined using a student t-test. Utilizing the multivariate least squares method, correction factors were created. Age at calving, which ranges from 1750 to 2000 days, milking days, which range from 300 to 350, and the dry season serve as the primary benchmarks for constructing correction factors. The R program was used to generate and run statistical tests and graphic representation. The findings indicated that the age of calving and lactation period had a very strong correlation (r= 0.94). The number of milking days, age at calving, and season at birth all significantly affected milk output per lactation, with the variance contributing 84.16 percent to the overall variation, according to the results of multivariate analysis (P &lt; 0.01). Actual milk production had a mean (standard deviation) of 3710.55 kg, while adjusted milk production had a mean (standard deviation) of 5167.91 kg. The adjustment parameters can lower the variation in milk production each lactation by 57.92%. (43.00 percent vs 18.09 percent). Conclusion: Non-genetic variability was successfully reduced by correcting milk production data on the number of days of milking, age at calving, and season at birth.

Cucurbit[8]uril-mediated SERS plasmonic nanostructures with sub-nanometer gap for the identification and determination of estrogens.

The SERS intensity of analytes is primarily influenced by the density and distribution of hotspots, which are often difficult to manipulate or regulate. In this study, cucurbit[8]uril (CB[8]), a kind of rigid macrocyclic molecule, was introduced to achieve ~ 1-nm nanogap between gold nanoparticles to increase the density of SERS hotspots. Three kinds of estrogens (estrone (E1), bisphenol A (BPA), and hexestrol (DES)) which are molecules with weak SERS signals were targeted in the hotspots by CB[8] to further improve the sensitivity and selectivity of SERS. It was demonstrated that CB[8] can link gold nanoparticles together through carbonyl groups. In addition, the host-guest interaction of CB[8] and estrogens was proved from the nuclear magnetic resonance hydrogen and infrared spectra. In the presence of CB[8], the SERS intensities of E1, BPA, and DES were increased to 19-fold, 74-fold, and 4-fold, respectively, and the LOD is 3.75µM, 1.19µM, and 8.26µM, respectively. Furthermore, the proposed SERS method was applied to actual milk sample analysis with recoveries of E1 (85.0 ~ 112.8%), BPA (83.0 ~ 103.7%), and DES (62.6 ~ 132.0%). It is expected that the proposed signal enlarging strategy can be applied to other analytes after further development.

Effect of Adding Curcuma Longa L. Powder on the Colostrum, Milk Production and its Composition and Growth of Newborns in Awassi ewes

In this study, 18 pregnant Awassi ewes were used to study the effect of different levels of turmeric in productive performance, ewes were divided into three equal groups. The three groups were fed six weeks before birth until weaning on a basal diet with a protein content of 14.46 and energy of 2583 kcal/kg. First group fed without additive (control), while turmeric powder was added to feed intake of the second and third groups by 5 and 10 g / day / ewe respectively. The results indicated that the use of turmeric powder 5g/day /ewe led to a significant increase (p ≤ 0.05) in the colostrum yield at the first day after lambing, actual milk production, percentage of protein and solids non-fat; and the body weights of lambs in weeks (8, 10 and 12). No significant differences were observed in the components of colostrum, and the ewes body weights.

Design of NiS@Ni3S2/CdS heterostructure with intimate contact interface for sensitive photoelectrochemical detection of lincomycin

Owing to their internal electric field effect and abundant photo-induced carriers, photoactive heterostructured materials are considered a feasible approach to improve the sensitivity of a photoelectrochemical (PEC) sensor. Herein, a novel NiS@Ni3S2/CdS heterostructure composite is derived from Ni-loaded zeolitic imidazolate framework (Ni-ZIF). The PEC experiments showed the NiS@Ni3S2/CdS composite exhibits superior photocurrent response than NiS@Ni3S2 and CdS. This is attributed to the fact that the type II heterojunction of NiS@Ni3S2/CdS with a tightly connected interface reduces the transport distance of carriers and facilitates electron-hole separation. Next, using the NiS@Ni3S2/CdS modified electrode, an aptamer/glutaraldehyde/chitosan/NiS@Ni3S2/CdS/ITO PEC biosensor is developed, which exhibits excellent sensitivity for lincomycin (Lin) detection with a wide linear range (0.0001 ∼ 1.25 nM) and a low detection limit of 0.067 pM. The prepared sensor is further employed to monitor Lin in the actual milk. The results confirm that the prepared sensing electrode displays good selectivity, repeatability and stability.

Effect of mango seeds as an untraditional source of energy on the productive performance of dairy Damascus goats.

Eighteen dairy Damascus goats weighing 38-45 kg live body weight and aged 3-4 years were divided into three groups according to their body weight, with six goats in each group. Yellow corn grain in their concentrate feed mixture was replaced with mango seeds (MS) at levels of 0% MS in group 1 (G1, control), 20% MS in group 2 (G2), and 40% MS in group 3 (G3). The digestibility coefficients of the organic matter, dry matter, crude fiber, crude protein, ether extract, nitrogen-free extract, and total digestible nutrients increased (P < 0.05) upon feeding MS to G2 and G3. The amounts of dry matter, total digestible nutrients, and digestible crude protein required per 1 kg 3.5% fat-corrected milk (FCM) were lower (P < 0.05) in G2 and G3 vs. G1. Actual milk and 3.5% FCM yield increased (P < 0.05) with the increasing MS dietary level. G2 and G3 had the highest significant (P < 0.05) total solids, total protein, non-protein nitrogen, casein, ash, fat, solids not fat, lactose, and calcium contents compared with G1. Replacing yellow corn grain with MS in G2 and G3 significantly (P < 0.05) decreased the cholesterol concentration and AST activity. Feeding MS increased the concentrations of caprioc, caprylic, capric, stearic, oleic, elaidic, and linoleic acids and decreased the concentrations of butyric, laueic, tridecanoic, myristic, myristoleic, pentadecanoic, heptadecanoic, cis-10-Heptadecanoic, cis-11-eicosenoic, linolenic, arachidonic, and lignoseric acids in the milk fat. The results show that the replacement of corn grain with MS improved the digestibility, milk yield, feed conversion, and economic efficiency, with no adverse effects on the performance of Damascus goats.

Highly Efficient Sensing of Hydrogen Peroxide Based on Atomically Dispersed Iron- and Nitrogen-Doped Carbon

Electrochemical hydrogen peroxide (H2O2) sensors are valuable tools in biological research and industrial applications for in situ monitoring H2O2 levels with the advantages of simplicity, portability, rapid response, and low cost. Herein, we demonstrate a novel electrochemical sensing platform based on Fe- and N-doped C composite (Fe–N–C) modified electrodes for sensitive detection of H2O2. This platform showed an excellent response to H2O2 reduction in near-neutral pH solutions with a low reduction potential and high sensitivities. The results of site-poisoning experiments suggest that the atomically dispersed Fe–Nx sites, which resemble the peroxidase-type enzymes, contribute to the high activity of the Fe-N-C catalyst for the H2O2 reduction reaction. Further, we developed a screen-printed electrode (SPE) modified with Fe–N–C with excellent electrocatalytic performances, including a favorable sensitivity (24.95 ± 0.77 μA μM−1 cm−2) and a low detection reagent (40 μl solution). Moreover, the as-prepared Fe–N–C/SPE was successfully applied to H2O2 sensing in an actual milk sample, with good recovery (between 98% and 102%). The as-prepared Fe–N–C/SPE sensor also exhibits superior selectivity, stability, and reproducibility, making it a promising candidate as a portable platform for H2O2 analytes, further improving its practical H2O2 sensing applications.