Morphometrics measurement, physiology traits and parasites infestation of dairy goats farms in North Sumatra, Indonesia: Challenges for the environmental sustainability of milk production

Morphometrics measurement, physiology traits and parasites infestation of dairy goats farms in North Sumatra, Indonesia: Challenges for the environmental sustainability of milk production | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Morphometrics measurement, physiology traits and parasites infestation of dairy goats farms in North Sumatra, Indonesia: Challenges for the environmental sustainability of milk production Bess Tiesnamurti, Santoso Santoso, Peni Wahyu Prihandini, Gresy Eva Tresia, and 11 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8839115/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The study aims to investigate factors that influence the sustainability of dairy goats in the Deli Serdang, Indonesia. A total of 172 head of dairy goats from different breeds at 9 subdistricts were used in this study. The parameters observed were the type of feeds given to the animals, the morphometric measurements, the physiological traits of the animals, gastrointestinal infestation, and milk production. The result showed that the majority of feeds given to the goats were cut and carry green fodder (95.83%), tofu by-products (58.33%), and concentrate (25%), respectively. The dairy goats in this study were categorized as short with an average body index of 0.91. There was a significant influence (p < 0.05) of age on rectal temperature (RT) and heat tolerant coefficient (HTC); however, not for heart rate (HR), respiration rate (RR), and adaptation coefficient (AC), respectively. The most abundant gastrointestinal parasite was coccidia, with the lowest (57%) and highest (100%) prevalence occurring in 4-year-old and 3-year-old goats, respectively. The highest milk production was found in 3-year-old goats (931.1 ml), whereas does with body condition score (BCS) = 3.5 have persistently higher milk production. By using modelling, the most likely scenario to improve dairy goats' sustainability was scenario 5 (increase dairy goat population of 2,266 heads, milk yield increase to 703.10 tons per year, and the highest growth rate of 9.65%). In this study, dairy goat farmers sustain their milk production by utilizing local feed resources, demonstrating good adaptation to internal parasites, and adjusting to the local environment. body index physiology traits gastrointestinal parasite milk production the dynamics system Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 1. Introduction Indonesia is an archipelago with an estimated 275.773 million human population and requires a continuous supply of animal-based protein such as milk, meat, and eggs. The dairy cattle population is 507,075 head and produced 837.2 thousand tons of milk in 2023, when compared to 2019, milk production decreased by 12.90 percent ((Ministry of Agriculture, 2024 ). The national milk demand is about 4.19 million tons, and 81% is still imported, therefore, the substitution with dairy goat milk is probably a solution to meet the national milk demand. BPS (2023) reported that the average National milk demand increases by approximately 6% per year, however, milk production grows only 1% per year. The national milk consumption is considered low, approximately 16.27 kg per capita per year, with a national milk production of 997,000 tons from the national demand of 4.3 million tons (BPS, 2023). The majority of dairy goat breeds in the country are Etawah crossbred (PE), even though other breeds are available, such as Saanen, Anglo-Nubian, and their crosses, respectively. PE goats are mostly similar to Jamnapari goats of India, imported around the 19th century. Indonesia's estimated dairy goat population is probably around 1% of the national goat population of 18.560.835 head (Ministry of Agriculture, 2023 ). The total milk production of the Etawah cross, Saanen and Etawah cross, Anglo Nubian, and Senduro breeds in Indonesia was 154.3, 264.6, 214.2, and 196.6 L/lactation, respectively (Soemarmono, 2022). The distribution of dairy goats spread over the country, presumably found in 21 out of 34 provinces in Indonesia. The linear measurement of animals is an important parameter in investigating growth rate according to age and the nutritional status given to the animals. Earlier study showed, that heart girth was the best indicator for differentiating goats with a history of multiple and single litter size in goats (Haldar et al., 2014), whereas body morphology is closely related to milk performance (Gulinski et al., 2005) and longevity, which determines the contributions to lifetime milk production of a dairy animal (Sawa et al., 2013). Heart rate (HR), respiration rate (RR), and rectal temperature (RT) are expressions of the metabolic process of the animal and depend largely on the ambient temperature where goats are raised. The temperature-humidity index (THI) has been widely used to estimate the degree of thermal stress that livestock experience. The infestation of internal parasites in small ruminants occurs either through grazing management or also carrying away the eggs on the forages given to the animal, through a cut-and-carry system. Gastrointestinal parasite infection, including nematode ( Strongyles ) and protozoa ( Coccidia ), is a major hindrance which have a significant impact on the development of goat production in many parts of the world (Maurizio, di Regalbono, and Cassini, 2021 ). In Indonesia, the average milk production of PE goat fed with 11% crude protein was 661.11- 892.22 mL day − 1 (Chintyadhevi Aulia Rahmi, Nenny Harijani, Suwarno Suwarno, Mohammad Anam Al Arif, Budiarto Budiarto, and Sunaryo Hadi Warsito 2021). Previous studies have highlighted morphometric and physiological measurements of dairy goat, but have rarely explored the dynamic interplay between population growth, milk production, and economic factors in dairy goat production systems. The system dynamics (SD) modeling offers a powerful tool to address the complexity of sustainability in dairy goat farming. SD is particularly effective in analyzing interconnected subsystems and feedback loops for evaluating long-term strategies (Sterman, 2000 ). Previous studies have applied SD models to various aspects of dairy farming, such as dairy cattle population dynamics, milk production, and feed management (Lie et al., 2018 ); dairy cattle population and milk supply-demand dynamics (Susanty et al., 2019 ); and dairy goat production systems (Guimarães et al., 2009 ). Furthermore, SD has been employed in the context of dairy supply chain systems (Azizsafaei et al., 2022 ) and technology adoption within dairy supply chains (Simões et al., 2020 ). This field study was meant to investigate the factors contributing to dairy goats' productivity that may influence their sustainability. Therefore, it is significant to explore more research on the morphometry, physiology, nutrition status, and external parasites on the dairy goats raised by smallholder farmers in the Deli Serdang District of North Sumatra province, which have not been extensively studied. This study has not been reported elsewhere, especially in conjunction with dairy goat sustainability. 2. Materials and methods 2.1. Study area and animals This study was undertaken on 24 dairy goat farmers with a total of 172 heads in nine sub-districts of Percut Sei Tuan, Sinembah Tanjung Muda Hilir, Deli Tua, Namorambe, Simalingkar, Kutalimbaru, Pancur Batu, Bangun Purba, and Sunggal, districts of Deli Serdang located on the East Coast of North Sumatra Province, Indonesia (Fig. 1 ). Goats were kept intensively at all times, with a group of three does per pen. Each observation used a different number of animals, depending on the substance of the study and the availability of the animals. 2.2. Nutrition and the feeding system In nutrition and feeding system study, farmers were voluntary participated in the survey. The study objectives and procedures were explained to all participants, and informed consent was obtained prior to the interviews. Consent was collected either in written form or verbally, depending on participants’ preference and feasibility in the field setting. No minors were involved in this study. A total of 24 randomly selected dairy farmers were interviewed using a pre-tested structured questionnaire and through direct observations. The respondents were farmers from nine sub-districts. The randomly selected farms were stratified into three groups based on the number of dairy goats owned: small farms owning 1–20 does (8 farms), medium farms with 21–40 animals (8 farms), and large farms with more than 40 animals (8 farms). A single-visit-multiple-subjects formal survey technique (ILCA, 1990) was used to collect data through household interviews. The data collected included: conventional and non-conventional feed resources, feeding practices/systems, and sources of feed acquisition. Feed samples were collected for proximate analysis following AOAC (2005) procedures. Feeding management was performed with a cut-and-carry system, offered twice a day, in the morning around 07:00 and at 17:00, and water was provided ad libitum . Various agricultural by-products and grasses were given to the goats, approximately 5 kg head − 1 day − 1 . The barn was cleaned daily before the doe was milked. Animal health was controlled by a veterinarian if there was a report from the owner, otherwise, all was handled by the farmer. Animals were offered roughage of different sources and agricultural by-products according to the season and availability. 2.3. Morphometric measurements and body indices Body weight (BW) and morphometric measurements were recorded from a total of 110 female Etawah Grade goats. The body measurements included body length (BL), withers height (WH), chest girth (CG), chest depth (CD), chest width (CW), rump height (RH), rump width (RW), cannon circumference (CC), head length (HL), head width (HW), ear length (EL), ear width (EW), teat perimeter (TP), and teat length (TL). Body weight was measured using a digital livestock scale, while body dimensions were obtained using measuring sticks and tape, following the standard procedures outlined by the Food and Agriculture Organization ((FAO, 2012 ), as described in Fig. 2 . 2.4. Physiological response and the adaptation coefficient The physiological response, including respiration rate (RR), heart rate (HR), and rectal temperature (RT), was measured from 112 heads of PE of different ages belonging to 4 farmers. RR was measured by counting the flank movement (time per minute), HR was measured by palpating the pulse rate (time per minute), and RT was measured by inserting a thermometer into the rectum for one minute (°C). Measurements were conducted individually in October 2021, in the morning around 08:00 am, inside the barn. Data on micro-climate (ambient temperature and humidity) were derived from the local meteorological office. The temperature and humidity index (THI), index Benezra (HTC), and the adaptation coefficient (AC) were calculated according to the following formula: THI = 0.8 × T + (H/100)× (T − 14.4) + 46.4 Kitajami et al., (2021) HTC = 100 - [18 x (RT − 38.60)] Araujo et al ., (2017) AC = RT/39.1 ± RR/19 ± HR/75 Araujo et al ., (2017) and Habeeb et al., ( 2018 ) Note: T=local temperature ( o C), H = air humidity (%), RT=rectal temperature ( 0 C), RR=respiration rate (time per minute), HR=heart rate (time per minute) 2.5. Infestation of internal parasites Fecal samples from 66 goats belong to five farmers from Percut Sei Tuan district, were taken directly from the rectum of each animal using disposable gloves and then placed in sterile plastic. The sampling date and goat information, including sex, age, and identification number for each case, were labelled on the plastic. Samples were transferred directly on the same day of collection to the laboratory in airtight boxes cooled with dry ice packs and then stored at 4°C until analysis. Fecal samples were examined microscopically for nematode eggs and oocyst coccidia presence using the Whitlock method with modification (Whitlock, 1948 ). Three grams of feces from each animal were dissolved with 17 ml of tap water and stirred homogeneously. Then, 40 mL of saturated salt solution (NaCl, specific gravity = 1.200) was used to float the nematode eggs/ oocyst coccidia. While stirring, the fecal solution was taken with a Pasteur pipette with a filter modification in the tip, and then the solution was put into the ‘Whitlock counting chamber’ (Whitlock, 1948 ), nematode eggs /oocyst coccidia were counted, and the number was multiplied by 40. The number of eggs was counted in units of eggs per gram (EPG) / oocysts per gram (OPG). 2.6. Milk production Milk production records from 172 crossbred does of Etawa owned by 7 farmers were used in this study. In addition to milk production, other records were also collected, such as body weight after giving birth, age, lactation period, and body condition score (BCS). They were milked twice daily, in the morning around 07:00 and at 15:00, by hand milking. Before milking, does were separated, and the mammae were cleansed thoroughly. Kids were allowed to suckle for 4 weeks, then separated and given milk replacements. The volume of milk was measured using a measuring cup with 10 mL sensitivity. 2.7. The system dynamics of dairy goat sustainability System dynamics (SD) is chosen for its capability to model and simulate the interrelated components of complex systems over time (Priyono et al., 2023 ; Sterman, 2000 ), with the goal of developing a sustainable dairy goat farming system. In this study, the SD model consists of five interconnected submodels: (a) Population Dynamics Submodel; (b) Milk Production Submodel; (c) Feed Management Submodel; (d) Milk Demand Submodel; and (e) Economic Submodel. Each submodel is constructed using causal loop diagrams and stock-and-flow diagrams to represent the dynamic relationships and feedback mechanisms (Fig. 3 ). Data for the model parameters were sourced from field surveys, secondary literature, and expert consultations. 2.8. Statistical Analysis Microsoft Excel was used for data management, coding, and entry. The SAS v.9.4 (2021) was used to describe the descriptive statistics (frequencies and percentages) of the feeding types given to the animal. Statistical analysis of body measurement, body indices, physiological response, HTC, and AC, was conducted by using the general linear model of SAS v.9.4 (2021) statistical package, with the following model and assumption: Y ijklm = µ + A i + B j + Ɛ ijk Description : Y ijk : the observation of body measurement, body indices, physiological response (RR, HR, RT, HTC, AC), from i th age of the animal and j th breed of goats µ : general mean A i : the effect of i th age, where i = 1, 2, 3, 4, and > 4 years old B j : the effect of j th breed, where j = PE, Saanen, Anglo Nubian, and Boerawa Ɛ ijk : standard error from the effect of age and breed The statistical analysis for milk production was conducted using the following model and assumption : Y ijk = µ + A i + B j + Ɛ ijk Description : Y ijk : the observation of milk production from the i th age of the animal, j th period of lactation, µ : general mean A i : the effect of i th age, where i = 1, 2, 3 age groups B j : the effect of k th lactation period, where k = 1,2,3 Ɛ ijkl : standard error from the effect of age, breed, and lactation period Differences among group means were assessed using Duncan’s Multiple Range Test (DMRT) at a significance level of p < 0.05. The results are presented as means ± standard deviations (SD). The sustainability model for population dynamics in dairy goat farming was validated through structural and behavioural validation processes. Structural validation involved verifying the logic and consistency of the causal and stock-flow diagrams with the input of experts. Additionally, behavioural validation was conducted by comparing the simulated outputs with historical data to confirm the model's ability to replicate observed trends. The Mean Absolute Percentage Error (MAPE) method was applied to assess behavioural validation (Sterman, 2000 ): $$\:MAPE=\:\frac{1}{n}\:{\sum\:}_{t=1}^{n}\left(\frac{\left|{Y}_{t}-\stackrel{-}{{Y}_{t}}\right|}{{Y}_{t}}\right)\:x\:100$$ Description: \(\:{Y}_{t}\) actual data values; \(\:{\stackrel{-}{Y}}_{t}\) model simulation values; and n = year/time interval. To assess the impact of various intervention strategies on the sustainability of dairy goat farming, the simulation (Table 1 ) included five intervention scenarios implemented under two different policy conditions: moderate intervention (begins in 2027) and optimistic intervention (begins in 2029). Each scenario targeted key factors affecting the female dairy goat population and their milk production. Each intervention scenario was modelled to simulate changes in key parameters: birth rate, conception rate, and milk production. The results were analysed over a simulation period from 2023 to 2045, capturing the long-term effects of different policy interventions. Table 1 Simulation parameters under different intervention scenarios. Intervention Baseline Scenario 1 Scenario 2 Scenario 3 Scenario 4 Scenario 5 Moderate policy intervention starts in 2027 Birth Rate (kids per doe per year) 1.40 1.50 1.40 1.50 1.40 1.50 Conception Rate (%) 45 45 50 50 45 50 Milk Production (liters/head/day) 0.70 0.70 0.70 0.70 1 1 Optimistic policy intervention starts in 2029 Birth Rate (kids per doe per year) 1.40 1.60 1.40 1.60 1.40 1.60 Conception Rate (%) 45 45 55 55 45 55 Milk Production (liters/head/day) 0.70 0.70 0.70 0.70 1.20 1.20 Notes: Birth Rate (Intervention: improved reproductive management); Conception Rate (Intervention: genetic quality improvement); and Milk Production (Intervention: enhanced feeding with concentrate and high-quality forage) 3. Results 3.1. Nutrition and feeding system of the dairy goats The feed resources predominantly used in the study area are shown in Table 2 . A total of sixteen major feed types used by dairy goat farmers were identified and divided into five categories: natural grass, green forage, silage, concentrates (including commercial mixtures and agro-industrial by-products), and non-conventional feed resources, respectively. Table 2 The nutrient content of the feeds commonly used by farmers Feedstuff DM (%) Chemical composition (% DM) Ash CP EE CF ADF NDF NFE TDN Natural grass/Nutgrass (Cyperus kyllinga ) 22.99 18.39 7.6 0.41 40.97 39.14 66.16 32.63 45.37 Green forages (cut and carry) Pennisetum purpureum cv.Mott 16.53 13.55 18.12 2.22 31.17 42.02 65.84 34.94 54.31 Pennisetum purpureum 8.50 16.69 18.52 2.261 22.63 37.54 69.61 39.897 57.27 Pennisetum purpureum cv.Zanzibar 16.53 11.26 5.62 1.58 33.38 41.64 68.56 48.16 49.29 Silages Maize silage 19.46 7.40 4.19 2.1 24.78 32.74 55.51 61.53 72.15 Cassava leaf silage 1 25.24 7.88 20.76 11.87 18.39 41.37 56.14 41.1 66.32 Concentrate and agro-industrial by-products Maize 2 88.00 1.5 8.6 2.7 1.7 3.4 5.1 85.5 85.28 Soybean meal 2 89.9 6.5 47.5 1.7 3.3 5.1 8.4 41.0 82.14 Soya waste 20.66 3.79 25.19 11.07 18.24 16.35 28.2 41.71 77.52 Tofu byproduct 3 10.73 4.34 15.81 3.6 35.15 16.37 22.24 41.1 57.87 Soya bean hulls 70.19 7.59 11.19 6.05 16.23 21.75 30.54 58.94 69.43 Tapioca by-products 9.17 3.27 4.19 1.32 25.16 32.31 46.83 66.06 54.97 Dried cassava 4 94.84 2.74 1.12 2.03 19.2 40.9 17.6 74.91 57.59 Non-conventional feed resources Banana plant stem 8.02 6.29 7.00 2.18 24.84 32.06 48.36 59.69 56.62 Cassava leaves 23.04 8.39 16.75 4.88 27.78 44.11 55.87 42.20 58.95 Dried cassava peel 4 94.23 4.86 5.30 2.98 38.40 37.40 51.40 48.46 52.61 Notes:DM: dry matter; CP: crude protein; EE: ether extract; ADF: Acid detergent fiber; NDF: Neutral detergent fiber; NFE: Nitrogen free extract; TDN: Total digestible nitrogen. NFE is based on the formula NFE = 100 – Dry matter – Crude protein – Crude fat – Crude fiber. Total digestible nutrient (TDN) content was estimated according to Hartadi et al. ( 1980 ). 1 Oni et al. ( 2014 ); 2 Barzegar et al. ( 2019 ); 3 Syafrudin et al. ( 2020 ); 4 Aro and Aletor, ( 2012 ). Table 3 depicts the frequencies (%) of feed resources utilized by smallholder dairy goat farmers in North Sumatra, grouped by farm size (small, medium, and large). In this study, natural grass, green forage, and tofu by-products were widely used as the basal diet, with more than 50% of goat farmers utilizing them. There are no significant differences in feedstuff usage (natural grass, green forage, concentrate, tofu by-product, and dried cassava) among different farm sizes. Table 3 Frequencies (%) of feed resources as reported by smallholder dairy goat farmers in the District of Deli Serdang, North Sumatra Province. Feedstuff Type of farm Total p value Small (n = 8) Medium (n = 8) Large (n = 8) Natural grass/Nut grass ( Cyperus rotundus L ) 75.00 50.00 37.50 54.17 0.584 Green forage (cut carry) 87.50 100.00 100.00 95.83 0.957 Silages Maize silage 0.00 0.00 12.50 4.17 - Cassava leaf silage 12.50 0.00 0.00 4.17 - Concentrate and agro-industrial by-products Concentrate 12.50 25.00 37.50 25.00 0.607 Maize 12.50 0.00 0.00 4.17 - Soybean meal 25.00 0.00 0.00 8.33 - Soya waste 0.00 25.00 12.50 12.50 - Tofu byproduct 50.00 62.50 62.50 58.33 0.109 Tapioca by-products 0.00 25.00 12.50 12.50 - Soya bean hulls 25.00 12.50 0.00 12.50 - Dried cassava 12.50 12.50 12.50 12.50 0.564 Non-conventional feed resource Banana plant stem 0.00 12.50 0.00 4.17 - Cassava leaves 12.50 0.00 25.00 12.50 - Cassava peel 12.50 0.00 0.00 4.17 - 3.2. Morphometric measurements and body indices of the dairy goats Body weight and body measurement of the female Etawah Grade goat in this study are presented in Table 4 . The results showed that there was an effect of age on body weight and nearly all body measurements in female Etawah Grade goat, except for cannon circumference (CC), ear length (EL), and ear width (EW). Body indices are distinguished by breed, sex and ages. The results of the body index of dairy goats in North Sumatra are shown in Table 5 . Length index, height index, height slope, depth index, body index, proportionality, and pelvic index based on breed, sex, and age did not show significant differences. Area index based on sex and age showed significant differences based on sex and age, while based on breed there was no significant difference. Area index of bucks was higher than does. Goats of age group I0 had lower area index compared to I2, I3 and I4, and goats of age I2 were only lower than goats of age group I4. Table 4 Body weight and body measurements (mean ± standard deviation) of female dairy goats in different age groups. Traits Age group Overall (n = 110) CV (%) 1PPI (n = 14) 2PPI (n = 32) 3PPI (n = 32) 4PPI (n = 32) Body weight (kg) 33.62 ± 6.28 a 36.50 ± 7.40 a,b 39.88 ± 5.19 b,c 47.18 ± 7.57 d 40.13 ± 8.26 20.58 Body length (cm) 59.96 ± 6.26 a 61.08 ± 4.49 a,b 63.38 ± 6.02 b,c 66.25 ± 5.40 c 63.11 ± 5.86 9.29 Withers height (cm) 66.43 ± 5.02 a 68.81 ± 4.52 a 68.89 ± 5.68 a 72.39 ± 4.91 b 69.57 ± 5.36 7.70 Chest girth (cm) 74.43 ± 8.10 a 76.31 ± 5.84 a,b 78.50 ± 4.72 b 83.50 ± 4.44 c 78.80 ± 6.35 8.06 Chest depth (cm) 23.36 ± 2.01 a 25.22 ± 2.99 b 25.47 ± 2.57 b 28.25 ± 2.55 c 25.94 ± 3.07 11.84 Chest width (cm) 12.25 ± 1.55 a 12.39 ± 1.86 a 13.05 ± 1.79 a 14.08 ± 1.67 b 13.06 ± 1.87 14.32 Rump height (cm) 69.07 ± 6.07 a 71.31 ± 4.48 a,b 71.34 ± 6.42 a,b 74.41 ± 5.03 b 71.94 ± 5.66 7.87 Rump width (cm) 11.61 ± 2.56 a 11.69 ± 1.73 a 12.16 ± 1.62 a,b 13.19 ± 1.86 b 12.25 ± 1.94 15.84 Cannon circumference (cm) ns 9.38 ± 0.84 a 10.11 ± 4.39 a 10.72 ± 4.45 a 10.06 ± 0.62 a 10.18 ± 3.39 33.30 Head length (cm) 16.14 ± 1.96 a 17.34 ± 2.62 a,b 17.88 ± 2.99 a,b 18.55 ± 4.24 b 17.70 ± 3.26 18.42 Head width (cm) 9.29 ± 1.07 a 9.27 ± 0.97 a 9.44 ± 1.43 a 10.22 ± 1.51 b 9.60 ± 1.34 13,96 Ear length (cm) ns 24.79 ± 5.44 24.65 ± 6.67 25.34 ± 5.07 28.01 ± 4.94 25.85 ± 5.70 22.05 Ear width (cm) ns 10.39 ± 2.54 10.25 ± 2.79 10.25 ± 2.52 11.34 ± 2.92 10.59 ± 2.73 25.78 Teat perimeter (cm) 6.50 ± 2.14 a 8.75 ± 3.93 b 9.41 ± 3.68 b 10.19 ± 4.10 b 9.07 ± 3.85 42.45 Teat length (cm) 5.71 ± 1.68 a 7.84 ± 3.23 b 8.72 ± 3.26 b 9.47 ± 2.93 b 8.30 ± 3.18 38.31 Note: Superscript letters (a-d) indicate significant differences (p < 0.05) within the same rows and age groups. ns = non-significant. PII = pair of permanent incisors Table 5 The average body index according to breed, sex, and age of the dairy goats (mean ± standard deviation) in the study area Length index Area Index Depth Index Body Ratio Height slope Proportionality Body Index Pelvix Index Average 0.91 4473.66 37.11 0.97 2.22 110.82 80.39 97.1 Max 1.21 6557 48.61 1.11 8 145.28 108 154.54 Min 0.69 2809 18.52 0.89 -7 82.58 60.98 68.75 Breed PE ( ) 0.91 ± 0.09 4465.2 ± 712.03 37.03 ± 4.21 0.97 ± 0.04 2.25 ± 2.55 110.91 ± 10.27 80.49 ± 7.29 97.2 ± 16.95 Sapera ( ) 0.94 ± 0.02 4970 ± 396 41.95 ± 4.78 0.99 ± 0.01 0.5 ± 0.71 105.81 ± 1.88 74.96 ± 2.89 91.25 ± 5.3 Sex Male 0.91 ± 0.09 5797.5 ± 641.3 b 34.04 ± 8.88 0.98 ± 0.07 1.5 ± 2.605 110.6 ± 7.79 82.10 ± 6.58 102.84 ± 14.08 Female 0.91 ± 0.09 4403.9 ± 644 a 37.27 ± 3.87 0.97 ± 0.04 2.26 ± 2.26 110.84 ± 10.84 80.30 ± 7.32 96.8 ± 16.96 Age I0 ( ) 0.88 ± 0.07 3377.5 ± 187.4 a 35.49 ± 0.15 0.99 ± 0.02 0 ± 1.41 113.82 ± 9.26 76.56 ± 11.05 97.43 ± 21.32 I1 ( ) 0.91 ± 0.11 3988.2 ± 534.4 ab 35.26 ± 3.1 0.96 ± 0.04 2.64 ± 2.62 111.63 ± 12.05 81.04 ± 8.06 94.61 ± 10.99 I2 ( ) 0.89 ± 0.05 4337.6 ± 668.5 bc 36.48 ± 3.51 0.97 ± 0.03 2.43 ± 2.33 113.05 ± 6.9 80.46 ± 5.38 95.66 ± 18.69 I3 ( ) 0.92 ± 0.11 4423.4 ± 649.6 bc 36.6 ± 5.41 0.97 ± 0.04 2.44 ± 2.65 109.44 ± 12.05 81.09 ± 9.34 97.1 ± 16.35 I4 ( ) 0.91 ± 0.1 4901.7 ± 643.6 c 39.01 ± 3.63 0.98 ± 0.04 1.79 ± 2.67 109.44 ± 10.45 79.65 ± 6.48 99.45 ± 17.64 Notes different alphabet from one category in one column means different (p < 0.05) 3.3. Physiological response and the adaptation coefficient of the dairy goats There was no significant influence of the animal’s age on HR, RR, and AC, however, a significant influence (p < 0.05) was investigated for RT and HTC (Table 6 ). The average HR, RR, RT, were 77.89 ± 11.4 beats per minute, 13.09 ± 2.36 breaths per minute, and 39.0 ± 0.41 0 C; respectively. The heart rate of the doe increases according to age. Whereas, the average HTC and AC from this study were 101.75 ± 30,0 and 0.41 ± 2.26, respectively. The average air temperature, relative humidity, and THI from the study site during 2021 were 27.05 0 C, 85.9%, and 78.9, respectively. The lowest THI (77.81) was found in January 2021, and the highest THI (80.15) occurred in May 2021. The THI calculation from February to December 2021 put them in extreme condition, ranging from 78.12 to 79.51. The average ambient temperature, humidity, and THI in 2021 is shown in Fig. 4 . Table 6 Mean of Physiological Response, Heat Tolerance Coefficient, and Adaptation Coefficient of the goats in the study area Source of variation Heart Rate (Beat/Min) Respiration Rate (Breath/Min) Rectal Temperature ( 0 C) Heat Tolerance Coefficient Adaptation Coefficient Age (n) I-2 (15) 75.4a 52.8 38.9a 107.3b 4.7a I-3 (35) 74.9a 53.9 39.0a 101.4b 4.8a I-4 (32) 81.1a 53.3 39.0a 102.4b 5.6a ≥ I-5 (30) 79.5a 49.0 39.0a 101.2b 4.6a Breed (n) PE (110) 77.6a 46.0 38.9a 101.8a 4.6a Senduro (2) 92.0a 52.4 39.2a 98.2a 4.9a Sex Male (4) 81.0 55.0 38.9a 104.5a 4.9a Female (108) 77.8 52.2 39.0a 101.6a 4.9a The average RT from younger animals (I-0) 38.3 0 C is significantly (p < 0.05) lower compared to the RT of the older animals (I-1 to I-4). 3.4. Infestation of the internal parasites The results of the examination of 66 fecal samples from this study indicated that the most abundant gastrointestinal parasites were coccidia. All ages of goats had a high prevalence of coccidia between 57% to 100% (Table 7 ; Fig. 5 ) Table 7 Prevalence and mean of fecal egg count in dairy goat Breed Sex Age (year) n Prevalence (%) Mean epg/opg ± SD Nematode (Strongyle) Coccidia Nematoda (epg) Coccidia (opg) PE Female 1 7 0 (0/7) 85.7 (6/7) 0 914.3 ± 808.4 PE Female 2 24 0.04 (1/25) 91.6 (22/24) 1.67 ± 0.33 731.7 ± 544.3 PE Female 3 17 0 (0/7) 100 (17/17) 0 607.1 ± 559.3 PE Female 4–5 7 0.14 (1/7) 57.1 (4/7) 5.71 ± 2.16 177.1 ± 172.6 PE Female > 5 11 0 (0/11) 81.8 (9/11) 0 472.7 ± 673.6 Total 66 3.66 83.26 3.5. Milk production of the goats Figure 6 illustrates the trends in goat milk production across five different locations over a six-month lactation period. Each location exhibits varying production patterns, with some areas experiencing significant fluctuations from month to month. Figure 7 illustrates the trend of milk production across different Body Condition Scores (BCS) over a six-month lactation period. The data shows distinct patterns for each BCS category (2.5, 3, and 3.5), highlighting the relationship between body condition and milk yield. Based on the figure, it can be seen that BCS 2.5 exhibits a sharp decline in milk production after the third month. While the production remains stable at 626.7 ml in the second and third months, it drops significantly to 300.0 ml in the fourth month and remains at that level through the sixth month. This suggests that goats with a lower BCS may struggle to sustain milk production in the later lactation stages. Table 8 presents data on body weight and milk production of dairy goats based on factor of age, and lactation period. Milk production data is recorded from the 2nd to the 6th month of lactation. The age of the goats gives different milk production patterns between groups. Table 8 Dairy goat milk production in the 2nd, 3rd, 4th, 5th and 6th months according to breed, age and lactation period Variable Body weight (kg) Milk production (ml) 2nd month 3rd month 4th month 5th month 6th month Age (years) * * * ns * * 1–2 32.8b ± 6.1 1083.4a ± 110.0 944.6a ± 97.5 755.7 ± 178.7 592.8b ± 218.2 411.1b ± 191.7 3 38.9a ± 8.2 814.4b ± 179.1 721.1b ± 297.6 664.0 ± 303.7 519.7b ± 312.3 734.9a ± 302.4 4–5 42.6a ± 5.7 665.4b ± 211.8 770.9b ± 154.0 753.5 ± 155.0 918.8a ± 259.8 826.6a ± 394.9 Lactation Period * * * ns ns * 1 34.0b ± 6.7 931.1a ± 274.9 881.0a ± 165.4 773.1 ± 160.4 655.8 ± 279.8 511.6b ± 356.6 2–3 39.2ab ± 7.9 874.1a ± 206.8 768.8b ± 303.2 707.0 ± 299.3 630.7 ± 279.1 728.4ab ± 208.0 4–5 43.6a ± 4.7 578.1b ± 82.9 759.6b ± 41.1 711.6 ± 143.2 704.5 ± 428.3 808.0a ± 572.8 Notes : ns = Not significantly different in the same variables and columns, * = Significantly different (p < 0.05) in the same variable and column, a,b,c, = Different letters in the same variable and column indicate significant differences (p < 0.05) 3.6. The dynamic system of dairy goat sustainability The simulation results reveal that different intervention strategies significantly impact the sustainability of dairy goat farming. The analysis considered two policy intervention scenarios: moderate intervention starting in 2027 and optimistic intervention starting in 2029. Under the moderate intervention scenario, strategies focused on reproductive management and genetic improvement to enhance birth rates led to a steady increase in female dairy goat population and goat milk yield (Table 9 ). Table 9 Simulation results of dairy goat population and milk production growth under different intervention scenarios Intervention scenario Dairy Goat Population (heads) Annual Growth Rate (%) Goat Milk Production (tons/year) Annual Growth Rate (%) Moderate policy intervention Baseline 1,417 2.75 293.76 2.80 Scenario 1 1,567 3.88 321.45 3.86 Scenario 2 1,659 4.49 338.34 4.44 Scenario 3 1,865 5.67 375.67 5.57 Scenario 4 1,417 2.75 384.78 4.56 Scenario 5 1,865 5.67 501.79 7.11 Optimistic policy intervention Baseline 1,417 2.75 293.76 2.80 Scenario 1 1,666 4.72 338.63 4.63 Scenario 2 1,829 5.77 367.73 5.61 Scenario 3 2,266 7.93 444.06 7.64 Scenario 4 1,417 2.75 445.46 5.34 Scenario 5 2,266 7.93 703.10 9.65 The optimistic intervention scenario further strengthened these effects, demonstrating that comprehensive policy supports dairy goat sustainability. The integrated approach of reproductive, genetic, and nutritional improvements resulted in the highest increases in both female dairy goat population and goat milk production. The results indicate that Scenario 3 resulted in a population of 2,266 heads with an annual growth rate of 7.93% and milk production reaching 444.06 tons per year (7.64% growth). The most extensive intervention (Scenario 5) led to a remarkable surge, with the population reaching 2,266 heads and milk yield increasing to 703.10 tons per year and marking the highest growth rate of 9.65%. Figure 8 illustrates the trends in the female dairy goat population across different scenarios from 2023 to 2045. This result confirms that combining reproductive and genetic improvements yields a greater impact than applying these interventions separately. Moreover, optimistic policy intervention results in a higher increase in female dairy goat population compared to moderate intervention. Figure 9 presents the trends in goat milk production over the same period. These findings reinforce that integrating reproductive, genetic, and nutritional improvements is the most effective strategy for maximizing dairy goat sustainability in North Sumatra. Additionally, optimistic policy intervention leads to greater improvements in goat population and milk production than moderate intervention, reinforcing the need for strong policy support to achieve dairy goat sustainability in North Sumatra. 4. Discussion 4.1. Nutrition and feeding system A well-balanced diet with adequate energy and protein is essential to meet the nutritional requirements of goats for both maintenance and productivity. According to NRC ( 2007 ), the maintenance requirements for mature does weighing 40 kg are 0.53 kg/day of total digestible nutrients (TDN) and 67 g/day of crude protein (CP), with 20% undegradable intake protein (UIP). These requirements are increased during gestation and lactation. For example, during early gestation (single-kid pregnancy), energy and protein requirements increase to 0.61 kg/day of TDN and 98 g/day of CP. In late gestation, when body weight reaches 50 kg, the demands rise further to 0.89 kg/day of TDN and 166 g/day of CP to support fetal growth and metabolic changes. Furthermore, during early lactation (with a single kid and milk yield ranging from 0.88 to 1.61 kg/day), the doe requires 0.79 kg of TDN and 166 g/day of CP. By mid-lactation (milk yield of 0.63 to 1.15 kg/day), the energy requirement slightly decreases to 0.78 kg of TDN, while protein needs to drop to 150 g/day. In this study, farmers and households used various feed ingredients to meet their goats' nutritional requirements. The variabilities of feed ingredients depend on the availability of the surroundings and the most economical feed they can afford, since feed contributes approximately 80% of the total cost of livestock management. Maize, dried cassava, and soybean meal are high-energy feed sources in the diet (TDN > 80%), while soybean meal and cassava leaves, which contain crude protein levels above 16%, serve as important protein supplements to enhance goat growth and productivity. Row & Pethick (1994) explained that cereal grains such as barley, corn, oats, and sorghum provide substantial amounts of readily digestible carbohydrates. The findings of the present study on identified feed resources align with previous research by Duguma and Janssens ( 2016 ). Regardless of farm size, the majority (94.4%) of interviewed farmers relied on green feeds as the primary basal diet, particularly during the wet season. Overall, feed acquisition sources in the area in this study were a combination of on-farm production and purchased feed, with concentrates and agro-industrial by-products being primarily obtained through purchase. It seems that soybean and its derivatives are the most important ingredients that are available in the market. The fiber and energy sources can be obtained by growing around the areas; however, soybeans and their products mostly are still imported. 4.2. Morphometric measurements and body indices of the dairy goats Table 3 indicates that age significantly affects body weight and body measurements of female Etawah Grade goat, except for CC, EL, and EW. The age effect was particularly evident between 1PPI and 4PPI age groups, whereas no significant differences were observed 2PPI and 3PPI groups. A similar age effect on body weight and body measurement traits was reported in indigenous Ethiopian goat populations (Melesse et al., 2022), although, in that study, significant differences in BW and morphometric traits such as BL, HG, WH, RL, and RW were observed between the 2PPI and 3PPI groups. Body measurements of female Etawah Grade goats in this study exhibited low to high CV values (Table 3 ). The area index based on sex and age is significantly different, where male goats are significantly higher than that of female goats. The difference in area index is due to the body length and shoulder height of the goats which also differ according to sex. The area index based on age shows a significant increase according to the age of dairy goats, the smallest average area index is in goat I0 and the largest average is in goat I4. The similarity of the pattern between body size and area index is because the area index is a combination of two body measurements. According to Tiesnamurti et al ( 2023 ) Body measurement indices are relationships among body measurements used to describe the proportions and general size of the part of animals. In that study (Tiesnamurti et al., 2023 ) also found the area index of male goats was larger than that of female goats, while based on age there was no significant difference. Length Index or also called relative body index (Chacón et al., 2011 ) in this study obtained an average value of 0.91 which is lower than several previous studies (Chacón et al., 2011 ; Khargharia et al., 2015 ; Dea et al., 2020 ; Getaneh et al., 2022 ; Saleh et al., 2022 ; Tiesnamurti et al., 2023 ; Dinesh et al., 2024 ), length index based on age and sex obtained by Tiesnamurti et al (Tiesnamurti et al., 2023 ) is also higher than dairy goats in this study. The area index of dairy goats in North Sumatra in this study was higher than that of Assam goats (Khargharia et al., 2015 ) and South Ethiopian native goats (Dea et al., 2020 ), lower PE goats (Tiesnamurti et al., 2023 ), several Chinese native goats (Saleh et al., 2022 ), and several Ethiopian native goats (Getaneh et al., 2022 ). The average depth index in this study showed a lower value than previous studies (Chacón et al., 2011 ; Khargharia et al., 2015 ; Dea et al., 2020 ; Saleh et al., 2022 ; Dinesh et al., 2024 ). The height slope and body ratio values ​​in this study were lower than Assam hill goat (Khargharia et al., 2015 ), Ethiopian native goat (Dea et al., 2020 ) and the body ratio was lower than Kothdar goat (Dinesh et al., 2024 ) and Several Chinese Goat (Saleh et al., 2022 ), while the body ratio of Cuban Creole goat was lower than this study (Chacón et al., 2011 ; Tiesnamurti et al., 2023 ). The proportionality index in this study was higher than previous studies on other goat breeds (Chacón et al., 2011 ; Khargharia et al., 2015 ; Dea et al., 2020 ; Getaneh et al., 2022 ; Saleh et al., 2022 ; Dinesh et al., 2024 ). Body index describes goats as long, medium, or short bodied. According to Khargaria et al (Khargharia et al., 2015 ), if the body index value is above 90, it is long bodied, 86–89 is medium category, and less than 85 is short bodied category. The overall average body index of dairy goats in this study showed that the goats were included in the short-bodied category, as well as goats grouped by breed, sex, and age. The average body index in this study was lower than the body index values ​​of several goats used in previous studies (Chacón et al., 2011 ; Khargharia et al., 2015 ; Dea et al., 2020 ; Getaneh et al., 2022 ; Saleh et al., 2022 ; Tiesnamurti et al., 2023 ; Dinesh et al., 2024 ). The pelvic index in this study was on average, higher than studies on several other goats in literature (Chacón et al., 2011 ; Khargharia et al., 2015 ; Dea et al., 2020 ; Getaneh et al., 2022 ; Saleh et al., 2022 ; Tiesnamurti et al., 2023 ; Dinesh et al., 2024 ). The high pelvic index value indicates a wider pelvic width dimension compared to previous studies. 4.3. Physiological response and the adaptation coefficient The average HR, RR, and RT from this study were in accordance with to study reported by Yuneriaty et al. (2022) for pregnant Kacang goats observed in Kupang, East Nusa Tenggara province, Indonesia. Ivanova et al (2023) reported that the average rectal temperature, respiration rate, and heart rate of the Bulgarian white dairy goat breed in South Bulgaria were 39.02 ± 0.15 0 C; 34.5 ± 1.28 beats/min and 87.88 ± 1.19 time/min, respectively. The rectal temperature did not differ during winter and summer; however, pulse/heart rate and respiration rate sharply increased in summer compared to winter. The THI increased along the seasonal changes from winter (11.2–12.5) to summer (32.8–33.3). Dias et al (2022) reported the average rectal temperature, respiration rate, and heart rate for adult Alpain male goats during summer were 38.05 ± 0.06 0 C; 38.50 ± 6.05 mov min -1 and 74.86 ± 3.65 beat min -1 , respectively. The average rectal temperature did not differ significantly during winter, spring, and autumn; however, the respiration rate significantly differed significantly, which is higher in summer 38.50 ± 6.05 mov min-1 compared to winter 23.36 ± 2.04 mov min-1. However, the heart rate did not differ significantly during the four seasons. Omar et al (2025) reported that Saanen does kept at different barn types, wooden and galvanized in Malaysia, showed that RR and HR were significantly (P < 0.05) affected by the housing system; however, RT remained unaffected. The average rectal temperature, respiration rate, and heart rate were 39.4 ± 0.02 0C; 61.9 ± 1.68 breath/min and 94.8 ± 1.38 beats/min of Saanen does kept at different barn types. Nonetheless, Srivastava et al. (2021) reported that THI influences RT and RR in small ruminants. THI was influenced significantly by the ambient temperature and relative humidity in the area, in different climatic zones, which were distributed according to the classification of Habeeb et al. ( 2018 ). The THI classification aims to evaluate the intensity of heat stress according to the following categories such as ‘no effect’ (THI < 70); ‘low’ (70 ≤ THI < 75); ‘moderate’ (75 ≤ THI < 78), and ‘extreme’ (THI ≥ 78), respectively. Indonesia is classified as a tropical humid country with average temperature and humidity relatively high, which will cause a high THI. Our study showed that average ambient temperature was a bit higher in some months from the temperature tolerance of goats (6–27°C), the average ambient temperature at midday and the humidity in the morning were a bit higher than the temperature tolerance of goats, and the comfortable humidity, which is 60–80% (Sejian et al 2021 ), and still at the normal range of comfortable temperature for tropical goat, which is in between 20 0 C and 30°C (Borges and Rocha, 2018). 4.4. Infestation of the gastrointestinal parasites All goats were fed elephant grass/Napier grass ( Pennisetum purpureum cv mott ) that came from the same source and without any treatment before being given to the goat. All animals sampled were clinically healthy and had no signs of disease. The prevalence rate of Gastrointestinal (GI) parasitism (Table 7 ), especially coccidia in all goats, was relatively high at all ages (57–100%), while the prevalence rate of nematodes was very low and tended to zero. According to Hassanen et al. ( 2020 ), Eimeria spp . infections are one of the most economically significant diseases of sheep and goats. Radostits, Blood, and Gay (1994) showed that some Eimeria species exhibited clinical symptoms such as diarrhea, poor weight gain, a rough coat, weakness, and decreased production, but coccidiosis in sheep and goats is usually asymptomatic/subclinical. Furthermore, subclinical individuals serve as carriers, contaminating the environment by excreting the oocysts in their feces without exhibiting clinical symptoms (Chartier and Paraud 2012 ). Coccidiosis causes acute and chronic gastrointestinal damage and increases the risk of secondary infections (Seddik et al. 2022 ). Coccidia infestations can result in health problems ranging from significant weight loss or impaired growth (in older animals) to animal death (in young animals) (Gondipon and Malaka 2021). Sixty-six goats were infected by coccidia; there were 7 goat kids aged 1 year, and the remaining 59 goats were adults aged between 2 to > 5 years (Table 9 ). This is despite previous reports that young ruminants have a higher susceptibility to Eimeriosis than adults (Abdelaziz et al. 2021 ; El-Alfy et al. 2020 ). According to our findings, adult and young goats are equally susceptible to acquiring the infection since they are exposed to the same stressors, such as intense rearing in small-scale pens with grass feed and water sources from the same location. In addition, this happens because the goats are often kept in damp conditions and lack sunlight. Haile ( 2018 ) stated that the significance of these diseases in restricted herds is highlighted by the fact that the infections are more common and more severe in animals raised in intensive systems. According to Urguhart et al. ( 1996 ), the incidence of the disease in sheep and goats is significantly influenced by rearing stressor conditions, including weaning, transportation or relocation to a new pen, starvation, overcrowding, and unfavorable weather. A young goat at one year old had the largest number of oocytes per gram of feces (914 opg) and was classified as a moderate infestation. The average opg for goat older than one year to five years is decreasing between 177 and 731, and they are classified as mild infestation. Coccidiosis typically manifests clinically in young animals rather than adults because they have developed immunity from prior infections (Olmos et al. 2020). The severity of strongyle/coccidia infection was reported based on egg/oocyst count according to Urguhart et al. ( 1996 ) as mild (50–799epg/opg), moderate (800–1200epg/opg), or severe (> 200epg/opg). The fact that subclinical coccidiosis affects more animals and might result in serious long-term intestinal health impairment makes it especially noteworthy since it is believed to produce higher output losses than its clinical equivalent (Razavi et al. 2024). Although the number of oocysts per gram of feces is classified as low to moderate, this still needs attention in maintenance management so that infestation does not get higher and can cause health problems and decreased productivity. In order to identify particular risk variables that significantly impact the occurrence and severity of the clinical presentation, further study is necessary to develop an effective control plan for gastrointestinal parasite disorders. 4.5. Milk production of the dairy goats Figure 6 highlights that goat milk production is significantly influenced by location, with some areas maintaining stable yields while others experience notable fluctuations. Factors such as environmental conditions (Laouadi et al., 2018; Mena et al., 2024), feed availability and quality (Mburu et al., 2014; Mena et al., 2024), and management practices such as breeding strategies (Laouadi et al., 2018; Sow et al., 2021) and economic strategies (Mena et al., 2024) likely play a crucial role in these differences. Locations like Namorambe and Percut Sei Tuan tend to have higher and more stable production, suggesting that conditions in these areas are more favorable for milk production. Deli Tua, STM Hilir, and Simalingkar exhibit more fluctuating and generally declining production trends, which may be affected by less optimal environmental conditions or limitations in farm management. The data suggests a strong correlation between BCS and lactation performance. Goats with a lower BCS (2.5) experience a sharp drop in milk yield, indicating that insufficient body reserves may limit milk production, particularly in mid to late lactation. Goats with moderate BCS (3) maintain relatively stable production but show a gradual decline, suggesting that while they have enough energy reserves, they may still experience a natural decrease in milk yield over time. Goats with a higher BCS (3.5) demonstrate a delayed peak and sustained increase in production, indicating that better body reserves can support prolonged lactation and higher yields in later months. These findings emphasize the importance of nutritional management in maintaining optimal body condition throughout lactation. Ensuring that goats achieve a BCS of 3.5 before and during lactation could contribute to higher and more sustained milk production, while goats with BCS 2.5 may require improved feeding strategies to prevent early declines in yield. The correlation between body condition score (BCS) and goat lactation performance is significant, as BCS serves as an indicator of energy reserves that directly influence milk production. Research indicates that BCS impacts various aspects of lactation, including milk yield and quality, which are crucial for optimizing dairy goat productivity. Higher BCS is associated with increased milk production, as it reflects better energy reserves and overall health of the goats (Gafsi et al., 2024). In a study, multiparous goats with higher BCS showed improved milk yield and composition, indicating that maintaining optimal BCS is essential for lactation performance (Ribeiro et al., 2023). 4.6. The dynamic system of dairy goat sustainability The findings of this study highlight the critical role of targeted interventions in ensuring the sustainability of dairy goat farming. The results demonstrate that improvements in reproductive management, genetic selection, and feeding strategies contribute significantly to female dairy goat population growth and goat milk production. These findings align with previous studies indicating that genetic improvement programs for goats have been reported to enhance meat and milk production (Sousa et al., 2011 ). Furthermore, achieving sustainable dairy goat farming requires a well-designed breeding program (Bett et al., 2009 ; Escareño et al., 2012 ). Reproductive efficiency in dairy goats through Multiple Ovulation and Embryo Transfer (MOET), estrus synchronization (ES), and artificial insemination (AI) has been shown to improve genetic quality and milk production (Luo et al., 2019 ). Lianou et al. (2022) also reported that improving reproductive performance in dairy does can enhance milk yield and litter size, while Ruvuga and Maleko ( 2023 ) found that superior dairy goat breeds contribute to improved lactation performance and milk production. The effectiveness of the combined intervention strategies (Scenario 5) suggests that a holistic approach is necessary to maximize dairy goat sustainability. The observed increase in population and milk production under this scenario supports the notion that integrating reproductive, genetic, and nutritional strategies leads to synergistic benefits. Similar findings have been reported in studies on dairy goats, where improved reproductive performance combined with the implementation of breeding strategies to enhance genetic quality has been shown to promote increased goat production (Upadhyay et al., 2024 ; Zewdie and Welday, 2015 ). Furthermore, Castañeda-Bustos et al. ( 2014 ) emphasized the importance of selecting genetic parameters for reproduction and milk production in dairy goats. Moreover, dietary improvements have been reported to enhance milk yield and overall productivity (Zamuner et al., 2023 ; Zazharska et al., 2016 ) as well as milk quality (Yin et al., 2024 ) in dairy goats. The comparison between moderate and optimistic policy interventions further underscores the importance of early and comprehensive policy support. The more pronounced growth under optimistic intervention suggests that stronger policy measures implemented earlier can accelerate the development of the dairy goat sector. This finding aligns with previous research, which indicated that integrating government policies, management, and market mechanisms supports the sustainable development of dairy goat farming (Miller and Lu, 2019 ). Furthermore, in South America, Brazil has developed its dairy goat industry by providing government assistance to small-scale goat farmers (Lu and Miller, 2019 ). Similarly, goat farms in Greece have been reported to remain viable due to government subsidies (Tsiouni et al., 2021 ). Moreover, the trends observed in Figs. 2 and 3 reinforce the results presented in the tables, demonstrating that Scenario 3 and Scenario 5 have the most substantial impact on population and milk production, respectively. The greater divergence of these scenarios from the baseline indicates their potential to drive long-term sustainability in dairy goat farming. Previous studies have highlighted that an increase in genetic quality, reproduction, and nutrition directly correlates with enhanced goat milk yield (Lianou et al., 2022; Ruvuga and Maleko, 2023 ; Sousa et al., 2011 ). Despite these findings, some limitations should be acknowledged. The study relies on simulation-based modelling, which may not fully capture real-world complexities such as disease outbreaks, market fluctuations, or climate change effects. Future research should incorporate more comprehensive modelling approaches, including stochastic simulations, to enhance the robustness of predictions. However, this study provides strong evidence that integrating reproductive, genetic, and nutritional improvements, supported by proactive policy measures, is the most effective strategy for ensuring the sustainability of dairy goat farming. 5. Conclusion The development of dairy goat farming throughout the country can be replicated based on a similar environment, based on the results of this study. Etawa crossbred did not experience heat stress in the intensive management system and can perform their milk production until about five years old. Even though goats were intensively kept at all times, infestation of internal parasites was observed; therefore, a protocol to monitor the gastrointestinal infestation should be anticipated. The sustainable development of dairy goats through the intervention of reproductive management, genetic improvement, and feeding strategies contributes significantly to the growth of the dairy goat population as well as their milk production. Declarations Ethical approval The ethical clearance was granted by the Indonesian Centre for Animal Research and Development, Indonesian Agency for Agricultural Research and Development, Ministry of Agriculture, to the Indonesian Research Institute for Goats, number: Balitbangtan/ Lolitkambing/Rm/02/2021. Credit Authorship/ Contribution Statement Bess Tiesnamurti: conceptual, writing, review, editing, validation, investigation, data analysis, supervision Santoso : validation, review, investigation Peni Wahyu Prihandini : validation, review, investigation Gresy Eva Tresia: conceptual, writing, review, editing, visualization, data analysis Alfian Destomo : writing, review, editing, data Analysis Alwiyah: data resources, investigation Anwar: data resources, investigation Arie Febretesiana: data resources, investigation Yeni Widiawati : supervision, editing, validation Alek Ibrahim : data analysis, writing, editing Dyah Haryuningtyas Sawitri : conceptual, writing, review, editing, visualization, data analysis Priyono : writing, review, editing, and data analysis Eko Handiwirawan: conceptualization, writing, review, editing, resources, investigation, data analysis, validation, investigation, supervision Mohammad Ikhsan Shiddieqy: writing, review, editing Endang Romjali: writing, review, investigation, validation, supervision Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Funding This work was supported by the Indonesian Centre for Animal Research and Development, Ministry of Agriculture (Fiscal Year 2021). M.I. Shiddieqy received funding from Indonesian Endowment Fund for Education (LPDP) for his study. Acknowledgement We appreciate the Indonesian Centre for Animal Research and Development. Ministry of Agriculture and the Indonesian Endowment Fund for Education (LPDP). The authors wish to appreciate the Local Livestock Services and farmers for their willingness to participate in this study. Data availability Data will be made available on reasonable request. References Abdelaziz, A. R., A. Gareh, E. K. Elmahallawy, R. A. Elmaghanawy, E. I. El Tokhy, and S. S. Sorour. 2021. Prevalence and Associated Risk Factors of Eimeria spp. Infection in Goats in Northern and Southern Egypt. Euro. J. Zool. Res. 9(5):30–37. Abdurrahman, M., A. Atabany, B.P. Purwanto, and A. Anggraeni. 2023. Studi Perbedaan Fenotipe Kambing Perah Berdasarkan Analisis Canonikal. J. 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Yamani HA and Koluman N. Impact Change Climate on the Milk Production in the Dairy Goats. Int J Zoo Animal Biol 2020, 3(3): 000228.DOI: 10.23880/izab-16000228 Yilmaz Tilki, H., and M. Keskin. 2021. Relationships between different body characteristics and milk yield traits in Kilis goats. Mustafa Kemal Üniversitesi Tarım Bilim. Derg. 26(2):272–277. Yin, Q., Yu, J., Li, J., Zhang, T., Wang, T., Zhu, Y., Zhang, J., Yao, J., 2024. Enhancing milk quality and modulating rectal microbiota of dairy goats in starch-rich diet: the role of bile acid supplementation. J Anim Sci Biotechnol 15, 7. https://doi.org/10.1186/s40104-023-00957-7 Zalewski, A. 2007. Does size dimorphism reduce competition between sexes? The diet of male and female pine martens at local and wider geographical scales. Acta Theriol. (Warsz). 52(3):237–250. Zamuner, F., Leury, B.J., DiGiacomo, K., 2023. Review: Feeding strategies for rearing replacement dairy goats – from birth to kidding. animal 17, 100853. https://doi.org/10.1016/j.animal.2023.100853 Zazharska, N., Boyko, O., Brygadyrenko, V., 2016. Influence of diet on the productivity and characteristics of goat milk. Indian J Anim Res. https://doi.org/10.18805/ijar.v0iOF.6826 Zewdie, B., Welday, K., 2015. Reproductive Performance and Breeding Strategies for Genetic Improvement of Goat in Ethiopia: A Review. Greener Journal of Agricultural Sciences 5, 023–033. https://doi.org/10.15580/GJAS.2015.1.080614317 Zhang, F., X. Cui, S. Wang, H. Sun, J. Wang, X. Wang, S. Fu, and Z. Guo. 2022a. Analysis of Kinematic Characteristics of Saanen Goat Spine under Multi-Slope. Biomimetics 7(4). Zhang, X. xin, Z. gao An, K. feng Niu, C. Chen, T. zhu Ye, A. Shaukatc, and L. guo Yang. 2022b. Evaluation of type traits in relation to production, and their importance in early selection for milk performance in dairy buffaloes. Animal 16(11):100653. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8839115","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":596782808,"identity":"6717d9e7-303a-4e41-8d92-2ddcddc1b247","order_by":0,"name":"Bess Tiesnamurti","email":"","orcid":"","institution":"Badan Riset dan Inovasi Nasional, Indonesia","correspondingAuthor":false,"prefix":"","firstName":"Bess","middleName":"","lastName":"Tiesnamurti","suffix":""},{"id":596782809,"identity":"6963f29d-39c6-477f-bbb3-484b174b2fd4","order_by":1,"name":"Santoso Santoso","email":"","orcid":"","institution":"Badan Riset dan Inovasi Nasional, Indonesia","correspondingAuthor":false,"prefix":"","firstName":"Santoso","middleName":"","lastName":"Santoso","suffix":""},{"id":596782810,"identity":"353db4e7-719b-4960-ae07-adda5e057091","order_by":2,"name":"Peni Wahyu Prihandini","email":"","orcid":"","institution":"Badan Riset dan Inovasi Nasional, Indonesia","correspondingAuthor":false,"prefix":"","firstName":"Peni","middleName":"Wahyu","lastName":"Prihandini","suffix":""},{"id":596782811,"identity":"0419d03e-61e6-4358-96d1-86b940a18000","order_by":3,"name":"Gresy Eva Tresia","email":"","orcid":"","institution":"Badan Riset dan Inovasi Nasional, Indonesia","correspondingAuthor":false,"prefix":"","firstName":"Gresy","middleName":"Eva","lastName":"Tresia","suffix":""},{"id":596782812,"identity":"b0d51175-c69b-420a-a5d1-ac22e3f105ec","order_by":4,"name":"Alfian Destomo","email":"","orcid":"","institution":"Badan Riset dan Inovasi Nasional, Indonesia","correspondingAuthor":false,"prefix":"","firstName":"Alfian","middleName":"","lastName":"Destomo","suffix":""},{"id":596782813,"identity":"a89b265c-5e45-4adb-8490-d75abb88d669","order_by":5,"name":"Alwiyah Alwiyah","email":"","orcid":"","institution":"Kementerian Pertanian Republik Indonesia","correspondingAuthor":false,"prefix":"","firstName":"Alwiyah","middleName":"","lastName":"Alwiyah","suffix":""},{"id":596782814,"identity":"b888761b-28f4-4250-9fc2-9de395ced5a4","order_by":6,"name":"Anwar Anwar","email":"","orcid":"","institution":"Kementerian Pertanian Republik Indonesia","correspondingAuthor":false,"prefix":"","firstName":"Anwar","middleName":"","lastName":"Anwar","suffix":""},{"id":596782815,"identity":"2f12033a-cfab-42a4-97ed-d0dd711799f0","order_by":7,"name":"Arie Febretrisiana","email":"","orcid":"","institution":"Kementerian Pertanian Republik 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Indonesia","correspondingAuthor":false,"prefix":"","firstName":"Dyah","middleName":"Haryuningtyas","lastName":"Sawitri","suffix":""},{"id":596782819,"identity":"f7f91b81-1806-4864-bacc-6dd281d2fb42","order_by":11,"name":"Priyono Priyono","email":"","orcid":"","institution":"Badan Riset dan Inovasi Nasional, Indonesia","correspondingAuthor":false,"prefix":"","firstName":"Priyono","middleName":"","lastName":"Priyono","suffix":""},{"id":596782820,"identity":"2b50f527-ad39-4322-905b-94115e9fd8c6","order_by":12,"name":"Eko Handiwirawan","email":"","orcid":"","institution":"Badan Riset dan Inovasi Nasional, Indonesia","correspondingAuthor":false,"prefix":"","firstName":"Eko","middleName":"","lastName":"Handiwirawan","suffix":""},{"id":596782821,"identity":"58d1cd3f-b771-415c-8e48-a033bc92e4e6","order_by":13,"name":"Mohammad Ikhsan Shiddieqy","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABDElEQVRIiWNgGAWjYFACHjDJ2MbAwMaQwMYM4jI+AIuxE9DSh6SF2QAsxkxAyzyQFgY2sDI2CXxadNt7D366mWMn28bA/uzBgzJrGX72HLNq3rZ7DOY4tJidOZcsnbst2biNgcfcIOFcOo9kzxuz27xtxQyWzTi03MgxAGphTgRqYZNIbDvMY3Ajx+x2blsCg8FhnFqMf+duq08EOQysxR6opZiAFjOgLYeBWhjMILZI5Jgx49Vy5oyZde6248ZtzDxmEiC/SJx5Viz951wCD04tx3uMb+duq5ad397+TPJHmbU9f3vyxo8zyhLkDI43YNcDB4ggzQDHJA8B9Sgg/QEpqkfBKBgFo2D4AwDoSVgS9d9vbQAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0002-9582-148X","institution":"Wageningen UR: Wageningen University \u0026 Research","correspondingAuthor":true,"prefix":"","firstName":"Mohammad","middleName":"Ikhsan","lastName":"Shiddieqy","suffix":""},{"id":596782822,"identity":"357d1d06-e5f4-4c9f-ac1b-a1353795b237","order_by":14,"name":"Endang Romjali","email":"","orcid":"","institution":"Badan Riset dan Inovasi Nasional, Indonesia","correspondingAuthor":false,"prefix":"","firstName":"Endang","middleName":"","lastName":"Romjali","suffix":""}],"badges":[],"createdAt":"2026-02-10 09:36:31","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8839115/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8839115/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104399154,"identity":"481f9746-5109-4b71-b4b9-a3f186c18097","added_by":"auto","created_at":"2026-03-11 12:04:53","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":106772,"visible":true,"origin":"","legend":"\u003cp\u003eDistrict of Deli Serdang (red) in North Sumatra Province (yellow)\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-8839115/v1/c5814d61befb3ddc425729a3.png"},{"id":103623658,"identity":"36ef6b07-f5a8-4d4d-9182-581b350abfec","added_by":"auto","created_at":"2026-02-27 19:21:57","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":329626,"visible":true,"origin":"","legend":"\u003cp\u003eThe Morphometric measurements of the dairy goat (Tiesnamurti et al., 2023)\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-8839115/v1/3fa94199232cb75581258ed1.png"},{"id":103623656,"identity":"cdbd126a-772b-45a0-bbfe-b0d49cf7915f","added_by":"auto","created_at":"2026-02-27 19:21:57","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":157653,"visible":true,"origin":"","legend":"\u003cp\u003eThe sustainability model for population dynamics in dairy goat farming\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-8839115/v1/bc3bd664e8de1c29fc43d076.png"},{"id":103623659,"identity":"29f93499-47b6-4bae-ac39-779561ea817d","added_by":"auto","created_at":"2026-02-27 19:21:58","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":79328,"visible":true,"origin":"","legend":"\u003cp\u003eThe Average Ambient Temperature, Humidity, and Temperature Humidity Index in 2021\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-8839115/v1/4649fbb84c9d7a94265dc9ab.png"},{"id":103623662,"identity":"5a3c9ce8-b881-44ee-8264-5df2341513b9","added_by":"auto","created_at":"2026-02-27 19:21:59","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":40667,"visible":true,"origin":"","legend":"\u003cp\u003eAverage fecal oocyte count according to the age of goats\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-8839115/v1/d38db9045b87443961eeb472.png"},{"id":104399590,"identity":"34b6e5ee-aa62-4174-871f-eaab4ffa3f98","added_by":"auto","created_at":"2026-03-11 12:06:44","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":25655,"visible":true,"origin":"","legend":"\u003cp\u003eDairy goat milk production graph by location (sub-district)\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-8839115/v1/13b0b86b45a930cae5198e2c.png"},{"id":103623655,"identity":"4f3118a9-ac35-4dd9-97c2-a5c97c01a0df","added_by":"auto","created_at":"2026-02-27 19:21:57","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":18489,"visible":true,"origin":"","legend":"\u003cp\u003eDairy goat milk production graph by body condition score (BCS)\u003c/p\u003e","description":"","filename":"image7.png","url":"https://assets-eu.researchsquare.com/files/rs-8839115/v1/329ba4f1be5cb14885dae4da.png"},{"id":103623663,"identity":"589a6876-ea12-4f5e-bc8a-f7b4eaa83044","added_by":"auto","created_at":"2026-02-27 19:21:59","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":89481,"visible":true,"origin":"","legend":"\u003cp\u003eProjected female dairy goat population under different intervention scenarios from 2023 to 2045\u003c/p\u003e","description":"","filename":"image8.png","url":"https://assets-eu.researchsquare.com/files/rs-8839115/v1/eda6dc0225663fbe256cb7f6.png"},{"id":103623660,"identity":"0da81aae-2274-486a-9d1a-02d8a4417b28","added_by":"auto","created_at":"2026-02-27 19:21:58","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":106548,"visible":true,"origin":"","legend":"\u003cp\u003eProjected goat milk production under different intervention scenarios from 2023 to 2045\u003c/p\u003e","description":"","filename":"image9.png","url":"https://assets-eu.researchsquare.com/files/rs-8839115/v1/5717da8f3d4831b27ada6b84.png"},{"id":109569104,"identity":"83bdeb00-00f1-459e-a7a3-83bd4fe7eb97","added_by":"auto","created_at":"2026-05-19 15:46:29","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1820722,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8839115/v1/0db6ced3-524b-4ba3-ad98-4e2f4f364979.pdf"}],"financialInterests":"","formattedTitle":"Morphometrics measurement, physiology traits and parasites infestation of dairy goats farms in North Sumatra, Indonesia: Challenges for the environmental sustainability of milk production","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eIndonesia is an archipelago with an estimated 275.773\u0026nbsp;million human population and requires a continuous supply of animal-based protein such as milk, meat, and eggs. The dairy cattle population is 507,075 head and produced 837.2 thousand tons of milk in 2023, when compared to 2019, milk production decreased by 12.90 percent ((Ministry of Agriculture, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe national milk demand is about 4.19\u0026nbsp;million tons, and 81% is still imported, therefore, the substitution with dairy goat milk is probably a solution to meet the national milk demand. BPS (2023) reported that the average National milk demand increases by approximately 6% per year, however, milk production grows only 1% per year. The national milk consumption is considered low, approximately 16.27 kg per capita per year, with a national milk production of 997,000 tons from the national demand of 4.3\u0026nbsp;million tons (BPS, 2023).\u003c/p\u003e \u003cp\u003eThe majority of dairy goat breeds in the country are Etawah crossbred (PE), even though other breeds are available, such as Saanen, Anglo-Nubian, and their crosses, respectively. PE goats are mostly similar to Jamnapari goats of India, imported around the 19th century. Indonesia's estimated dairy goat population is probably around 1% of the national goat population of 18.560.835 head (Ministry of Agriculture, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The total milk production of the Etawah cross, Saanen and Etawah cross, Anglo Nubian, and Senduro breeds in Indonesia was 154.3, 264.6, 214.2, and 196.6 L/lactation, respectively (Soemarmono, 2022). The distribution of dairy goats spread over the country, presumably found in 21 out of 34 provinces in Indonesia.\u003c/p\u003e \u003cp\u003e The linear measurement of animals is an important parameter in investigating growth rate according to age and the nutritional status given to the animals. Earlier study showed, that heart girth was the best indicator for differentiating goats with a history of multiple and single litter size in goats (Haldar et al., 2014), whereas body morphology is closely related to milk performance (Gulinski et al., 2005) and longevity, which determines the contributions to lifetime milk production of a dairy animal (Sawa et al., 2013).\u003c/p\u003e \u003cp\u003eHeart rate (HR), respiration rate (RR), and rectal temperature (RT) are expressions of the metabolic process of the animal and depend largely on the ambient temperature where goats are raised. The temperature-humidity index (THI) has been widely used to estimate the degree of thermal stress that livestock experience. The infestation of internal parasites in small ruminants occurs either through grazing management or also carrying away the eggs on the forages given to the animal, through a cut-and-carry system. Gastrointestinal parasite infection, including nematode (\u003cem\u003eStrongyles\u003c/em\u003e) and protozoa (\u003cem\u003eCoccidia\u003c/em\u003e), is a major hindrance which have a significant impact on the development of goat production in many parts of the world (Maurizio, di Regalbono, and Cassini, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In Indonesia, the average milk production of PE goat fed with 11% crude protein was 661.11- 892.22 mL day\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (Chintyadhevi Aulia Rahmi, Nenny Harijani, Suwarno Suwarno, Mohammad Anam Al Arif, Budiarto Budiarto, and Sunaryo Hadi Warsito 2021).\u003c/p\u003e \u003cp\u003ePrevious studies have highlighted morphometric and physiological measurements of dairy goat, but have rarely explored the dynamic interplay between population growth, milk production, and economic factors in dairy goat production systems. The system dynamics (SD) modeling offers a powerful tool to address the complexity of sustainability in dairy goat farming. SD is particularly effective in analyzing interconnected subsystems and feedback loops for evaluating long-term strategies (Sterman, \u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). Previous studies have applied SD models to various aspects of dairy farming, such as dairy cattle population dynamics, milk production, and feed management (Lie et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2018\u003c/span\u003e); dairy cattle population and milk supply-demand dynamics (Susanty et al., \u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e2019\u003c/span\u003e); and dairy goat production systems (Guimar\u0026atilde;es et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Furthermore, SD has been employed in the context of dairy supply chain systems (Azizsafaei et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) and technology adoption within dairy supply chains (Sim\u0026otilde;es et al., \u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis field study was meant to investigate the factors contributing to dairy goats' productivity that may influence their sustainability. Therefore, it is significant to explore more research on the morphometry, physiology, nutrition status, and external parasites on the dairy goats raised by smallholder farmers in the Deli Serdang District of North Sumatra province, which have not been extensively studied. This study has not been reported elsewhere, especially in conjunction with dairy goat sustainability.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Study area and animals\u003c/h2\u003e \u003cp\u003eThis study was undertaken on 24 dairy goat farmers with a total of 172 heads in nine sub-districts of Percut Sei Tuan, Sinembah Tanjung Muda Hilir, Deli Tua, Namorambe, Simalingkar, Kutalimbaru, Pancur Batu, Bangun Purba, and Sunggal, districts of Deli Serdang located on the East Coast of North Sumatra Province, Indonesia (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Goats were kept intensively at all times, with a group of three does per pen. Each observation used a different number of animals, depending on the substance of the study and the availability of the animals.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Nutrition and the feeding system\u003c/h2\u003e \u003cp\u003eIn nutrition and feeding system study, farmers were voluntary participated in the survey. The study objectives and procedures were explained to all participants, and informed consent was obtained prior to the interviews. Consent was collected either in written form or verbally, depending on participants\u0026rsquo; preference and feasibility in the field setting. No minors were involved in this study. A total of 24 randomly selected dairy farmers were interviewed using a pre-tested structured questionnaire and through direct observations. The respondents were farmers from nine sub-districts. The randomly selected farms were stratified into three groups based on the number of dairy goats owned: small farms owning 1\u0026ndash;20 does (8 farms), medium farms with 21\u0026ndash;40 animals (8 farms), and large farms with more than 40 animals (8 farms). A single-visit-multiple-subjects formal survey technique (ILCA, 1990) was used to collect data through household interviews. The data collected included: conventional and non-conventional feed resources, feeding practices/systems, and sources of feed acquisition. Feed samples were collected for proximate analysis following AOAC (2005) procedures.\u003c/p\u003e \u003cp\u003eFeeding management was performed with a cut-and-carry system, offered twice a day, in the morning around 07:00 and at 17:00, and water was provided \u003cem\u003ead libitum\u003c/em\u003e. Various \u003cem\u003eagricultural by-products\u003c/em\u003e and grasses were given to the goats, approximately 5 kg head\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e day\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The barn was cleaned daily before the doe was milked. Animal health was controlled by a veterinarian if there was a report from the owner, otherwise, all was handled by the farmer. Animals were offered roughage of different sources and agricultural by-products according to the season and availability.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Morphometric measurements and body indices\u003c/h2\u003e \u003cp\u003eBody weight (BW) and morphometric measurements were recorded from a total of 110 female Etawah Grade goats. The body measurements included body length (BL), withers height (WH), chest girth (CG), chest depth (CD), chest width (CW), rump height (RH), rump width (RW), cannon circumference (CC), head length (HL), head width (HW), ear length (EL), ear width (EW), teat perimeter (TP), and teat length (TL). Body weight was measured using a digital livestock scale, while body dimensions were obtained using measuring sticks and tape, following the standard procedures outlined by the Food and Agriculture Organization ((FAO, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), as described in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Physiological response and the adaptation coefficient\u003c/h2\u003e \u003cp\u003eThe physiological response, including respiration rate (RR), heart rate (HR), and rectal temperature (RT), was measured from 112 heads of PE of different ages belonging to 4 farmers. RR was measured by counting the flank movement (time per minute), HR was measured by palpating the pulse rate (time per minute), and RT was measured by inserting a thermometer into the rectum for one minute (\u0026deg;C). Measurements were conducted individually in October 2021, in the morning around 08:00 am, inside the barn. Data on micro-climate (ambient temperature and humidity) were derived from the local meteorological office. The temperature and humidity index (THI), index Benezra (HTC), and the adaptation coefficient (AC) were calculated according to the following formula:\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTHI\u0026thinsp;=\u0026thinsp;0.8 \u0026times; T + (H/100)\u0026times; (T\u0026thinsp;\u0026minus;\u0026thinsp;14.4)\u0026thinsp;+\u0026thinsp;46.4\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKitajami et al., (2021)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHTC\u0026thinsp;=\u0026thinsp;100 - [18 x (RT\u0026thinsp;\u0026minus;\u0026thinsp;38.60)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAraujo \u003cem\u003eet al\u003c/em\u003e., (2017)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAC\u0026thinsp;=\u0026thinsp;RT/39.1\u0026thinsp;\u0026plusmn;\u0026thinsp;RR/19\u0026thinsp;\u0026plusmn;\u0026thinsp;HR/75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAraujo \u003cem\u003eet al\u003c/em\u003e., (2017) and Habeeb et al., (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2018\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003eNote: T=local temperature (\u003csup\u003eo\u003c/sup\u003eC), H\u0026thinsp;=\u0026thinsp;air humidity (%), RT=rectal temperature (\u003csup\u003e0\u003c/sup\u003eC), RR=respiration rate (time per minute), HR=heart rate (time per minute)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Infestation of internal parasites\u003c/h2\u003e \u003cp\u003eFecal samples from 66 goats belong to five farmers from Percut Sei Tuan district, were taken directly from the rectum of each animal using disposable gloves and then placed in sterile plastic. The sampling date and goat information, including sex, age, and identification number for each case, were labelled on the plastic. Samples were transferred directly on the same day of collection to the laboratory in airtight boxes cooled with dry ice packs and then stored at 4\u0026deg;C until analysis. Fecal samples were examined microscopically for nematode eggs and oocyst coccidia presence using the Whitlock method with modification (Whitlock, \u003cspan citationid=\"CR110\" class=\"CitationRef\"\u003e1948\u003c/span\u003e). Three grams of feces from each animal were dissolved with 17 ml of tap water and stirred homogeneously. Then, 40 mL of saturated salt solution (NaCl, specific gravity\u0026thinsp;=\u0026thinsp;1.200) was used to float the nematode eggs/ oocyst coccidia. While stirring, the fecal solution was taken with a Pasteur pipette with a filter modification in the tip, and then the solution was put into the \u0026lsquo;Whitlock counting chamber\u0026rsquo; (Whitlock, \u003cspan citationid=\"CR110\" class=\"CitationRef\"\u003e1948\u003c/span\u003e), nematode eggs /oocyst coccidia were counted, and the number was multiplied by 40. The number of eggs was counted in units of eggs per gram (EPG) / oocysts per gram (OPG).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6. Milk production\u003c/h2\u003e \u003cp\u003eMilk production records from 172 crossbred does of Etawa owned by 7 farmers were used in this study. In addition to milk production, other records were also collected, such as body weight after giving birth, age, lactation period, and body condition score (BCS). They were milked twice daily, in the morning around 07:00 and at 15:00, by hand milking. Before milking, does were separated, and the mammae were cleansed thoroughly. Kids were allowed to suckle for 4 weeks, then separated and given milk replacements. The volume of milk was measured using a measuring cup with 10 mL sensitivity.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7. The system dynamics of dairy goat sustainability\u003c/h2\u003e \u003cp\u003eSystem dynamics (SD) is chosen for its capability to model and simulate the interrelated components of complex systems over time (Priyono et al., \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Sterman, \u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e2000\u003c/span\u003e), with the goal of developing a sustainable dairy goat farming system. In this study, the SD model consists of five interconnected submodels: (a) Population Dynamics Submodel; (b) Milk Production Submodel; (c) Feed Management Submodel; (d) Milk Demand Submodel; and (e) Economic Submodel. Each submodel is constructed using causal loop diagrams and stock-and-flow diagrams to represent the dynamic relationships and feedback mechanisms (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Data for the model parameters were sourced from field surveys, secondary literature, and expert consultations.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.8. Statistical Analysis\u003c/h2\u003e \u003cp\u003eMicrosoft Excel was used for data management, coding, and entry. The SAS v.9.4 (2021) was used to describe the descriptive statistics (frequencies and percentages) of the feeding types given to the animal. Statistical analysis of body measurement, body indices, physiological response, HTC, and AC, was conducted by using the general linear model of SAS v.9.4 (2021) statistical package, with the following model and assumption:\u003c/p\u003e \u003cp\u003eY\u003csub\u003eijklm\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;\u0026micro;\u0026thinsp;+\u0026thinsp;A\u003csub\u003ei\u003c/sub\u003e + B\u003csub\u003ej\u003c/sub\u003e + Ɛ\u003csub\u003eijk\u003c/sub\u003e\u003c/p\u003e \u003cp\u003eDescription :\u003c/p\u003e \u003cp\u003eY\u003csub\u003eijk\u003c/sub\u003e : the observation of body measurement, body indices, physiological response (RR, HR, RT, HTC, AC), from i\u003csup\u003eth\u003c/sup\u003e age of the animal and j\u003csup\u003eth\u003c/sup\u003e breed of goats\u003c/p\u003e \u003cp\u003e\u0026micro; : general mean\u003c/p\u003e \u003cp\u003eA\u003csub\u003ei\u003c/sub\u003e : the effect of i\u003csup\u003eth\u003c/sup\u003e age, where i\u0026thinsp;=\u0026thinsp;1, 2, 3, 4, and \u0026gt;\u0026thinsp;4 years old\u003c/p\u003e \u003cp\u003eB\u003csub\u003ej\u003c/sub\u003e : the effect of j\u003csup\u003eth\u003c/sup\u003e breed, where j\u0026thinsp;=\u0026thinsp;PE, Saanen, Anglo Nubian, and Boerawa\u003c/p\u003e \u003cp\u003eƐ\u003csub\u003eijk\u003c/sub\u003e : standard error from the effect of age and breed\u003c/p\u003e \u003cp\u003eThe statistical analysis for milk production was conducted using the following model and assumption :\u003c/p\u003e \u003cp\u003eY\u003csub\u003eijk\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;\u0026micro;\u0026thinsp;+\u0026thinsp;A\u003csub\u003ei\u003c/sub\u003e + B\u003csub\u003ej\u003c/sub\u003e + Ɛ\u003csub\u003eijk\u003c/sub\u003e\u003c/p\u003e \u003cp\u003eDescription :\u003c/p\u003e \u003cp\u003eY\u003csub\u003eijk\u003c/sub\u003e : the observation of milk production from the i\u003csup\u003eth\u003c/sup\u003e age of the animal, j\u003csup\u003eth\u003c/sup\u003e period of lactation,\u003c/p\u003e \u003cp\u003e\u0026micro; : general mean\u003c/p\u003e \u003cp\u003eA\u003csub\u003ei\u003c/sub\u003e : the effect of i\u003csup\u003eth\u003c/sup\u003e age, where i\u0026thinsp;=\u0026thinsp;1, 2, 3 age groups\u003c/p\u003e \u003cp\u003eB\u003csub\u003ej\u003c/sub\u003e : the effect of k\u003csup\u003eth\u003c/sup\u003e lactation period, where k\u0026thinsp;=\u0026thinsp;1,2,3\u003c/p\u003e \u003cp\u003eƐ\u003csub\u003eijkl\u003c/sub\u003e : standard error from the effect of age, breed, and lactation period\u003c/p\u003e \u003cp\u003eDifferences among group means were assessed using Duncan\u0026rsquo;s Multiple Range Test (DMRT) at a significance level of p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. The results are presented as means\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviations (SD).\u003c/p\u003e \u003cp\u003eThe sustainability model for population dynamics in dairy goat farming was validated through structural and behavioural validation processes. Structural validation involved verifying the logic and consistency of the causal and stock-flow diagrams with the input of experts. Additionally, behavioural validation was conducted by comparing the simulated outputs with historical data to confirm the model's ability to replicate observed trends. The Mean Absolute Percentage Error (MAPE) method was applied to assess behavioural validation (Sterman, \u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e2000\u003c/span\u003e):\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:MAPE=\\:\\frac{1}{n}\\:{\\sum\\:}_{t=1}^{n}\\left(\\frac{\\left|{Y}_{t}-\\stackrel{-}{{Y}_{t}}\\right|}{{Y}_{t}}\\right)\\:x\\:100$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eDescription:\u003c/p\u003e \u003cp\u003e \u003cstrong\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{Y}_{t}\\)\u003c/span\u003e\u003c/span\u003e\u003c/strong\u003e \u003cp\u003eactual data values;\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\stackrel{-}{Y}}_{t}\\)\u003c/span\u003e\u003c/span\u003e\u003c/strong\u003e \u003cp\u003emodel simulation values; and n\u0026thinsp;=\u0026thinsp;year/time interval.\u003c/p\u003e \u003c/p\u003e \u003cp\u003eTo assess the impact of various intervention strategies on the sustainability of dairy goat farming, the simulation (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) included five intervention scenarios implemented under two different policy conditions: moderate intervention (begins in 2027) and optimistic intervention (begins in 2029). Each scenario targeted key factors affecting the female dairy goat population and their milk production. Each intervention scenario was modelled to simulate changes in key parameters: birth rate, conception rate, and milk production. The results were analysed over a simulation period from 2023 to 2045, capturing the long-term effects of different policy interventions.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSimulation parameters under different intervention scenarios.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntervention\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eScenario 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eScenario 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eScenario 3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eScenario 4\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eScenario 5\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003eModerate policy intervention starts in 2027\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBirth Rate (kids per doe per year)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConception Rate (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMilk Production (liters/head/day)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003eOptimistic policy intervention starts in 2029\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBirth Rate (kids per doe per year)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConception Rate (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMilk Production (liters/head/day)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003eNotes: Birth Rate (Intervention: improved reproductive management); Conception Rate (Intervention: genetic quality improvement); and Milk Production (Intervention: enhanced feeding with concentrate and high-quality forage)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Nutrition and feeding system of the dairy goats\u003c/h2\u003e \u003cp\u003eThe feed resources predominantly used in the study area are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. A total of sixteen major feed types used by dairy goat farmers were identified and divided into five categories: natural grass, green forage, silage, concentrates (including commercial mixtures and agro-industrial by-products), and non-conventional feed resources, respectively.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe nutrient content of the feeds commonly used by farmers\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eFeedstuff\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDM (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"8\" nameend=\"c10\" namest=\"c3\"\u003e \u003cp\u003eChemical composition (% DM)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAsh\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eADF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNDF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNFE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eTDN\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNatural grass/Nutgrass \u003cem\u003e(Cyperus kyllinga\u003c/em\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e40.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e39.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e66.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e32.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e45.37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eGreen forages (cut and carry)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePennisetum purpureum\u003c/em\u003e cv.Mott\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e31.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e42.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e65.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e34.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e54.31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePennisetum purpureum\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.261\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e37.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e69.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e39.897\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e57.27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePennisetum purpureum\u003c/em\u003e cv.Zanzibar\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e33.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e41.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e68.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e48.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e49.29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSilages\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaize silage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e24.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e32.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e55.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e61.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e72.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCassava leaf silage\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e18.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e41.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e56.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e41.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e66.32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003eConcentrate and agro-industrial by-products\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaize\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e88.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e85.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e85.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSoybean meal\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e89.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e41.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e82.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSoya waste\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e18.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e28.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e41.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e77.52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTofu byproduct\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e35.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e22.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e41.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e57.87\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSoya bean hulls\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e21.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e30.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e58.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e69.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTapioca by-products\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e25.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e32.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e46.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e66.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e54.97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDried cassava\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e94.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e40.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e17.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e74.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e57.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eNon-conventional feed resources\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBanana plant stem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e24.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e32.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e48.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e59.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e56.62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCassava leaves\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e27.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e44.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e55.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e42.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e58.95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDried cassava peel\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e94.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e38.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e37.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e51.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e48.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e52.61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003eNotes:DM: dry matter; CP: crude protein; EE: ether extract; ADF: Acid detergent fiber; NDF: Neutral detergent fiber; NFE: Nitrogen free extract; TDN: Total digestible nitrogen. NFE is based on the formula NFE\u0026thinsp;=\u0026thinsp;100 \u0026ndash; Dry matter \u0026ndash; Crude protein \u0026ndash; Crude fat \u0026ndash; Crude fiber. Total digestible nutrient (TDN) content was estimated according to Hartadi et al. (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e1980\u003c/span\u003e). \u003csup\u003e1\u003c/sup\u003eOni et al. (\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2014\u003c/span\u003e); \u003csup\u003e2\u003c/sup\u003eBarzegar et al. (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2019\u003c/span\u003e); \u003csup\u003e3\u003c/sup\u003eSyafrudin et al. (\u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e2020\u003c/span\u003e); \u003csup\u003e4\u003c/sup\u003eAro and Aletor, (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e depicts the frequencies (%) of feed resources utilized by smallholder dairy goat farmers in North Sumatra, grouped by farm size (small, medium, and large). In this study, natural grass, green forage, and tofu by-products were widely used as the basal diet, with more than 50% of goat farmers utilizing them. There are no significant differences in feedstuff usage (natural grass, green forage, concentrate, tofu by-product, and dried cassava) among different farm sizes.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFrequencies (%) of feed resources as reported by smallholder dairy goat farmers in the District of Deli Serdang, North Sumatra Province.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eFeedstuff\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eType of farm\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ep value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSmall (n\u0026thinsp;=\u0026thinsp;8)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMedium (n\u0026thinsp;=\u0026thinsp;8)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLarge (n\u0026thinsp;=\u0026thinsp;8)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNatural grass/Nut grass (\u003cem\u003eCyperus rotundus L\u003c/em\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e75.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e54.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.584\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGreen forage (cut carry)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e87.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e95.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.957\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSilages\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaize silage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCassava leaf silage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eConcentrate and agro-industrial by-products\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConcentrate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.607\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaize\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSoybean meal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSoya waste\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTofu byproduct\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e50.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e58.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.109\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTapioca by-products\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSoya bean hulls\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDried cassava\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.564\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eNon-conventional feed resource\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBanana plant stem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCassava leaves\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCassava peel\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Morphometric measurements and body indices of the dairy goats\u003c/h2\u003e \u003cp\u003eBody weight and body measurement of the female Etawah Grade goat in this study are presented in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. The results showed that there was an effect of age on body weight and nearly all body measurements in female Etawah Grade goat, except for cannon circumference (CC), ear length (EL), and ear width (EW). Body indices are distinguished by breed, sex and ages. The results of the body index of dairy goats in North Sumatra are shown in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. Length index, height index, height slope, depth index, body index, proportionality, and pelvic index based on breed, sex, and age did not show significant differences. Area index based on sex and age showed significant differences based on sex and age, while based on breed there was no significant difference. Area index of bucks was higher than does. Goats of age group I0 had lower area index compared to I2, I3 and I4, and goats of age I2 were only lower than goats of age group I4.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBody weight and body measurements (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation) of female dairy goats in different age groups.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTraits\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eAge group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eOverall (n\u0026thinsp;=\u0026thinsp;110)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCV (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1PPI (n\u0026thinsp;=\u0026thinsp;14)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2PPI (n\u0026thinsp;=\u0026thinsp;32)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3PPI (n\u0026thinsp;=\u0026thinsp;32)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4PPI (n\u0026thinsp;=\u0026thinsp;32)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody weight (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33.62\u0026thinsp;\u0026plusmn;\u0026thinsp;6.28\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36.50\u0026thinsp;\u0026plusmn;\u0026thinsp;7.40\u003csup\u003ea,b\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39.88\u0026thinsp;\u0026plusmn;\u0026thinsp;5.19\u003csup\u003eb,c\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e47.18\u0026thinsp;\u0026plusmn;\u0026thinsp;7.57\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e40.13\u0026thinsp;\u0026plusmn;\u0026thinsp;8.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e20.58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody length (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59.96\u0026thinsp;\u0026plusmn;\u0026thinsp;6.26\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61.08\u0026thinsp;\u0026plusmn;\u0026thinsp;4.49\u003csup\u003ea,b\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e63.38\u0026thinsp;\u0026plusmn;\u0026thinsp;6.02\u003csup\u003eb,c\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e66.25\u0026thinsp;\u0026plusmn;\u0026thinsp;5.40\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e63.11\u0026thinsp;\u0026plusmn;\u0026thinsp;5.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9.29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWithers height (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66.43\u0026thinsp;\u0026plusmn;\u0026thinsp;5.02\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68.81\u0026thinsp;\u0026plusmn;\u0026thinsp;4.52\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e68.89\u0026thinsp;\u0026plusmn;\u0026thinsp;5.68\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e72.39\u0026thinsp;\u0026plusmn;\u0026thinsp;4.91\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e69.57\u0026thinsp;\u0026plusmn;\u0026thinsp;5.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChest girth (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e74.43\u0026thinsp;\u0026plusmn;\u0026thinsp;8.10\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e76.31\u0026thinsp;\u0026plusmn;\u0026thinsp;5.84\u003csup\u003ea,b\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e78.50\u0026thinsp;\u0026plusmn;\u0026thinsp;4.72\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e83.50\u0026thinsp;\u0026plusmn;\u0026thinsp;4.44\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e78.80\u0026thinsp;\u0026plusmn;\u0026thinsp;6.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChest depth (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23.36\u0026thinsp;\u0026plusmn;\u0026thinsp;2.01\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.22\u0026thinsp;\u0026plusmn;\u0026thinsp;2.99\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.47\u0026thinsp;\u0026plusmn;\u0026thinsp;2.57\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28.25\u0026thinsp;\u0026plusmn;\u0026thinsp;2.55\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e25.94\u0026thinsp;\u0026plusmn;\u0026thinsp;3.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e11.84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChest width (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.25\u0026thinsp;\u0026plusmn;\u0026thinsp;1.55\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.39\u0026thinsp;\u0026plusmn;\u0026thinsp;1.86\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.05\u0026thinsp;\u0026plusmn;\u0026thinsp;1.79\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.08\u0026thinsp;\u0026plusmn;\u0026thinsp;1.67\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e13.06\u0026thinsp;\u0026plusmn;\u0026thinsp;1.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e14.32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRump height (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69.07\u0026thinsp;\u0026plusmn;\u0026thinsp;6.07\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71.31\u0026thinsp;\u0026plusmn;\u0026thinsp;4.48\u003csup\u003ea,b\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e71.34\u0026thinsp;\u0026plusmn;\u0026thinsp;6.42\u003csup\u003ea,b\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e74.41\u0026thinsp;\u0026plusmn;\u0026thinsp;5.03\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e71.94\u0026thinsp;\u0026plusmn;\u0026thinsp;5.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.87\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRump width (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.61\u0026thinsp;\u0026plusmn;\u0026thinsp;2.56\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.69\u0026thinsp;\u0026plusmn;\u0026thinsp;1.73\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.16\u0026thinsp;\u0026plusmn;\u0026thinsp;1.62\u003csup\u003ea,b\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.19\u0026thinsp;\u0026plusmn;\u0026thinsp;1.86\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e12.25\u0026thinsp;\u0026plusmn;\u0026thinsp;1.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e15.84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCannon circumference (cm)\u003csup\u003ens\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.84\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.11\u0026thinsp;\u0026plusmn;\u0026thinsp;4.39\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.72\u0026thinsp;\u0026plusmn;\u0026thinsp;4.45\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.62\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e10.18\u0026thinsp;\u0026plusmn;\u0026thinsp;3.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e33.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHead length (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.14\u0026thinsp;\u0026plusmn;\u0026thinsp;1.96\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.34\u0026thinsp;\u0026plusmn;\u0026thinsp;2.62\u003csup\u003ea,b\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.88\u0026thinsp;\u0026plusmn;\u0026thinsp;2.99\u003csup\u003ea,b\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18.55\u0026thinsp;\u0026plusmn;\u0026thinsp;4.24\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e17.70\u0026thinsp;\u0026plusmn;\u0026thinsp;3.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e18.42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHead width (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.29\u0026thinsp;\u0026plusmn;\u0026thinsp;1.07\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.97\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.44\u0026thinsp;\u0026plusmn;\u0026thinsp;1.43\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.22\u0026thinsp;\u0026plusmn;\u0026thinsp;1.51\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e9.60\u0026thinsp;\u0026plusmn;\u0026thinsp;1.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e13,96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEar length (cm)\u003csup\u003ens\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24.79\u0026thinsp;\u0026plusmn;\u0026thinsp;5.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.65\u0026thinsp;\u0026plusmn;\u0026thinsp;6.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.34\u0026thinsp;\u0026plusmn;\u0026thinsp;5.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28.01\u0026thinsp;\u0026plusmn;\u0026thinsp;4.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e25.85\u0026thinsp;\u0026plusmn;\u0026thinsp;5.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e22.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEar width (cm)\u003csup\u003ens\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.39\u0026thinsp;\u0026plusmn;\u0026thinsp;2.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.25\u0026thinsp;\u0026plusmn;\u0026thinsp;2.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.25\u0026thinsp;\u0026plusmn;\u0026thinsp;2.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.34\u0026thinsp;\u0026plusmn;\u0026thinsp;2.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e10.59\u0026thinsp;\u0026plusmn;\u0026thinsp;2.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e25.78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTeat perimeter (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.50\u0026thinsp;\u0026plusmn;\u0026thinsp;2.14\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.75\u0026thinsp;\u0026plusmn;\u0026thinsp;3.93\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.41\u0026thinsp;\u0026plusmn;\u0026thinsp;3.68\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.19\u0026thinsp;\u0026plusmn;\u0026thinsp;4.10\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e9.07\u0026thinsp;\u0026plusmn;\u0026thinsp;3.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e42.45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTeat length (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.71\u0026thinsp;\u0026plusmn;\u0026thinsp;1.68\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.84\u0026thinsp;\u0026plusmn;\u0026thinsp;3.23\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.72\u0026thinsp;\u0026plusmn;\u0026thinsp;3.26\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.47\u0026thinsp;\u0026plusmn;\u0026thinsp;2.93\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e8.30\u0026thinsp;\u0026plusmn;\u0026thinsp;3.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e38.31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eNote: Superscript letters (a-d) indicate significant differences (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) within the same rows and age groups. ns\u0026thinsp;=\u0026thinsp;non-significant. PII\u0026thinsp;=\u0026thinsp;pair of permanent incisors\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe average body index according to breed, sex, and age of the dairy goats (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation) in the study area\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLength index\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eArea Index\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDepth Index\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBody Ratio\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHeight slope\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eProportionality\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eBody Index\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003ePelvix Index\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4473.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e37.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e110.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e80.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e97.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMax\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6557\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e48.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e145.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e154.54\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2809\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e18.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e82.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e60.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e68.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBreed\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePE ( )\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.91\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4465.2\u0026thinsp;\u0026plusmn;\u0026thinsp;712.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e37.03\u0026thinsp;\u0026plusmn;\u0026thinsp;4.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.97\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.25\u0026thinsp;\u0026plusmn;\u0026thinsp;2.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e110.91\u0026thinsp;\u0026plusmn;\u0026thinsp;10.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e80.49\u0026thinsp;\u0026plusmn;\u0026thinsp;7.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e97.2\u0026thinsp;\u0026plusmn;\u0026thinsp;16.95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSapera ( )\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.94\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4970\u0026thinsp;\u0026plusmn;\u0026thinsp;396\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e41.95\u0026thinsp;\u0026plusmn;\u0026thinsp;4.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.99\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e105.81\u0026thinsp;\u0026plusmn;\u0026thinsp;1.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e74.96\u0026thinsp;\u0026plusmn;\u0026thinsp;2.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e91.25\u0026thinsp;\u0026plusmn;\u0026thinsp;5.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.91\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5797.5\u0026thinsp;\u0026plusmn;\u0026thinsp;641.3\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e34.04\u0026thinsp;\u0026plusmn;\u0026thinsp;8.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.98\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.605\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e110.6\u0026thinsp;\u0026plusmn;\u0026thinsp;7.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e82.10\u0026thinsp;\u0026plusmn;\u0026thinsp;6.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e102.84\u0026thinsp;\u0026plusmn;\u0026thinsp;14.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.91\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4403.9\u0026thinsp;\u0026plusmn;\u0026thinsp;644\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e37.27\u0026thinsp;\u0026plusmn;\u0026thinsp;3.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.97\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.26\u0026thinsp;\u0026plusmn;\u0026thinsp;2.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e110.84\u0026thinsp;\u0026plusmn;\u0026thinsp;10.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e80.30\u0026thinsp;\u0026plusmn;\u0026thinsp;7.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e96.8\u0026thinsp;\u0026plusmn;\u0026thinsp;16.96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI0 ( )\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.88\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3377.5\u0026thinsp;\u0026plusmn;\u0026thinsp;187.4\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.99\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e113.82\u0026thinsp;\u0026plusmn;\u0026thinsp;9.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e76.56\u0026thinsp;\u0026plusmn;\u0026thinsp;11.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e97.43\u0026thinsp;\u0026plusmn;\u0026thinsp;21.32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI1 ( )\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.91\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3988.2\u0026thinsp;\u0026plusmn;\u0026thinsp;534.4\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35.26\u0026thinsp;\u0026plusmn;\u0026thinsp;3.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.96\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.64\u0026thinsp;\u0026plusmn;\u0026thinsp;2.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e111.63\u0026thinsp;\u0026plusmn;\u0026thinsp;12.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e81.04\u0026thinsp;\u0026plusmn;\u0026thinsp;8.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e94.61\u0026thinsp;\u0026plusmn;\u0026thinsp;10.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI2 ( )\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.89\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4337.6\u0026thinsp;\u0026plusmn;\u0026thinsp;668.5\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e36.48\u0026thinsp;\u0026plusmn;\u0026thinsp;3.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.97\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.43\u0026thinsp;\u0026plusmn;\u0026thinsp;2.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e113.05\u0026thinsp;\u0026plusmn;\u0026thinsp;6.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e80.46\u0026thinsp;\u0026plusmn;\u0026thinsp;5.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e95.66\u0026thinsp;\u0026plusmn;\u0026thinsp;18.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI3 ( )\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4423.4\u0026thinsp;\u0026plusmn;\u0026thinsp;649.6\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e36.6\u0026thinsp;\u0026plusmn;\u0026thinsp;5.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.97\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.44\u0026thinsp;\u0026plusmn;\u0026thinsp;2.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e109.44\u0026thinsp;\u0026plusmn;\u0026thinsp;12.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e81.09\u0026thinsp;\u0026plusmn;\u0026thinsp;9.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e97.1\u0026thinsp;\u0026plusmn;\u0026thinsp;16.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI4 ( )\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.91\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4901.7\u0026thinsp;\u0026plusmn;\u0026thinsp;643.6\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e39.01\u0026thinsp;\u0026plusmn;\u0026thinsp;3.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.98\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.79\u0026thinsp;\u0026plusmn;\u0026thinsp;2.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e109.44\u0026thinsp;\u0026plusmn;\u0026thinsp;10.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e79.65\u0026thinsp;\u0026plusmn;\u0026thinsp;6.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e99.45\u0026thinsp;\u0026plusmn;\u0026thinsp;17.64\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eNotes\u003c/strong\u003e \u003cp\u003edifferent alphabet from one category in one column means different (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05)\u003c/p\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Physiological response and the adaptation coefficient of the dairy goats\u003c/h2\u003e \u003cp\u003eThere was no significant influence of the animal\u0026rsquo;s age on HR, RR, and AC, however, a significant influence (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) was investigated for RT and HTC (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). The average HR, RR, RT, were 77.89\u0026thinsp;\u0026plusmn;\u0026thinsp;11.4 beats per minute, 13.09\u0026thinsp;\u0026plusmn;\u0026thinsp;2.36 breaths per minute, and 39.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.41 \u003csup\u003e0\u003c/sup\u003eC; respectively. The heart rate of the doe increases according to age. Whereas, the average HTC and AC from this study were 101.75\u0026thinsp;\u0026plusmn;\u0026thinsp;30,0 and 0.41\u0026thinsp;\u0026plusmn;\u0026thinsp;2.26, respectively. The average air temperature, relative humidity, and THI from the study site during 2021 were 27.05 \u003csup\u003e0\u003c/sup\u003eC, 85.9%, and 78.9, respectively. The lowest THI (77.81) was found in January 2021, and the highest THI (80.15) occurred in May 2021. The THI calculation from February to December 2021 put them in extreme condition, ranging from 78.12 to 79.51. The average ambient temperature, humidity, and THI in 2021 is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMean of Physiological Response, Heat Tolerance Coefficient, and Adaptation Coefficient of the goats in the study area\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSource of variation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHeart Rate\u003c/p\u003e \u003cp\u003e(Beat/Min)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRespiration Rate\u003c/p\u003e \u003cp\u003e(Breath/Min)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRectal Temperature\u003c/p\u003e \u003cp\u003e(\u003csup\u003e0\u003c/sup\u003e C)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHeat Tolerance Coefficient\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAdaptation Coefficient\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eAge (n)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI-2 (15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75.4a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.9a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e107.3b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.7a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI-3 (35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e74.9a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39.0a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e101.4b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.8a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI-4 (32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e81.1a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39.0a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e102.4b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.6a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge; I-5 (30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e79.5a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39.0a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e101.2b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.6a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eBreed (n)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePE (110)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e77.6a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.9a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e101.8a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.6a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSenduro (2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e92.0a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39.2a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e98.2a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.9a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale (4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e81.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.9a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e104.5a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.9a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale (108)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e77.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39.0a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e101.6a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.9a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe average RT from younger animals (I-0) 38.3 \u003csup\u003e0\u003c/sup\u003eC is significantly (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) lower compared to the RT of the older animals (I-1 to I-4).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Infestation of the internal parasites\u003c/h2\u003e \u003cp\u003eThe results of the examination of 66 fecal samples from this study indicated that the most abundant gastrointestinal parasites were coccidia. All ages of goats had a high prevalence of coccidia between 57% to 100% (Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e; Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrevalence and mean of fecal egg count in dairy goat\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBreed\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAge (year)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003ePrevalence (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eMean epg/opg\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;SD\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNematode (Strongyle)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCoccidia\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNematoda (epg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eCoccidia (opg)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0/7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e85.7 (6/7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e914.3\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;808.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.04 (1/25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e91.6 (22/24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.67\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e731.7\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;544.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0/7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100 (17/17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e607.1\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;559.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u0026ndash;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.14 (1/7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e57.1 (4/7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.71\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;2.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e177.1\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;172.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0/11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e81.8 (9/11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e472.7\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;673.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e83.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.5. Milk production of the goats\u003c/h2\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e illustrates the trends in goat milk production across five different locations over a six-month lactation period. Each location exhibits varying production patterns, with some areas experiencing significant fluctuations from month to month.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e illustrates the trend of milk production across different Body Condition Scores (BCS) over a six-month lactation period. The data shows distinct patterns for each BCS category (2.5, 3, and 3.5), highlighting the relationship between body condition and milk yield. Based on the figure, it can be seen that BCS 2.5 exhibits a sharp decline in milk production after the third month. While the production remains stable at 626.7 ml in the second and third months, it drops significantly to 300.0 ml in the fourth month and remains at that level through the sixth month. This suggests that goats with a lower BCS may struggle to sustain milk production in the later lactation stages. Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e presents data on body weight and milk production of dairy goats based on factor of age, and lactation period. Milk production data is recorded from the 2nd to the 6th month of lactation. The age of the goats gives different milk production patterns between groups.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDairy goat milk production in the 2nd, 3rd, 4th, 5th and 6th months according to breed, age and lactation period\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBody weight (kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c7\" namest=\"c3\"\u003e \u003cp\u003eMilk production (ml)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2nd month\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3rd month\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4th month\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5th month\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6th month\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u0026ndash;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32.8b\u0026thinsp;\u0026plusmn;\u0026thinsp;6.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1083.4a\u0026thinsp;\u0026plusmn;\u0026thinsp;110.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e944.6a\u0026thinsp;\u0026plusmn;\u0026thinsp;97.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e755.7\u0026thinsp;\u0026plusmn;\u0026thinsp;178.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e592.8b\u0026thinsp;\u0026plusmn;\u0026thinsp;218.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e411.1b\u0026thinsp;\u0026plusmn;\u0026thinsp;191.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38.9a\u0026thinsp;\u0026plusmn;\u0026thinsp;8.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e814.4b\u0026thinsp;\u0026plusmn;\u0026thinsp;179.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e721.1b\u0026thinsp;\u0026plusmn;\u0026thinsp;297.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e664.0\u0026thinsp;\u0026plusmn;\u0026thinsp;303.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e519.7b\u0026thinsp;\u0026plusmn;\u0026thinsp;312.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e734.9a\u0026thinsp;\u0026plusmn;\u0026thinsp;302.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u0026ndash;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42.6a\u0026thinsp;\u0026plusmn;\u0026thinsp;5.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e665.4b\u0026thinsp;\u0026plusmn;\u0026thinsp;211.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e770.9b\u0026thinsp;\u0026plusmn;\u0026thinsp;154.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e753.5\u0026thinsp;\u0026plusmn;\u0026thinsp;155.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e918.8a\u0026thinsp;\u0026plusmn;\u0026thinsp;259.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e826.6a\u0026thinsp;\u0026plusmn;\u0026thinsp;394.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLactation Period\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34.0b\u0026thinsp;\u0026plusmn;\u0026thinsp;6.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e931.1a\u0026thinsp;\u0026plusmn;\u0026thinsp;274.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e881.0a\u0026thinsp;\u0026plusmn;\u0026thinsp;165.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e773.1\u0026thinsp;\u0026plusmn;\u0026thinsp;160.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e655.8\u0026thinsp;\u0026plusmn;\u0026thinsp;279.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e511.6b\u0026thinsp;\u0026plusmn;\u0026thinsp;356.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u0026ndash;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39.2ab\u0026thinsp;\u0026plusmn;\u0026thinsp;7.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e874.1a\u0026thinsp;\u0026plusmn;\u0026thinsp;206.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e768.8b\u0026thinsp;\u0026plusmn;\u0026thinsp;303.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e707.0\u0026thinsp;\u0026plusmn;\u0026thinsp;299.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e630.7\u0026thinsp;\u0026plusmn;\u0026thinsp;279.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e728.4ab\u0026thinsp;\u0026plusmn;\u0026thinsp;208.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u0026ndash;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43.6a\u0026thinsp;\u0026plusmn;\u0026thinsp;4.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e578.1b\u0026thinsp;\u0026plusmn;\u0026thinsp;82.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e759.6b\u0026thinsp;\u0026plusmn;\u0026thinsp;41.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e711.6\u0026thinsp;\u0026plusmn;\u0026thinsp;143.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e704.5\u0026thinsp;\u0026plusmn;\u0026thinsp;428.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e808.0a\u0026thinsp;\u0026plusmn;\u0026thinsp;572.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eNotes : ns\u0026thinsp;=\u0026thinsp;Not significantly different in the same variables and columns, * = Significantly different (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in the same variable and column, a,b,c, = Different letters in the same variable and column indicate significant differences (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.6. The dynamic system of dairy goat sustainability\u003c/h2\u003e \u003cp\u003eThe simulation results reveal that different intervention strategies significantly impact the sustainability of dairy goat farming. The analysis considered two policy intervention scenarios: moderate intervention starting in 2027 and optimistic intervention starting in 2029. Under the moderate intervention scenario, strategies focused on reproductive management and genetic improvement to enhance birth rates led to a steady increase in female dairy goat population and goat milk yield (Table\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSimulation results of dairy goat population and milk production growth under different intervention scenarios\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntervention scenario\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDairy Goat Population (heads)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAnnual Growth Rate (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGoat Milk Production (tons/year)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAnnual Growth Rate (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eModerate policy intervention\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,417\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e293.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScenario 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,567\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e321.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScenario 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,659\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e338.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScenario 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,865\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e375.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScenario 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,417\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e384.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.56\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScenario 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,865\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e501.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eOptimistic policy intervention\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,417\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e293.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScenario 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,666\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e338.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScenario 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,829\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e367.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScenario 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e444.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.64\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScenario 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,417\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e445.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScenario 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e703.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe optimistic intervention scenario further strengthened these effects, demonstrating that comprehensive policy supports dairy goat sustainability. The integrated approach of reproductive, genetic, and nutritional improvements resulted in the highest increases in both female dairy goat population and goat milk production. The results indicate that Scenario 3 resulted in a population of 2,266 heads with an annual growth rate of 7.93% and milk production reaching 444.06 tons per year (7.64% growth). The most extensive intervention (Scenario 5) led to a remarkable surge, with the population reaching 2,266 heads and milk yield increasing to 703.10 tons per year and marking the highest growth rate of 9.65%.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e illustrates the trends in the female dairy goat population across different scenarios from 2023 to 2045. This result confirms that combining reproductive and genetic improvements yields a greater impact than applying these interventions separately. Moreover, optimistic policy intervention results in a higher increase in female dairy goat population compared to moderate intervention. Figure\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e presents the trends in goat milk production over the same period. These findings reinforce that integrating reproductive, genetic, and nutritional improvements is the most effective strategy for maximizing dairy goat sustainability in North Sumatra. Additionally, optimistic policy intervention leads to greater improvements in goat population and milk production than moderate intervention, reinforcing the need for strong policy support to achieve dairy goat sustainability in North Sumatra.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e4.1. Nutrition and feeding system\u003c/h2\u003e \u003cp\u003eA well-balanced diet with adequate energy and protein is essential to meet the nutritional requirements of goats for both maintenance and productivity. According to NRC (\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), the maintenance requirements for mature does weighing 40 kg are 0.53 kg/day of total digestible nutrients (TDN) and 67 g/day of crude protein (CP), with 20% undegradable intake protein (UIP). These requirements are increased during gestation and lactation. For example, during early gestation (single-kid pregnancy), energy and protein requirements increase to 0.61 kg/day of TDN and 98 g/day of CP. In late gestation, when body weight reaches 50 kg, the demands rise further to 0.89 kg/day of TDN and 166 g/day of CP to support fetal growth and metabolic changes.\u003c/p\u003e \u003cp\u003eFurthermore, during early lactation (with a single kid and milk yield ranging from 0.88 to 1.61 kg/day), the doe requires 0.79 kg of TDN and 166 g/day of CP. By mid-lactation (milk yield of 0.63 to 1.15 kg/day), the energy requirement slightly decreases to 0.78 kg of TDN, while protein needs to drop to 150 g/day. In this study, farmers and households used various feed ingredients to meet their goats' nutritional requirements. The variabilities of feed ingredients depend on the availability of the surroundings and the most economical feed they can afford, since feed contributes approximately 80% of the total cost of livestock management. Maize, dried cassava, and soybean meal are high-energy feed sources in the diet (TDN\u0026thinsp;\u0026gt;\u0026thinsp;80%), while soybean meal and cassava leaves, which contain crude protein levels above 16%, serve as important protein supplements to enhance goat growth and productivity. Row \u0026amp; Pethick (1994) explained that cereal grains such as barley, corn, oats, and sorghum provide substantial amounts of readily digestible carbohydrates.\u003c/p\u003e \u003cp\u003eThe findings of the present study on identified feed resources align with previous research by Duguma and Janssens (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Regardless of farm size, the majority (94.4%) of interviewed farmers relied on green feeds as the primary basal diet, particularly during the wet season. Overall, feed acquisition sources in the area in this study were a combination of on-farm production and purchased feed, with concentrates and agro-industrial by-products being primarily obtained through purchase. It seems that soybean and its derivatives are the most important ingredients that are available in the market. The fiber and energy sources can be obtained by growing around the areas; however, soybeans and their products mostly are still imported.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e4.2. Morphometric measurements and body indices of the dairy goats\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e indicates that age significantly affects body weight and body measurements of female Etawah Grade goat, except for CC, EL, and EW. The age effect was particularly evident between 1PPI and 4PPI age groups, whereas no significant differences were observed 2PPI and 3PPI groups. A similar age effect on body weight and body measurement traits was reported in indigenous Ethiopian goat populations (Melesse et al., 2022), although, in that study, significant differences in BW and morphometric traits such as BL, HG, WH, RL, and RW were observed between the 2PPI and 3PPI groups.\u003c/p\u003e \u003cp\u003eBody measurements of female Etawah Grade goats in this study exhibited low to high CV values (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The area index based on sex and age is significantly different, where male goats are significantly higher than that of female goats. The difference in area index is due to the body length and shoulder height of the goats which also differ according to sex. The area index based on age shows a significant increase according to the age of dairy goats, the smallest average area index is in goat I0 and the largest average is in goat I4. The similarity of the pattern between body size and area index is because the area index is a combination of two body measurements. According to Tiesnamurti et al (\u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) Body measurement indices are relationships among body measurements used to describe the proportions and general size of the part of animals. In that study (Tiesnamurti et al., \u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) also found the area index of male goats was larger than that of female goats, while based on age there was no significant difference.\u003c/p\u003e \u003cp\u003eLength Index or also called relative body index (Chac\u0026oacute;n et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) in this study obtained an average value of 0.91 which is lower than several previous studies (Chac\u0026oacute;n et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Khargharia et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Dea et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Getaneh et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Saleh et al., \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Tiesnamurti et al., \u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Dinesh et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), length index based on age and sex obtained by Tiesnamurti et al (Tiesnamurti et al., \u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) is also higher than dairy goats in this study. The area index of dairy goats in North Sumatra in this study was higher than that of Assam goats (Khargharia et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) and South Ethiopian native goats (Dea et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), lower PE goats (Tiesnamurti et al., \u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), several Chinese native goats (Saleh et al., \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), and several Ethiopian native goats (Getaneh et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The average depth index in this study showed a lower value than previous studies (Chac\u0026oacute;n et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Khargharia et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Dea et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Saleh et al., \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Dinesh et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The height slope and body ratio values ​​in this study were lower than Assam hill goat (Khargharia et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), Ethiopian native goat (Dea et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and the body ratio was lower than Kothdar goat (Dinesh et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) and Several Chinese Goat (Saleh et al., \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), while the body ratio of Cuban Creole goat was lower than this study (Chac\u0026oacute;n et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Tiesnamurti et al., \u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The proportionality index in this study was higher than previous studies on other goat breeds (Chac\u0026oacute;n et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Khargharia et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Dea et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Getaneh et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Saleh et al., \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Dinesh et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBody index describes goats as long, medium, or short bodied. According to Khargaria et al (Khargharia et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), if the body index value is above 90, it is long bodied, 86\u0026ndash;89 is medium category, and less than 85 is short bodied category. The overall average body index of dairy goats in this study showed that the goats were included in the short-bodied category, as well as goats grouped by breed, sex, and age. The average body index in this study was lower than the body index values ​​of several goats used in previous studies (Chac\u0026oacute;n et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Khargharia et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Dea et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Getaneh et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Saleh et al., \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Tiesnamurti et al., \u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Dinesh et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The pelvic index in this study was on average, higher than studies on several other goats in literature (Chac\u0026oacute;n et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Khargharia et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Dea et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Getaneh et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Saleh et al., \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Tiesnamurti et al., \u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Dinesh et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The high pelvic index value indicates a wider pelvic width dimension compared to previous studies.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e4.3. Physiological response and the adaptation coefficient\u003c/h2\u003e \u003cp\u003eThe average HR, RR, and RT from this study were in accordance with to study reported by Yuneriaty et al. (2022) for pregnant Kacang goats observed in Kupang, East Nusa Tenggara province, Indonesia. Ivanova et al (2023) reported that the average rectal temperature, respiration rate, and heart rate of the Bulgarian white dairy goat breed in South Bulgaria were 39.02\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;0.15 \u003csup\u003e0\u003c/sup\u003eC; 34.5\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;1.28 beats/min and 87.88\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;1.19 time/min, respectively. The rectal temperature did not differ during winter and summer; however, pulse/heart rate and respiration rate sharply increased in summer compared to winter. The THI increased along the seasonal changes from winter (11.2\u0026ndash;12.5) to summer (32.8\u0026ndash;33.3).\u003c/p\u003e \u003cp\u003eDias et al (2022) reported the average rectal temperature, respiration rate, and heart rate for adult Alpain male goats during summer were 38.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06 \u003csup\u003e0\u003c/sup\u003eC; 38.50\u0026thinsp;\u0026plusmn;\u0026thinsp;6.05 mov min\u003csup\u003e-1\u003c/sup\u003eand 74.86\u0026thinsp;\u0026plusmn;\u0026thinsp;3.65 beat min\u003csup\u003e-1\u003c/sup\u003e, respectively. The average rectal temperature did not differ significantly during winter, spring, and autumn; however, the respiration rate significantly differed significantly, which is higher in summer 38.50\u0026thinsp;\u0026plusmn;\u0026thinsp;6.05 mov min-1 compared to winter 23.36\u0026thinsp;\u0026plusmn;\u0026thinsp;2.04 mov min-1. However, the heart rate did not differ significantly during the four seasons.\u003c/p\u003e \u003cp\u003eOmar et al (2025) reported that Saanen does kept at different barn types, wooden and galvanized in Malaysia, showed that RR and HR were significantly (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) affected by the housing system; however, RT remained unaffected. The average rectal temperature, respiration rate, and heart rate were 39.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02 0C; 61.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.68 breath/min and 94.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.38 beats/min of Saanen does kept at different barn types. Nonetheless, Srivastava et al. (2021) reported that THI influences RT and RR in small ruminants.\u003c/p\u003e \u003cp\u003eTHI was influenced significantly by the ambient temperature and relative humidity in the area, in different climatic zones, which were distributed according to the classification of Habeeb et al. (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The THI classification aims to evaluate the intensity of heat stress according to the following categories such as \u0026lsquo;no effect\u0026rsquo; (THI\u0026thinsp;\u0026lt;\u0026thinsp;70); \u0026lsquo;low\u0026rsquo; (70\u0026thinsp;\u0026le;\u0026thinsp;THI\u0026thinsp;\u0026lt;\u0026thinsp;75); \u0026lsquo;moderate\u0026rsquo; (75\u0026thinsp;\u0026le;\u0026thinsp;THI\u0026thinsp;\u0026lt;\u0026thinsp;78), and \u0026lsquo;extreme\u0026rsquo; (THI\u0026thinsp;\u0026ge;\u0026thinsp;78), respectively. Indonesia is classified as a tropical humid country with average temperature and humidity relatively high, which will cause a high THI. Our study showed that average ambient temperature was a bit higher in some months from the temperature tolerance of goats (6\u0026ndash;27\u0026deg;C), the average ambient temperature at midday and the humidity in the morning were a bit higher than the temperature tolerance of goats, and the comfortable humidity, which is 60\u0026ndash;80% (Sejian et al \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), and still at the normal range of comfortable temperature for tropical goat, which is in between 20\u003csup\u003e0\u003c/sup\u003eC and 30\u0026deg;C (Borges and Rocha, 2018).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003e4.4. Infestation of the gastrointestinal parasites\u003c/h2\u003e \u003cp\u003eAll goats were fed elephant grass/Napier grass (\u003cem\u003ePennisetum purpureum cv mott\u003c/em\u003e) that came from the same source and without any treatment before being given to the goat. All animals sampled were clinically healthy and had no signs of disease. The prevalence rate of Gastrointestinal (GI) parasitism (Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e), especially coccidia in all goats, was relatively high at all ages (57\u0026ndash;100%), while the prevalence rate of nematodes was very low and tended to zero. According to Hassanen et al. (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), \u003cem\u003eEimeria spp\u003c/em\u003e. infections are one of the most economically significant diseases of sheep and goats. Radostits, Blood, and Gay (1994) showed that some Eimeria species exhibited clinical symptoms such as diarrhea, poor weight gain, a rough coat, weakness, and decreased production, but coccidiosis in sheep and goats is usually asymptomatic/subclinical. Furthermore, subclinical individuals serve as carriers, contaminating the environment by excreting the oocysts in their feces without exhibiting clinical symptoms (Chartier and Paraud \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Coccidiosis causes acute and chronic gastrointestinal damage and increases the risk of secondary infections (Seddik et al. \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Coccidia infestations can result in health problems ranging from significant weight loss or impaired growth (in older animals) to animal death (in young animals) (Gondipon and Malaka 2021).\u003c/p\u003e \u003cp\u003eSixty-six goats were infected by coccidia; there were 7 goat kids aged 1 year, and the remaining 59 goats were adults aged between 2 to \u0026gt;\u0026thinsp;5 years (Table\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e). This is despite previous reports that young ruminants have a higher susceptibility to Eimeriosis than adults (Abdelaziz et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; El-Alfy et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). According to our findings, adult and young goats are equally susceptible to acquiring the infection since they are exposed to the same stressors, such as intense rearing in small-scale pens with grass feed and water sources from the same location. In addition, this happens because the goats are often kept in damp conditions and lack sunlight. Haile (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) stated that the significance of these diseases in restricted herds is highlighted by the fact that the infections are more common and more severe in animals raised in intensive systems. According to Urguhart et al. (\u003cspan citationid=\"CR107\" class=\"CitationRef\"\u003e1996\u003c/span\u003e), the incidence of the disease in sheep and goats is significantly influenced by rearing stressor conditions, including weaning, transportation or relocation to a new pen, starvation, overcrowding, and unfavorable weather. A young goat at one year old had the largest number of oocytes per gram of feces (914 opg) and was classified as a moderate infestation. The average opg for goat older than one year to five years is decreasing between 177 and 731, and they are classified as mild infestation. Coccidiosis typically manifests clinically in young animals rather than adults because they have developed immunity from prior infections (Olmos et al. 2020).\u003c/p\u003e \u003cp\u003eThe severity of strongyle/coccidia infection was reported based on egg/oocyst count according to Urguhart et al. (\u003cspan citationid=\"CR107\" class=\"CitationRef\"\u003e1996\u003c/span\u003e) as mild (50\u0026ndash;799epg/opg), moderate (800\u0026ndash;1200epg/opg), or severe (\u0026gt;\u0026thinsp;200epg/opg). The fact that subclinical coccidiosis affects more animals and might result in serious long-term intestinal health impairment makes it especially noteworthy since it is believed to produce higher output losses than its clinical equivalent (Razavi et al. 2024). Although the number of oocysts per gram of feces is classified as low to moderate, this still needs attention in maintenance management so that infestation does not get higher and can cause health problems and decreased productivity. In order to identify particular risk variables that significantly impact the occurrence and severity of the clinical presentation, further study is necessary to develop an effective control plan for gastrointestinal parasite disorders.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec23\" class=\"Section2\"\u003e \u003ch2\u003e4.5. Milk production of the dairy goats\u003c/h2\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e highlights that goat milk production is significantly influenced by location, with some areas maintaining stable yields while others experience notable fluctuations. Factors such as environmental conditions (Laouadi et al., 2018; Mena et al., 2024), feed availability and quality (Mburu et al., 2014; Mena et al., 2024), and management practices such as breeding strategies (Laouadi et al., 2018; Sow et al., 2021) and economic strategies (Mena et al., 2024) likely play a crucial role in these differences. Locations like Namorambe and Percut Sei Tuan tend to have higher and more stable production, suggesting that conditions in these areas are more favorable for milk production. Deli Tua, STM Hilir, and Simalingkar exhibit more fluctuating and generally declining production trends, which may be affected by less optimal environmental conditions or limitations in farm management.\u003c/p\u003e \u003cp\u003eThe data suggests a strong correlation between BCS and lactation performance. Goats with a lower BCS (2.5) experience a sharp drop in milk yield, indicating that insufficient body reserves may limit milk production, particularly in mid to late lactation. Goats with moderate BCS (3) maintain relatively stable production but show a gradual decline, suggesting that while they have enough energy reserves, they may still experience a natural decrease in milk yield over time. Goats with a higher BCS (3.5) demonstrate a delayed peak and sustained increase in production, indicating that better body reserves can support prolonged lactation and higher yields in later months. These findings emphasize the importance of nutritional management in maintaining optimal body condition throughout lactation. Ensuring that goats achieve a BCS of 3.5 before and during lactation could contribute to higher and more sustained milk production, while goats with BCS 2.5 may require improved feeding strategies to prevent early declines in yield.\u003c/p\u003e \u003cp\u003eThe correlation between body condition score (BCS) and goat lactation performance is significant, as BCS serves as an indicator of energy reserves that directly influence milk production. Research indicates that BCS impacts various aspects of lactation, including milk yield and quality, which are crucial for optimizing dairy goat productivity. Higher BCS is associated with increased milk production, as it reflects better energy reserves and overall health of the goats (Gafsi et al., 2024). In a study, multiparous goats with higher BCS showed improved milk yield and composition, indicating that maintaining optimal BCS is essential for lactation performance (Ribeiro et al., 2023).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003e4.6. The dynamic system of dairy goat sustainability\u003c/h2\u003e \u003cp\u003eThe findings of this study highlight the critical role of targeted interventions in ensuring the sustainability of dairy goat farming. The results demonstrate that improvements in reproductive management, genetic selection, and feeding strategies contribute significantly to female dairy goat population growth and goat milk production. These findings align with previous studies indicating that genetic improvement programs for goats have been reported to enhance meat and milk production (Sousa et al., \u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Furthermore, achieving sustainable dairy goat farming requires a well-designed breeding program (Bett et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Escare\u0026ntilde;o et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Reproductive efficiency in dairy goats through Multiple Ovulation and Embryo Transfer (MOET), estrus synchronization (ES), and artificial insemination (AI) has been shown to improve genetic quality and milk production (Luo et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Lianou et al. (2022) also reported that improving reproductive performance in dairy does can enhance milk yield and litter size, while Ruvuga and Maleko (\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) found that superior dairy goat breeds contribute to improved lactation performance and milk production.\u003c/p\u003e \u003cp\u003eThe effectiveness of the combined intervention strategies (Scenario 5) suggests that a holistic approach is necessary to maximize dairy goat sustainability. The observed increase in population and milk production under this scenario supports the notion that integrating reproductive, genetic, and nutritional strategies leads to synergistic benefits. Similar findings have been reported in studies on dairy goats, where improved reproductive performance combined with the implementation of breeding strategies to enhance genetic quality has been shown to promote increased goat production (Upadhyay et al., \u003cspan citationid=\"CR105\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Zewdie and Welday, \u003cspan citationid=\"CR119\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Furthermore, Casta\u0026ntilde;eda-Bustos et al. (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) emphasized the importance of selecting genetic parameters for reproduction and milk production in dairy goats. Moreover, dietary improvements have been reported to enhance milk yield and overall productivity (Zamuner et al., \u003cspan citationid=\"CR117\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Zazharska et al., \u003cspan citationid=\"CR118\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) as well as milk quality (Yin et al., \u003cspan citationid=\"CR115\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) in dairy goats.\u003c/p\u003e \u003cp\u003eThe comparison between moderate and optimistic policy interventions further underscores the importance of early and comprehensive policy support. The more pronounced growth under optimistic intervention suggests that stronger policy measures implemented earlier can accelerate the development of the dairy goat sector. This finding aligns with previous research, which indicated that integrating government policies, management, and market mechanisms supports the sustainable development of dairy goat farming (Miller and Lu, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Furthermore, in South America, Brazil has developed its dairy goat industry by providing government assistance to small-scale goat farmers (Lu and Miller, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Similarly, goat farms in Greece have been reported to remain viable due to government subsidies (Tsiouni et al., \u003cspan citationid=\"CR104\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMoreover, the trends observed in Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e reinforce the results presented in the tables, demonstrating that Scenario 3 and Scenario 5 have the most substantial impact on population and milk production, respectively. The greater divergence of these scenarios from the baseline indicates their potential to drive long-term sustainability in dairy goat farming. Previous studies have highlighted that an increase in genetic quality, reproduction, and nutrition directly correlates with enhanced goat milk yield (Lianou et al., 2022; Ruvuga and Maleko, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Sousa et al., \u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDespite these findings, some limitations should be acknowledged. The study relies on simulation-based modelling, which may not fully capture real-world complexities such as disease outbreaks, market fluctuations, or climate change effects. Future research should incorporate more comprehensive modelling approaches, including stochastic simulations, to enhance the robustness of predictions. However, this study provides strong evidence that integrating reproductive, genetic, and nutritional improvements, supported by proactive policy measures, is the most effective strategy for ensuring the sustainability of dairy goat farming.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThe development of dairy goat farming throughout the country can be replicated based on a similar environment, based on the results of this study. Etawa crossbred did not experience heat stress in the intensive management system and can perform their milk production until about five years old. Even though goats were intensively kept at all times, infestation of internal parasites was observed; therefore, a protocol to monitor the gastrointestinal infestation should be anticipated. The sustainable development of dairy goats through the intervention of reproductive management, genetic improvement, and feeding strategies contributes significantly to the growth of the dairy goat population as well as their milk production.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eEthical approval\u003c/h2\u003e \u003cp\u003e The ethical clearance was granted by the Indonesian Centre for Animal Research and Development, Indonesian Agency for Agricultural Research and Development, Ministry of Agriculture, to the Indonesian Research Institute for Goats, number: Balitbangtan/ Lolitkambing/Rm/02/2021.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCredit Authorship/ Contribution Statement\u003c/h2\u003e \u003cp\u003e Bess Tiesnamurti: conceptual, writing, review, editing, validation, investigation, data analysis, supervision\u003c/p\u003e \u003cp\u003eSantoso : validation, review, investigation\u003c/p\u003e \u003cp\u003ePeni Wahyu Prihandini : validation, review, investigation\u003c/p\u003e \u003cp\u003eGresy Eva Tresia: conceptual, writing, review, editing, visualization, data analysis\u003c/p\u003e \u003cp\u003e Alfian Destomo : writing, review, editing, data Analysis\u003c/p\u003e \u003cp\u003eAlwiyah: data resources, investigation\u003c/p\u003e \u003cp\u003eAnwar: data resources, investigation\u003c/p\u003e \u003cp\u003eArie Febretesiana: data resources, investigation\u003c/p\u003e \u003cp\u003eYeni Widiawati : supervision, editing, validation\u003c/p\u003e \u003cp\u003eAlek Ibrahim : data analysis, writing, editing\u003c/p\u003e \u003cp\u003eDyah Haryuningtyas Sawitri : conceptual, writing, review, editing, visualization, data analysis\u003c/p\u003e \u003cp\u003e Priyono : writing, review, editing, and data analysis\u003c/p\u003e \u003cp\u003eEko Handiwirawan: conceptualization, writing, review, editing, resources, investigation, data analysis, validation, investigation, supervision\u003c/p\u003e \u003cp\u003eMohammad Ikhsan Shiddieqy: writing, review, editing\u003c/p\u003e \u003cp\u003eEndang Romjali: writing, review, investigation, validation, supervision\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eDeclaration of competing interest\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis work was supported by the Indonesian Centre for Animal Research and Development, Ministry of Agriculture (Fiscal Year 2021). M.I. Shiddieqy received funding from Indonesian Endowment Fund for Education (LPDP) for his study.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e \u003cp\u003eWe appreciate the Indonesian Centre for Animal Research and Development. Ministry of Agriculture and the Indonesian Endowment Fund for Education (LPDP). The authors wish to appreciate the Local Livestock Services and farmers for their willingness to participate in this study.\u003c/p\u003e\u003ch2\u003eData availability\u003c/h2\u003e \u003cp\u003eData will be made available on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAbdelaziz, A. R., A. Gareh, E. K. Elmahallawy, R. A. Elmaghanawy, E. I. El Tokhy, and S. S. Sorour. 2021. Prevalence and Associated Risk Factors of Eimeria spp. Infection in Goats in Northern and Southern Egypt. Euro. J. Zool. 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Animal 16(11):100653.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"body index, physiology traits, gastrointestinal parasite, milk production, the dynamics system","lastPublishedDoi":"10.21203/rs.3.rs-8839115/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8839115/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe study aims to investigate factors that influence the sustainability of dairy goats in the Deli Serdang, Indonesia. A total of 172 head of dairy goats from different breeds at 9 subdistricts were used in this study. The parameters observed were the type of feeds given to the animals, the morphometric measurements, the physiological traits of the animals, gastrointestinal infestation, and milk production. The result showed that the majority of feeds given to the goats were cut and carry green fodder (95.83%), tofu by-products (58.33%), and concentrate (25%), respectively. The dairy goats in this study were categorized as short with an average body index of 0.91. There was a significant influence (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) of age on rectal temperature (RT) and heat tolerant coefficient (HTC); however, not for heart rate (HR), respiration rate (RR), and adaptation coefficient (AC), respectively. The most abundant gastrointestinal parasite was coccidia, with the lowest (57%) and highest (100%) prevalence occurring in 4-year-old and 3-year-old goats, respectively. The highest milk production was found in 3-year-old goats (931.1 ml), whereas does with body condition score (BCS)\u0026thinsp;=\u0026thinsp;3.5 have persistently higher milk production. By using modelling, the most likely scenario to improve dairy goats' sustainability was scenario 5 (increase dairy goat population of 2,266 heads, milk yield increase to 703.10 tons per year, and the highest growth rate of 9.65%). In this study, dairy goat farmers sustain their milk production by utilizing local feed resources, demonstrating good adaptation to internal parasites, and adjusting to the local environment.\u003c/p\u003e","manuscriptTitle":"Morphometrics measurement, physiology traits and parasites infestation of dairy goats farms in North Sumatra, Indonesia: Challenges for the environmental sustainability of milk production","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-27 19:21:48","doi":"10.21203/rs.3.rs-8839115/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"82e5e042-6c85-49b5-8e1b-a0ccebe42d72","owner":[],"postedDate":"February 27th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Reject, do not Transfer","date":"2026-05-19T11:44:15+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-19T15:46:24+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-27 19:21:48","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8839115","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8839115","identity":"rs-8839115","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}