دانشگاه محقق اردبیلی یافته‌های نوین علوم دامی 1 1 2026 03 21 Investigation of Reproductive Trends and Postpartum Problems in an Industrial Dairy Farm in Yazd, Iran بررسی روند تولید مثلی و مشکلات پس از زایش در یک واحد گاوداری صنعتی در استان یزد 1 12 4384 10.22098/naas.2025.18890.1005 FA خسرو پارسائی مهر دکترای علوم دامی، دانشکده کشاورزی، دانشگاه ارومیه، ارومیه، ایران منیره دره زرشکی پور دانشجوی دامپزشکی، دانشکده دامپزشکی، دانشگاه تهران، تهران، ایران حبیب چراغی دانشجوی دکتری علوم دامی، دانشکده کشاورزی، دانشگاه تبریز، تبریز، ایران غلامعلی مقدم استاد گروه علوم دامی، دانشکده کشاورزی، دانشگاه تبریز، تبریز، ایران. علی حسین خانی استاد گروه علوم دامی، دانشکده کشاورزی، دانشگاه تبریز، تبریز، ایران Journal Article 2025 11 23 Introduction Effective reproductive management is a cornerstone of profitability in commercial dairy farming. A key challenge is the well-documented negative correlation between milk yield and reproductive efficiency, which is often exacerbated by postpartum complications. This study aimed to conduct a systematic analysis of reproductive performance and identify critical postpartum health challenges in a large-scale industrial Holstein farm in Yazd province, Iran. The primary objectives were to evaluate the impact of specific factors calf sex and cow parity on the type of calving (normal vs. dystocia) and the incidence of postpartum disorders (uterine infection and ovarian cysts). The ultimate goal was to provide management recommendations to improve reproductive outcomes and herd profitability. Method A descriptive-analytical study was conducted using historical data from one of the largest industrial dairy farms in Yazd province. The dataset included 373 dairy cows and their calving records spanning a ten-year period (2005-2014, equivalent to Iranian years 1384-1393). Records from parity 1 to 5 were included, with each calving event treated as an independent observation. Data extracted from electronic and paper farm was recorded including calving type (normal, assisted, dystocia), calf sex, and diagnoses of postpartum disorders (uterine infection and ovarian cyst) confirmed by veterinary clinical examination. Incomplete or duplicate records were excluded. Statistical analysis was performed using SAS software (version 9.1). The Chi-Square test was employed to assess the significance of associations between categorical variables: calf sex and calving type, calf sex and postpartum problems, and parity number with both calving type and reproductive disorders. Results The analysis significant results was as follows several: Calving Type and Calf Sex: Normal parity were most frequent. However, male calf births were significantly associated with a higher incidence of dystocia and assisted parity compared to female calf births. Postpartum Disorders and Calf Sex: The majority of postpartum problems were uterine infections (87.35%), and ovarian cysts comprising 12.64%. The birth of male calves was linked to a higher occurrence of both of these disorders. Parity and Calving Type: Reproductive performance improved with higher parity. The rate of normal parity increased significantly after the third parity, while the rates of assisted calving and dystocia decreased. The lowest incidence of dystocia was observed in third to fifth parities. Parity and Postpartum Disorders: The prevalence of ovarian cysts increased up to the third parity and then declined in fourth and fifth parities. In contrast, uterine infection was most common in heifers and decreased in subsequent parities. Discussion: according to the findings, two primary determinants of reproductive difficulty are calf sex and cow parity. Male calves especially heavy one increase the risk of dystocia, which makes cows susceptible to secondary complications like uterine infections. The vulnerability of early-parity cows (especially first and second) is attributed to the simultaneous demands of growth and lactation, and the profound negative energy balance (NEB) in early lactation. This NEB impairs immune function and ovarian activity, explaining the higher rates of uterine infection and the initial rise in ovarian cysts. The subsequent improvement in health indicators after the third parity indicates better metabolic adaptation and energy balance in mature cows. Conclusions The study concludes that targeted management strategies are essential to mitigate these risks. Key recommendations include: Strategic Sire Selection for Heifers: Using sires with proven genetic value for low birth weight and easy calving, particularly for high genetic value heifers. Enhanced Care for Early-Parity Cows: Implementing specialized nutritional, metabolic, and health monitoring programs for cows in their first to third lactations to manage energy balance and support uterine health. Precision Calving Management: Providing increased supervision and timely assistance during calving for cows carrying male calves. By focusing on these factors, dairy farms can improve reproductive efficiency, reduce the calving interval, and decrease involuntary culling, thereby enhancing overall herd productivity and economic sustainability. هدف: مدیریت مؤثر تولیدمثلی در گاوداری‌های صنعتی نقش حیاتی در تداوم سودآوری این واحدها ایفا می‌کند. این پژوهش با هدف تحلیل نظام‌مند کارایی تولیدمثلی و شناسایی چالش‌های سلامت پس از زایش در یک گله‌ از گاوهای هلشتاین انجام شد. به نظر می‌رسد برنامهریزی تولیدمثلی مدون و انجام به موقع تلقیحهای منجر به آبستنی تا حد امکان از مشکلات بعد از زایش و نیز از افزایش روزهای باز جلوگیری میکند. روش پژوهش: برای انجام این تحقیق از دادههای آماری یکی از بزرگترین گاوداریهای صنعتی استان یزد استفاده شد، بدین منظور دادههای آماری 373 رأس گاو شیری در طی سالهای 1384 تا 1393 مورد بررسی قرار گرفت. آنالیز آماری دادهها با نرم افزار 9.1 SAS و مقایسه دادهها از آزمون مربع کای (Chi-Square) استفاده شد. یافته ها: نتایج این مطالعه نشان می‌دهد که در مجموع، اکثر زایشها به‌صورت طبیعی انجام گرفت و میزان سخت‌زایی کمتر از زایش طبیعی بود. با این حال، جنسیت گوسالهها نیز تأثیر قابل توجهی بر عوارض پس از زایش داشت، به‌طوری‌که تولد گوساله‌های نر منجر به افزایش مشکلات پس از آبستنی شد. همچنین، با افزایش سن و شکم زایش، روند بهتری در شاخصه‌های سلامتی مشاهده گردید. به‌طور مشخص، با بالا رفتن سن گاو، میزان زایش طبیعی افزایش و میزان عفونت رحمی کاهش یافت. در مورد کیست تخمدانی نیز روند خاصی ملاحظه گردید، به‌طوری که تا شکم سوم زایش، میزان ابتلا به این عارضه افزایش یافته، اما از شکم سوم به بعد، از تعداد گاوهای مبتلا به کیست تخمدانی کاسته شد. نتیجه گیری کلی: نتایج نشان داد که جنسیت گوساله و شکم زایش از عوامل تعیین‌کننده در بروز مشکلات تولیدمثلی و پس از زایش هستند. بر این اساس مدیریت هدفمند این عوامل، از طریق انتخاب گاوهای نر مناسب برای تلیسه‌ها و مراقبت‌های ویژه از گاوهای شکم اول تا سوم، می‌تواند به بهبود کارایی تولیدمثل و به تبع آن گوساله‌زایی به موقع کمک شایانی کند.

https://naias.uma.ac.ir/article_4384_9923fd87322cf6ac6e6cb081023346e9.pdf

دانشگاه محقق اردبیلی یافته‌های نوین علوم دامی 1 1 2026 03 21 The Effect of Sesame Hull Feeding on Performance Characteristics, Blood Parameters, and Nutrient Digestibility of Moghani Male Lambs تأثیر تغذیه پوسته کنجد بر صفات عملکردی، فراسنجه‌های خونی و قابلیت هضم مواد مغذی در بره‌های نر مغانی 1 16 4269 10.22098/naas.2025.4269 FA فرزاد میرزائی آقجه قشلاق استادگروه علوم دامی دانشکده کشاورزی و منابع طبیعی دانشگاه محقق اردبیلی، اردبیل ، ایران انصار حیدرزاده فارغ التحصیل کارشناسی ارشد گروه آموزشی علوم دامی، دانشکده کشاورزی و منابع طبیعی دانشگاه محقق اردبیلی، اردبیل ، ایران جمال سیف دواتی استاد گروه علوم دامی دانشکده کشاورزی و منابع طبیعی دانشگاه محقق اردبیلی، اردبیل ، ایران بهمن نویدشاد استاد گروه علوم دامی دانشکده کشاورزی و منابع طبیعی دانشگاه محقق اردبیلی، اردبیل ، ایران مهدی جمالی دانشجوی دکتری گروه آموزشی علوم دامی، دانشکده کشاورزی و منابع طبیعی ، دانشگاه محقق اردبیلی، اردبیل Journal Article 2025 09 02 Introduction Population growth and competition with humans for grain have increased the price of animal feed, leading to a search for cheaper feed ingredients for animal diets. Additionally, the primary objective of animal husbandry is to achieve high production with a low cost to maximize net income; however, rising feed prices have impacted the economic situation of livestock breeders. Since the share of animal protein in the human protein supply should be at least 25%, it is necessary to increase milk and meat production by 30% over the next two decades. Therefore, it is necessary to devise measures that utilize waste and materials that cannot be used in human nutrition due to their high lignocellulosic content in animal nutrition. the plants by-products, such as its hull and meal, can be used in animal feed. Sesame hulls are left as waste and residue from oil mills and related industries, posing problems for livestock farmers, regional residents, and the environment. However, they can be used as a substitute for barley and other dietary components in animal nutrition. In addition, sesame hulls have high antioxidant and fiber content, and they can also meet parts of animal needs. However, studies conducted in this regard are few. Method 24 male Moghani lambs with an average weight of 30±2 were used in four treatments and 6 replications in a completely randomized design. The experimental treatments included: (1) control, (2) treatment receiving 10% sesame hull, (3) treatment receiving 20% sesame hull, and (4) treatment receiving 30% sesame hull. Feed intake, weight gain, and several blood parameters, including glucose, cholesterol, triglycerides, and total protein, were measured. After slaughter, cold and warm carcass weights were also calculated. The data obtained were analyzed using SAS software. Results The results of the effect of sesame husk consumption on dry matter intake and daily weight gain, period weight gain, and feed conversion ratio (days 45 and 80 of the rearing period) in Moghani fattening lambs are shown in Table 3. According to these results, although the third treatment (receiving a diet containing 20% sesame husk) numerically showed the highest dry matter intake, in general, no significant effect of the experimental treatments on dry matter intake was observed across the first, second, and entire rearing periods. The experimental treatments also had no significant effect on the feed conversion ratio. In the present study, different levels of sesame husk significantly changed the apparent digestibility of dry matter in Moghani fattening lambs. The results of the present study showed that the treatments in the first period had a significant effect on glucose levels. In contrast, they had no significant effect on cholesterol, triglycerides, or protein. The results of the experimental treatments on the weight of hot and cold carcasses in Moghani fattening lambs showed that the treatments had no significant effect on them. However, numerically, the highest weight of hot and cold carcasses was observed in the group receiving the control diet. In addition, except for leg weight, the experimental treatments had no significant effect on the weight of the carcass parts. The highest leg weight was observed in the treatment receiving 20% sesame husks, and the lowest in the control treatment and the treatment receiving 30% sesame husks. The results of the effect of sesame husk consumption on the cost of feed in fattening lambs demonstrated that the lowest price of feed per kilogram of live weight gain, according to the feed conversion ratio of the animal, was observed in the treatment receiving 10% sesame husks. however, feed costs were 18.13% and 11.63% higher in the treatment receiving 20% and 30% sesame husks than the control group, respectively. The results showed that the treatment receiving 30% sesame husks had more feed cost. Conclusions In general, the results of the present study showed that the use of sesame hulls in fattening lambs' feed is acceptable without adversely affecting performance or digestibility. It was also demonstrated that sesame hull can be used as a substitute for barley at levels of 20% and 30%. In this way, in addition to being included in the livestock diet as a food source, it also prevents environmental pollution. هدف: این تحقیق به‌منظور بررسی اثر مصرف پوسته کنجد در جیره بر عملکرد، مصرف خوراک، قابلیت هضم، برخی فراسنجههای خونی، صفات لاشه برههای نر مغانی و هزینه خوراک انجام شد. روش پژوهش: بدین منظور، از تعداد 24 رأس بره نر مغانی با متوسط وزن 2±30 کیلوگرم، در چهار تیمار و 6 تکرار در قالب طرح کاملاً تصادفی استفاده شد. تیمارهای آزمایش شامل: (1) تیمار شاهد، (2) تیمار دریافت‌کننده 10 درصد پوسته کنجد، (3) تیمار دریافت‌کننده 20 درصد پوسته کنجد و (4) تیمار دریافت‌کننده 30 درصد پوسته کنجد بودند. خوراک مصرفی، افزایش وزن و برخی پارامترهای خونی شامل گلوکز، کلسترول، تریگلیسیرید و پروتئین کل اندازهگیری و بررسی شد. پس از کشتار وزن لاشه سرد و گرم نیز محاسبه شد. دادههای به وسیله نرم‌افزار SAS مورد آنالیز قرار گرفتند. یافته ها: نتایج حاصل نشان داد که در دوره اول بیشترین افزایش وزن مربوط تیمار دریافت کننده 10 درصد پوسته کنجد (57/8 کیلوگرم) و کمترین مربوط به تیمار دریافت کننده 30 درصد پوسته کنجد (2/4 کیلوگرم) بود. کمترین غلظت گلوکز در تیمار دوم (240/72 میلیگرم بر دسی لیتر) و بیشترین غلظت در تیمارهای سوم (150/86 میلیگرم بر دسی لیتر) و چهارم (965/83 میلیگرم بر دسی لیتر) مشاهده شدند. از طرفی کمترین هزینه خوراک به ازای هر کیلوگرم افزایش وزن زنده در تیمار دریافت کننده 10 درصد پوسته کنجد (65/83 درصد نسبت به شاهد) مشاهده شد. نتیجه گیری کلی: به‌طورکلی، نتایج نشان داد پوسته کنجد تا 30 درصد جیره میتواند جایگزین مناسبی برای جو بدون بروز اثرات سوء بر قابلیت هضم، افزایش وزن، ضریب تبدیل و عملکرد پروار باشد.

https://naias.uma.ac.ir/article_4269_119069adcd0bfbe5264588c5887c067d.pdf

دانشگاه محقق اردبیلی یافته‌های نوین علوم دامی 1 1 2026 03 21 Repeatability of Production Traits of Sepahan Native Chickens in Diets Including Camelina and Soybean Oil تکرارپذیری صفات تولیدی مرغان بومی سپاهان تحت جیره‌های حاوی روغن کاملینا و سویا 1 12 4385 10.22098/naas.2026.19106.1011 FA محمد حیدری استادیار بخش تحقیقات علوم دامی، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی کرمانشاه، سازمان تحقیقات، آموزش و ترویج کشاورزی، کرمانشاه سجاد بادبرین استادیار بخش تحقیقات علوم دامی، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی کرمانشاه، سازمان تحقیقات، آموزش و ترویج کشاورزی، کرمانشاه، Journal Article 2025 12 21 Introduction Native chickens are valuable genetic resources in Iran, having evolved through natural selection and adaptation to local environmental conditions. They represent a national asset and contribute to rural livelihoods and food security. The growing global population, economic development, increased life expectancy, and adoption of dietary habits from developed countries have led to higher demand for animal-based protein. Iranian native breeds, such as the Sepahan chicken, are genetically diverse and adaptable to local climates. moderate disease resistance, and acceptable product quality, making them valuable for breeding and research programs. Previous studies on Sepahan hens in rural conditions showed that these birds produce an average of approximately 155 eggs per year, with a mean weight of 53 g and a hen-day production rate of around 44%. Their performance is highly influenced by environmental and management factors, with warmer climates reducing the onset of lay and colder climates increasing egg weight. However, the overall production and feed efficiency remain lower than commercial lines. Improving these traits through nutritional management and selective breeding is a priority in semi-intensive and rural production systems. Recent research highlights the potential of omega-3-rich oils, such as Camelina oil, and phytogenic additives, including cinnamon and lemon balm essential oils, to enhance poultry health and product quality. although several studies have examined the effects of dietary energy, protein, amino acids, and mineral levels on native chicken performance, there is limited information on the variance components and repeatability of production traits under such nutritional interventions. Estimating repeatability at the experimental unit level, even without pedigree data, allows assessment of performance stability and aids the design of management and selection strategies. Therefore, the objective of this study was to evaluate the effect of dietary oil (soybean vs. Camelina) on egg production, egg mass, and feed conversion ratio (FCR) in Sepahan native hens, and to estimate variance components and repeatability for these traits at the pen level. The findings provide insights into production performance and the potential for nutritional and genetic improvement in this native breed. Method The study involved 864 Sepahan hens aged 54–62 weeks, housed in floor pens with a temperature of approximately 20°C, a 16-hour light/8-hour dark photoperiod, and a stocking density of 500 cm² per bird. Beforeto the experimental period, hens were adapted to the experimental conditions for two weeks. A completely randomized design with two dietary treatments (soybean oil and Camelina oil) was employed. Each treatment included six replicates, with eight hens per pen, for a total of 12 experimental units (pens). Diets were formulated using WUFFDA software to meet the nutritional requirements of native hens, differed only in oil source. Feed was provided as mash, and water and feed were offered ad libitum throughout the eight-weeks study. Daily records of egg production and egg weight were collected at the pen level. Weekly calculations included hen-day egg production (%), average egg weight, egg mass (g/hen/day), and FCR (feed intake per unit egg mass). Variance components and repeatability were estimated using a mixed-effects model with pen as a random effect and dietary oil as a fixed effect, modeling weekly records as repeated measures. Between-pen (σ²ᵤ) and within-pen (σ²ₑ) variance components were estimated using restricted maximum likelihood (REML) in SAS 9.1, and repeatability (R) was calculated as σ²ᵤ / (σ²ᵤ + σ²ₑ). Duncan's multiple range tests at P < 0.05 were used to compare mean differences between treatments. Results The effects of dietary oil on egg production, egg mass, egg weight, feed intake, and feed conversion ratio (FCR) in Sepahan native hens are different. Mean egg weight in the soybean oil group was 52.1 ± 1.9 g, while the Camelina oil group exhibited a slightly higher mean of 53.2 ± 2.0 g. Feed intake averaged 251 ± 13 g/hen/day in the soybean group and 256 ± 16 g/hen/day in the Camelina group. Statistical analysis indicated that these differences were not significant (P>0.05), suggesting that replacing soybean oil with Camelina oil did not influence either egg weight or feed consumption. in contrast, dietary oil source significantly affected egg production, egg mass, and FCR. Hens fed Camelina oil produced 39.2% of hen-day eggs compared to 35.8% in the soybean group, representing a significant improvement (P<0.05). Egg mass also increased significantly from 15.9 g/hen/day in the soybean group to 17.7 g/hen/day in the Camelina group (P<0.05). This improvement in production efficiency was accompanied by a reduction in FCR, which decreased from 3.22 to 2.98 kg feed per kilogram of egg mass (P<0.05), indicating enhanced feed utilization. Variance component analysis revealed that approximately 38% of the observed variation in egg production and egg mass was attributable to consistent differences between experimental units (pens), with the remainder due to within-pen weekly fluctuations and random effects. In contrast, FCR exhibited greater within-pen variability, resulting in a lower repeatability of 0.30. These results suggest that while egg production and egg mass are relatively stable traits over time, FCR is more sensitive to short-term environmental and management changes. Overall, these findings demonstrate that dietary supplementation with Camelina oil enhances production performance and feed efficiency in Sepahan native hens. The improvement occurs without affecting feed intake or egg weight, highlighting the potential of Camelina oil as a nutritionally and economically valuable dietary modification in native poultry production systems. Conclusions Camelina oil improved egg production and egg mass and enhanced feed efficiency, consistent with studies on omega-3-enriched diets in laying hens. While production levels in Sepahan hens were lower than those of commercial lines, the relative response demonstrates nutritional potential. The range of production traits (egg production: 28–46%, egg mass: 11.5–21 g/day, FCR: 2.60–3.80 kg/kg) aligns with reports from other native chicken populations and indicates variability among pens. Moderate repeatability of egg production and egg mass supports the use of repeated pen-level measurements for identifying superior units for management or selection. Lower repeatability of FCR highlights its susceptibility to environmental and management factors and suggests the need for more extended observation periods or additional replicates to assess feed efficiency accurately. Dietary inclusion of Camelina oil enhanced egg production, egg mass, and feed efficiency in Sepahan native hens. Moderate repeatability of production traits indicates reliable performance assessment at the pen level. Nutritional strategies such as replacing soybean oil with Camelina oil can improve production in native chickens, contributing to higher economic returns in rural poultry systems. Future studies should estimate genetic parameters using pedigree-based models and investigate egg quality traits and metabolic indicators in conjunction with production traits to optimize breeding strategies. هدف: پژوهش حاضر با هدف برآورد تکرارپذیری صفات تولیدی مرغان بومی نژاد سپاهان و ارزیابی اثر دو منبع روغن خوراک (سویا و کاملینا) بر عملکرد تخم‌گذاری (درصد تولید، توده تخم‌مرغ و ضریب تبدیل خوراک) انجام شد. روش پژوهش: برای این منظور، ۸۶۴ قطعه مرغ تخم‌گذار سپاهان در سن ۵۴ تا ۶۲ هفتگی در قالب طرح کاملاً تصادفی با دو تیمار روغن (سویا و کاملینا)، ۶ تکرار و ۸ قطعه مرغ در هر واحد آزمایشی، به‌مدت ۸ هفته مورد بررسی قرار گرفتند. درصد تولید تخم‌مرغ، توده تخم‌مرغ (گرم/مرغ/روز) و ضریب تبدیل خوراک (کیلوگرم خوراک/کیلوگرم توده تخم) به‌صورت هفتگی در سطح واحد آزمایشی ثبت شد و برای برآورد اجزای واریانس و تکرارپذیری، از مدل اثرات مختلط با در نظر گرفتن نوع روغن به‌عنوان اثر ثابت، واحد آزمایشی به‌عنوان اثر تصادفی و رکوردهای هفتگی به‌عنوان تکرار زمانی، و روش حداکثر درست‌نمایی محدود شده (REML) در نرم‌افزار SAS ورژه 1/9 استفاده گردید. یافته‌ها: استفاده از روغن کاملینا در مقایسه با روغن سویا موجب افزایش معنی‌دار درصد تولید تخم‌مرغ (۲/32 در برابر 8/35 درصد)،توده تخم‌مرغ (9/15 در برابر 9/17 گرم/مرغ/روز) و بهبود ضریب تبدیل خوراک (22/3 در برابر 98/2 کیلوگرم خوراک/کیلوگرم توده تخم) شد (P<0.05). میانگین کلی طی دوره ۸ هفته‌ای برابر با 5/37 درصد تولید تخم‌مرغ، 8/16 گرم توده تخم‌مرغ و10/3 کیلوگرم خوراک/کیلوگرم توده تخم بود و تکرارپذیری برای درصد تولید تخم‌مرغ و توده تخم‌مرغ هر یک 38/0 و برای ضریب تبدیل خوراک 30/0 برآورد شد که نشان‌دهنده سهم قابل توجه تفاوت‌های پایدار بین واحدهای آزمایشی در تغییرات این صفات بود. نتیجه‌گیری: نتایج این پژوهش نشان داد که استفاده از روغن کاملینا می‌تواند به‌عنوان یک راهکار تغذیه‌ای مؤثر برای بهبود پایدار عملکرد تخم‌گذاری و کارایی مصرف خوراک در مرغان بومی نژاد سپاهان مورد استفاده قرار گیرد.

https://naias.uma.ac.ir/article_4385_a18c70d16514c5d5a9047914c5710e71.pdf

دانشگاه محقق اردبیلی یافته‌های نوین علوم دامی 1 1 2026 03 21 Effect of Phenological Stage on Chemical Composition, Digestibility, and Fermentation Characteristics of Chenopodium album L. under Laboratory Conditions تأثیر مرحله فنولوژیکی بر ترکیب شیمیایی، قابلیت هضم و ویژگی‌های تخمیری گیاه سلمه‌تره (Chenopodium Album L.) در شرایط آزمایشگاهی 1 16 4465 10.22098/naas.2025.18600.1004 FA ندا حسینی گروه علوم دامی، دانشکده کشاورزی و منابع طبیعی دانشگاه آزاد اسلامی واحد بندرگز، بندرگز، ایران اسماعیل گنجی جامه شوران گروه علوم دامی، دانشکده کشاورزی و منابع طبیعی، دانشگاه آزاد اسلامی واحد آزادشهر، آزادشهر، ایران جواد بیات کوهسار گروه علوم دامی، دانشکده کشاورزی و منابع طبیعی دانشگاه گنبد کاووس، گنبدکاووس، ایران Journal Article 2025 10 16 Introduction Rangelands are among the most fundamental resources for livestock feed in animal production systems and play a crucial role in sustaining livestock production, reducing feeding costs, and conserving natural resources. The quality and quantity of rangeland forages directly affect feed intake, digestibility, nutrient balance, and ultimately the productive performance of ruminant animals. Rangeland plants exhibit considerable variation in chemical composition, cellular structure, and ruminal fermentability, which are influenced by plant species, climatic conditions, rangeland management practices, and, in particular, phenological stage. As plants mature, substantial changes occur in their chemical composition, characterized by increases in cell wall components and lignin content, and reductions in soluble constituents such as crude protein and fermentable carbohydrates. These changes are generally associated with decreased digestibility, metabolizable energy content, and microbial protein synthesis efficiency. Therefore, determining the optimal harvesting or grazing time is essential to maximize the nutritional value of rangeland forages. Common lambsquarters (Chenopodium album L.) is an annual plant widely distributed in rangelands and agricultural fields of northern Iran. Due to its rapid growth, high biomass production, and relatively good tolerance to environmental stresses, this species is naturally abundant in many regions. In addition to its traditional use as human food in some regions, common lambsquarters contains substantial amounts of crude protein, minerals, and bioactive compounds, indicating its potential as a forage resource for ruminants. However, information on changes in nutritional value, digestibility, and ruminal fermentation characteristics of this plant across growth stages is limited, and most previous studies have focused primarily on its chemical composition. Therefore, a comprehensive evaluation integrating chemical composition, digestibility, fermentation characteristics, and gas production is required to understand the feeding value of this plant better. Furthermore, comparison of common lambsquarters with conventional feedstuffs such as alfalfa hay and wheat straw can provide practical insights into its potential use in ruminant diets. Accordingly, the objective of this study was to investigate the effects of phenological stage on chemical composition, digestibility, and in vitro gas production parameters of common lambsquarters and to compare its nutritional value with alfalfa hay and wheat straw under laboratory conditions. Method This study was conducted in the spring of 2023 at the Animal Nutrition Laboratory, Faculty of Agriculture, Gonbad Kavous University. Samples of common lambsquarters were collected at three phenological stages, including vegetative, flowering, and seed-setting stages, from farms located in Bandar Gaz County, Golestan Province, Iran. After transport to the laboratory, the samples were initially wilted in the open air and subsequently oven-dried with alfalfa hay (second cut, harvested at the early-flowering stage) and wheat straw. All samples were then ground using a suitable mill and sieve to obtain homogeneous material for laboratory analyses. The experimental treatments consisted of five feeds: wheat straw, common Lamb’s quarters at the vegetative stage, common Lamb’s quarters at the flowering stage, common Lamb’s quarters at the seed-setting stage, and alfalfa hay. Chemical composition analyses, including dry matter, crude protein, and ash, were performed according to standard procedures. Neutral detergent fiber (NDF) and acid detergent fiber (ADF) contents were determined using the Van Soest method. Net energy values, total digestible nutrients, and metabolizable energy were calculated using reference equations. To evaluate fermentation characteristics, in vitro gas production was measured using a pressure transducer system. Rumen fluid was collected from rumen-fistulated male sheep, filtered, and mixed with artificial saliva. Gas volume was recorded at incubation times of 2 to 96 hours, and gas production parameters, including potential gas production and gas production rate, were estimated using a nonlinear model. Dry matter digestibility and organic matter digestibility were determined using the closed culture technique. Microbial indices, including the partitioning factor, microbial biomass, and the efficiency of microbial biomass production, were calculated. Statistical analysis was performed using the GLM procedure, and mean comparisons were conducted using Duncan’s multiple range test at a significance level of 5%. Results The results indicated that phenological stage significantly affected the chemical composition and nutritional value of common lambsquarters. The highest contents of crude protein, ash, total digestible nutrients, and metabolizable energy were observed in the vegetative stage. As plant maturity advanced toward flowering and seed-setting stages, crude protein content decreased, while NDF and ADF concentrations increased, reflecting the accumulation of structural components in the plant cell wall. Compared with wheat straw, common lambsquarters exhibited higher nutritional value at all growth stages, and at the vegetative stage, it even surpassed alfalfa hay in some nutritional parameters. In vitro gas production results showed that alfalfa hay had the highest potential gas production, whereas common lambsquarters at the seed-setting stage produced the lowest amount of gas. However, the rate of gas production was higher in common lambsquarters at the vegetative stage, indicating more rapid fermentation of soluble components. Dry matter and organic matter digestibility were highest in alfalfa hay and lowest in wheat straw. In common lambsquarters, although digestibility generally declined with advancing maturity, a relative improvement in some digestibility indices and microbial parameters was observed at the seed-setting stage due to the presence of seeds and softer plant tissues. Increased microbial biomass and partitioning factor at this stage suggested more efficient utilization of fermentable organic matter by rumen microorganisms. Conclusions Overall, the findings showed that the nutritional quality of Chenopodium album declines with advancing phenological stage. Crude protein, metabolizable energy, digestible organic matter, and volatile fatty acids decrease during plant maturation, while NDF, ADF, and lignin contents increase. The vegetative stage exhibited the highest nutritional quality, as assessed by chemical composition, digestibility, and gas production. Therefore, harvesting Chenopodium album at the vegetative stage can provide higher nutritional value for ruminants and may serve as a suitable supplementary forage source in their diets. مقدمه و هدف: گیاه سلمه‌تره (Chenopodium album L.) یکی از علف‌های هرز مرتعی رایج در شمال کشور است که به‌دلیل تولید بالا و قابلیت دسترسی آسان، می‌تواند به‌عنوان منبع بالقوه علوفه‌ای مورد استفاده قرار گیرد. این پژوهش با هدف بررسی تغییرات ترکیب شیمیایی، گوارش پذیری و فراسنجههای تولید گاز سلمهتره در مراحل مختلف فنولوژیکی و مقایسه آن با یونجه خشک و کاه گندم در شرایط آزمایشگاهی انجام شد. مواد و روش‌ها: نمونه‌برداری از گیاه سلمه‌تره از اطراف مزارع شهرستان بندرگز (استان گلستان) انجام شد. نمونه‌ها پس از خشک شدن در هوای آزاد و آسیاب‌شدن با مش ۲ میلی‌متری، جهت آنالیز شیمیایی و آزمون تولید گاز مورد استفاده قرار گرفتند. تیمارهای آزمایشی شامل: (۱) کاه گندم، ۲) سلمه‌تره در مرحله رویشی، ۳) سلمه‌تره در مرحله گل‌دهی، ۴) سلمه‌تره در مرحله بذردهی و ۵) یونجه خشک بودند. داده‌ها در قالب طرح کاملاً تصادفی با سه تکرار تجزیه و تحلیل شدند. نتایج: نتایج نشان داد بین تیمارهای آزمایشی از نظر ترکیب شیمیایی، قابلیت هضم و پارامترهای تولید گاز اختلاف معنیداری وجود داشت (05/0P<) بالاترین میزان پروتئین خام (98/26 درصد)، خاکستر (12/24 درصد)، کل مواد مغذی قابل هضم (84/69 درصد) و انرژی خالص مربوط به سلمه‌تره در مرحله رویشی بود. با افزایش سن گیاه، مقادیر پروتئین کاهش و میزان الیاف نامحلول در شوینده اسیدی (ADF) و الیاف نامحلول در شوینده خنثی (NDF) افزایش یافت، بهطوری که ADF از 5/21 درصد در مرحله رویشی به 2/34 درصد در مرحله بذردهی و NDF از 3/28 درصد به 1/46 درصد افزایش یافت. بیشترین پتانسیل تولید گاز مربوط به یونجه (۲۳۶ میلی‌لیتر) و کمترین مقدار آن به سلمهتره در مرحله بذردهی (6/210 میلی‌لیتر) تعلق داشت. همچنین، قابلیت هضم ماده خشک و ماده آلی در یونجه بیشترین و در کاه گندم کمترین مقدار را نشان دادند. نتیجه‌گیری: به‌طور کلی نتایج این پژوهش نشان داد که با پیشرفت مرحله فنولوژیکی، کیفیت تغذیه‌ای سلمه‌ تره کاهش می‌یابد. مقادیر پروتئین خام، انرژی قابل متابولیسم، ماده آلی قابل هضم و اسیدهای چرب فرار در مراحل پیشرفته‌تر رشد کاهش یافته و هم‌زمان مقادیر NDF،ADF و لیگنین افزایش پیدا کردند. بر اساس یافته‌ها، مرحله رویشی بهترین کیفیت تغذیه‌ای را از نظر ترکیب شیمیایی، قابلیت هضم و تولید گاز نشان داد. بنابراین، برداشت سلمه‌تره در مرحله رویشی می‌تواند ارزش غذایی بالاتری برای نشخوارکنندگان فراهم کند و به‌عنوان منبع علوفه‌ای مکمل در جیره آن‌ها مورد استفاده قرار گیرد.

https://naias.uma.ac.ir/article_4465_7e6d3c7a64f02695ed359afa9c97e5aa.pdf

دانشگاه محقق اردبیلی یافته‌های نوین علوم دامی 1 1 2026 03 21 Deep Learning in Intelligent Livestock Management: A Comprehensive Review of the Role of Convolutional Neural Networks یادگیری عمیق در مدیریت دامداری هوشمند: بررسی جامع نقش شبکه‌های عصبی کانولوشن 1 14 4473 10.22098/naas.2026.18530.1006 FA امجد سلیمی دانشجوی دکتری فیزیولوژی دام، گروه علوم دامی، دانشکده کشاورزی، دانشگاه کردستان، سنندج، ایران Journal Article 2025 11 25 Introduction The Paradigm Shift in Precision Livestock Farming (PLF). The global livestock industry is currently undergoing a radical digital transformation. As demand for high-quality protein increases alongside a growing global population, traditional husbandry methods struggle to balance productivity with the growing requirements for animal welfare and environmental sustainability. Precision Livestock Farming (PLF) has emerged as the definitive solution, utilizing technologies such as the Internet of Things (IoT), smart sensors, and advanced analytics. Among these, Computer Vision (CV), powered by Convolutional Neural Networks (CNNs), stands out as the most promising non-invasive tool. Unlike wearable sensors that may cause physical stress or require constant battery maintenance, CNN-based systems offer a "set-and-forget" approach to continuous, real-time monitoring of ethological patterns. Despite the proliferation of individual studies, there is a critical need for a comprehensive synthesis that maps the entire development pipeline—from image acquisition hardware to high-level algorithmic inference—across diverse species, including cattle, small ruminants, swine, and poultry. This study addresses this gap by reviewing the integration of Deep Learning for identifying phenotypic traits and by providing a strategic roadmap for sustainable, modern production. Method This review was conducted in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines to ensure transparency and replicability. A systematic multi-database search was conducted in Scopus, Web of Science, PubMed, and Google Scholar, focusing on peer-reviewed literature published between 2015 and 2024. The search string integrated keywords such as "Convolutional Neural Networks," "Deep Learning," "Precision Livestock Farming," and specific CV tasks. Out of hundreds of screened papers, only those demonstrating high technical validity and practical relevance to livestock management were selected. The inclusion criteria focused on the four pillars of computer vision: Object Detection, Semantic/Instance Segmentation, Pose Estimation, and Multi-Object Tracking (MOT). The study synthesized data from various farm environments, specifically analyzing how these models handle the "domain shift" between controlled lab settings and the harsh, unpredictable conditions of commercial barns characterized by variable illumination and high-density stocking. Results Core Computer Vision Applications in Animal Husbandry Object Detection and Individual Identification: Identifying, counting, and localizing animals is foundational to digital inventory management and Biosecurity. Advanced architectures such as the YOLO (You Only Look Once) series (v5-v8), Faster R-CNN, and SSD (Single Shot Multi Box Detector) have revolutionized this domain. Beyond simple counting, these models are now tuned for high-stakes event detection, such as Calving (Parturition) monitoring and Estrous behavior recognition. By automating the detection of these physiological milestones, farmers can intervene precisely when needed, reducing mortality rates and improving reproductive efficiency. Segmentation for Morphological Analysis: Image segmentation (specifically Mask R-CNN and U-Net) involves a pixel-level understanding of the animal's body. This technology is instrumental in automated Body Condition Scoring (BCS). By isolating specific anatomical markers, such as the rump, hooks, and pins, in dairy cows, the system can provide a numerical score of the animal's fat reserves. This objective, human-bias-free measurement is critical for managing nutritional intake and predicting milk yield, ensuring that metabolic diseases are caught before they escalate. Pose Estimation and Locomotion Analysis: By detecting skeletal key points and joints, systems such as Alpha Pose and Open Pose enable granular analysis of animal movement. In the dairy industry, this is applied to Locomotion Scoring for the early diagnosis of Lameness. Since CNNs can detect subtle changes in gait cycles and joint angles—often invisible to the human eye—they enable early treatment, preventing significant economic losses and protecting animal welfare. Multi-Object Tracking (MOT) and Behavioral Time Budgets: Combining CNN detectors with tracking algorithms such as Deep SORT (Simple Online and Realtime Tracking) enables persistent monitoring of individuals within a herd. This creates a high-fidelity map of an animal's Time Budget, recording exactly how long it spends feeding, drinking, or resting. Anomalies in these patterns act as "early warning signals" for distress, social isolation, or the onset of sub-clinical illness. Technical Development Pipeline: From Hardware to Inference A successful CNN implementation in a livestock barn is not merely about the code; it is a complex engineering pipeline: Data Acquisition and Hardware Selection: The review highlights the importance of camera specifications (resolution, frame rate) and placement (nadir vs. oblique views). The role of Graphics Processing Units (GPUs) is emphasized as the engine for training these deep models, alongside the potential of thermal and depth cameras for low-light environments. Pre-processing and Data Augmentation: Farm images are often noisy, dusty, or poorly lit. Techniques to enhance the Contrast-to-Noise Ratio (CNR) are essential. To address the challenge of small "farm-specific" datasets, this study reviews strategies such as Data Augmentation (flipping, cropping, and color jittering) and Transfer Learning (leveraging pre-trained weights from ImageNet) to prevent Overfitting and ensure the model generalizes well to new barns. Evaluation Benchmarks: To ensure scientific rigor, the study advocates for the standardized use of Mean Average Precision (mAP) for detection tasks, Intersection over Union (IoU) for segmentation, and MOTA (Multi-Object Tracking Accuracy) for monitoring systems. Discussion: Barriers to Implementation and Future Horizons While the technical accuracy of these models is high, the "Real-world" farm presents significant hurdles. Occlusions-where animals block the camera's view of one another-and extreme animal density remain the primary causes of "ID switches" in tracking systems. Furthermore, the high computational demands of state-of-the-art CNNs make them difficult to deploy on Edge Devices (e.g., local, low-power farm servers). Looking ahead, the trend is toward Sensor Fusion, in which CV data are integrated with Bio-acoustic sensors and environmental data (e.g., humidity and temperature) to create a comprehensive Digital Twin of the farm. Additionally, the shift toward Semi-supervised and Unsupervised Learning will likely reduce the substantial labor costs associated with manual data labeling, thereby making these systems more adaptable to different breeds and global farming practices. Conclusions CNN-based computer vision systems represent the cornerstone of the next generation of Smart Livestock Management. By automating the monitoring of health, welfare, and productivity, these technologies enable producers to shift from reactive to proactive management. This review provides the necessary strategic and technical framework for researchers and industry practitioners to successfully deploy deep learning models, ensuring a future that is more efficient, welfare-centric, and economically sustainable. هدف: تلفیق سیستم‌های بینایی کامپیوتری (CV) بر پایه شبکه عصبی کانولوشن (CNN) به‌سرعت در حال تغییر مدیریت حیوانات مزرعه‌ای در صنعت کشاورزی است. باوجود پیشرفت‌های قابل‌توجهی در این سیستم‌ها ، هنوز نیاز اساسی به یک مرور جامع و کامل از کاربردهای فعلی، نمونه‌های کاربردی، نواقص اصلی و راه‌حل‌های پیشنهادی آن‌ها وجود دارد. در این مقاله مروری به بررسی مراحل کاربردهای گوناگون بینایی کامپیوتری بر پایه شبکه عصبی(CNN) در حوزه مدیریت دام‌پروری هوشمند پرداخته‌شده است روش پژوهش: در این مطالعه به تحلیل و بررسی کاربردهای مختلف و به‌کارگیری شبکه عصبی کانولوشن، در زمینه تشخیص اشیاء، دسته‌بندی معنایی نمونه، پیش‌بینی حالت و ردیابی در بین دام‌های اصلی مزرعه مانند گاو، گوسفند و بز، خوک و طیور پرداخته‌شده است. در این مطالعه مراحل مهم برای توسعه سیستم، ازجمله تنظیمات دقیق دوربین، روش‌های مختلف جمع‌آوری داده‌ها، واحدهای پردازش گرافیکی، آماده‌سازی و پردازش اولیه تصاویر و برچسب‌گذاری مؤثر داده‌ها را بررسی می‌کند. همچنین معماری‌های مختلف شبکه عصبی کانولوشن متناسب با وظایف خاص بینایی ماشینی را شکل کامل و دقیق جمع‌آوری مورد تحلیل قرارگرفته است. یافته‌ها: این پژوهش نکات کاربردی مهمی برای توسعه الگوریتم، مانند تقسیم‌بندی دقیق داده‌ها، افزایش داده‌ها، تنظیم داده‌ها قبل از شروع یادگیری و انتخاب معیارهای ارزیابی مناسب را ارائه می‌دهد. همچنین در این مطالعه یک چارچوب کلی و نظام‌مند برای تشخیص چالش‌های موجود و مشکلات آینده ارائه می‌دهد نتیجه‌گیری: هدف نهایی این مقاله مروری ارائه یک راهنما به پژوهشگران و فعالان و متخصصان جهت توسعه و پیاده‌سازی موفقیت‌آمیز سیستم‌های بینایی ماشینی (CV) مبتنی بر شبکه عصبی کانولوشن(CNN) برای مدیریت پایدار و صحیح در دام‌پروری نوین است.

https://naias.uma.ac.ir/article_4473_4c76aa494f965fda33e114032ca8509e.pdf

دانشگاه محقق اردبیلی یافته‌های نوین علوم دامی 1 1 2026 04 24 Using Nonlinear Regression Functions to Growth Curve Description of Sanjabi Sheep استفاده از توابع رگرسیون غیرخطی جهت توصیف منحنی رشد گوسفند سنجابی 1 12 4474 10.22098/naas.2026.19102.1010 FA سجاد بادبرین استادیار بخش تحقیقات علوم دامی، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی کرمانشاه، سازمان تحقیقات، آموزش و ترویج کشاورزی، کرمانشاه، محمد حیدری استادیار بخش تحقیقات علوم دامی، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی کرمانشاه، سازمان تحقیقات، آموزش و ترویج کشاورزی، کرمانشاه، جواد احمد پناه بخش تحقیقات علوم دامی، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی استان ایلام، سازمان تحقیقات، آموزش و ترویج کشاورزی، ایلام، ایران. Journal Article 1970 01 01 Introduction Growth traits are among the most critical components determining productivity and economic efficiency in sheep production systems. Body weight gain over time directly influences feed conversion efficiency, carcass yield, meat quality, and profitability. Accurate characterization of growth patterns enables producers and researchers to optimize management practices, improve feeding strategies, and design effective breeding programs. Growth curve analysis provides a comprehensive approach to describe longitudinal body weight changes by fitting mathematical models with biologically interpretable parameters. These models allow prediction of body weight at different ages, identification of growth acceleration and deceleration phases, and estimation of mature body weight and growth rate. However, the suitability and performance of growth models may vary depending on breed, environmental conditions, management system, and data structure. Therefore, it is essential to evaluate breed-specific growth models to obtain reliable and applicable results. Sanjabi sheep is a native fat-tailed breed predominantly raised in Kermanshah province, located in western Iran. This breed is known for its large body size, adaptability to harsh environmental conditions, acceptable growth performance, and high market preference due to meat quality. Sanjabi sheep play a significant role in regional red meat production and rural livelihoods. Despite its economic and genetic importance, limited information is available about growth pattern characterization and appropriate nonlinear growth models for this breed. A clear understanding of growth dynamics in Sanjabi sheep is essential to improv production efficiency and support sustainable breeding strategies. The primary objective of this study was to describe the growth curve of Sanjabi lambs using different nonlinear regression models and to compare their performance in predicting body weight changes from birth to nine months of age. An additional objective was to identify the most appropriate model based on goodness-of-fit criteria, which could be applied in breeding, nutritional planning, and management decision-making for Sanjabi sheep. Method The data used in this study consisted of body weight records of Sanjabi lambs measured at birth and at 1, 2, 3, 6, and 9 months of age. Records were collected from lambs raised at the Mehrgan Research Station located in Kermanshah province during the period 2018 to 2024. The flock was managed under a semi-intensive production system. Animals grazed on natural rangelands and cultivated pastures from spring to early autumn, while indoor feeding was practiced during late autumn and winter. Diets were formulated according to age, sex, and physiological status, and lambs were weaned at approximately three months of age. All lambs were identified and ear-tagged at birth, and body weights were recorded at predetermined intervals. Prior to statistical analysis, data editing was performed to remove incomplete records and biologically implausible weight changes between consecutive ages, ensuring data reliability. Four nonlinear growth models, including Gompertz, Logistic, Von Bertalanffy, and Brody models, were fitted to the body weight data using nonlinear regression procedures in SAS software. Each model included three parameters: A, representing asymptotic or mature body weight; B, an integration constant related to initial body weight; and K, the maturity or growth rate parameter indicating the growth rate of animals to mature weight. Model were compared and selected using multiple goodness-of-fit criteria, including the coefficient of determination (R²), mean square error (MSE), and Akaike information criterion (AIC). Models with higher R² values and lower MSE and AIC values were considered to provide a better fit to the observed data. Results Descriptive statistics indicated a steady increase in mean body weight from birth to nine months of age, accompanied by an increase in standard deviation and coefficient of variation at later stages of growth. This pattern reflects increasing phenotypic variability among animals as growth progresses, likely due to cumulative effects of genetic differences and environmental factors. Estimated values of the mature weight parameter (A) varied among the evaluated models. The highest estimate of mature weight was obtained from the Brody model, while the lowest estimate was observed in the Logistic model. The differences in mature weight estimates reflect structural differences among models and their sensitivity to data from later stages of growth. The maturity rate parameter (K) also differed considerably among models. The Logistic model produced the highest K value, indicating a faster growth rate during early life. In contrast, the Brody model showed the lowest K value, suggesting a slower but more gradual growth rate. Correlation analysis between growth curve parameters revealed a consistent negative relationship between mature weight (A) and maturity rate (K) across all models. This inverse relationship suggests that animals exhibiting faster early growth do not necessarily achieve higher mature weights. Such relationships have important implications for breeding programs, as selection solely for rapid early growth may result in reduced mature body size. In terms of model performance, the Gompertz model exhibited the highest coefficient of determination, indicating strong explanatory power. However, the Brody model showed the lowest AIC and MSE values, reflecting superior overall goodness-of-fit and lower prediction error. Considering all evaluation criteria simultaneously, the Brody model was identified as the most appropriate model for describing the growth curve of Sanjabi lambs. Conclusions The results of this study demonstrate that nonlinear growth models are practical tools for describing and analyzing growth patterns in Sanjabi sheep. Although all evaluated models were capable of fitting body weight data reasonably well, the Brody model provided the best overall fit based on information criteria and prediction accuracy. The superiority of the Brody model suggests that it more accurately reflects the biological growth pattern of Sanjabi lambs, characterized by rapid growth during early life followed by a gradual reduction in growth rate at later stages. The findings of this research have practical implications for sheep production systems. The selected growth model can be used to predict body weight at different ages, identify growth slowdown points, optimize feeding and management strategies, and determine appropriate slaughter age. Furthermore, growth curve parameters derived from the Brody model may serve as valuable auxiliary traits in selection indices, enabling simultaneous improvement of growth performance and economic efficiency in Sanjabi sheep breeding programs. هدف: به دلیل اهمیت اقتصادی صفات رشد در گوسفند، چگونگی تغییرات وزن بدن در سنین مختلف از نظر طراحی برنامه‌های اصلاح نژادی اهمیت زیادی دارد. بهترین تابع توصیف کننده منحنی رشد بسته به نژاد و جمعیت تحت بررسی می‌تواند متفاوت باشد. هدف این پروژه توصیف منحنی رشد گوسفند سنجابی برای صفات وزن بدن در سنین مختلف با استفاده از مدل‌های غیر خطی رشد بود. روش پژوهش: اطلاعات مورد استفاده در این تحقیق شامل رکوردهای کامل وزن تولد، 1، 2، 3، 6 و 9 ماهگی وزن بدن 719 رأس بره سنجابی (369 رأس بره ماده و 350 رأس بره نر) بود که در طی سال‌های 1397 تا 1403 در ایستگاه تحقیقات مهرگان واقع در استان کرمانشاه جمع‌آوری شده بود. برای توصیف منحنی رشد از چهار مدل تابعیت غیرخطی شامل مدل‌های گومپرتز، لجستیک، ون برتالانفی و برودی استفاده شد. مدل‌ها با رویه NLIN نرم‌افزار SAS (4/9) برازش شد. بهترین مدل یا استفاده از معیارهای ضریب تبیین، میانگین مربعات خطا و شاخص اطلاعات آکائیک تعیین شد. یافته‌ها: مقدار پارامتر A در مدل‌های گومپرتز، لجستیک، وان برتالانفی و برودی به ترتیب برابر با 54/38، 93/36، 32/39 و 77/42 کیلوگرم محاسبه شد. همچنین مقدار پارامتر K در این مدل‌ها به ترتیب برابر با 46/0، 70/0، 39/0 و 23/0 محاسبه شد. بر اساس معیارهای نیکویی برازش، با وجود آن‌که مدل گومپرتز بیشترین مقدار ضریب تعیین را نشان داد، ولی مدل برودی با کمترین مقادیر شاخص اطلاعات آکائیک و میانگین مربعات خطا، به‌عنوان مناسب‌ترین مدل برای توصیف منحنی رشد بره‌های نژاد سنجابی انتخاب شد. نتیجه‌گیری: نتایج این تحقیق نشان داد که مدل‌های آماری بررسی شده با دقت بسیار بالایی توانایی توصیف چگونگی رشد گوسفند سنجابی را دارند و از میان آن‌ها مدل برودی بهترین برازش و انطباق را نشان داد. بنابراین از این منحنی می‌توان در بررسی مشکلات مدیریتی، تنظیم برنامه‌های تغذیه‌ای و شناسایی نقطه کاهش رشد گوسفند سنجابی استفاده نمود.

https://naias.uma.ac.ir/article_4474_ee58da32f7b6eb8e766117d022ed0183.pdf