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African Swine Fever (ASF) has affected all pig breeds in North-East India since 2020, except Doom pigs, a unique indigenous breed from Assam and the closest progenitor to Indian wild pigs, resulting in significant economic losses for pig farmers in the region. Based on the complete sequences of theB646L(p72) gene, it has been determined that the virus responsible for the outbreak is ASFV genotype II. The further characterization of three complete sequences of theB646L(p72) gene established 100% identical with other existing sequences of different parts of the world as well as confirmed that there is no co-circulation of different genotypes of ASFV in India except genotype II. Present studies also corroborate thatMYD88, LDHBandIFIT1were important genes of the immune system involved in the pathogenesis of ASFV. The differential expression patterns of these genes in ASFV-infected survived, and healthy Doom breed pigs, compared to healthy control pigs, were studied to distinguish the expression pattern at different stages. The hardiness and ability of the Doom pig to withstand common pig diseases, along with its genetic resemblance to wild pigs, make it an ideal candidate for studying tolerance to ASFV infection. So, the present study investigates the natural resistance to ASF in Doom pigs from an endemic area in North-East India to support the proposition that Doom pigs can co-exist with virulent ASFVs recently break in North-East India. The results of this study also provide important molecular insights into the regulation of the ASFV-tolerant gene.ImportanceStudying the natural resistance to African Swine Fever (ASF) in Doom pigs from North-East India holds crucial importance. ASF has inflicted significant economic losses on pig farmers in the region, necessitating the identification and comprehension of factors contributing to resistance and tolerance in specific pig breeds such as Doom pigs. Understanding the molecular mechanisms and genetic factors associated with ASFV tolerance could help in breeding programs and the selection of resilient pig breeds, ultimately aiding in disease control efforts.

The present study aimed to identify novel biostimulatory compounds in boar seminal gel (SG), saliva and semen using Gas chromatography-mass spectrometry (GC-MS). SG alone and its combined application with saliva (SG+saliva) and semen (SG+semen) also studied to train young boars. SG alone and SG+Saliva investigated for estrus induction in gilts and sows. Distilled water (DW) exposure was kept as control. SG, saliva and semen screened for total 105, 96 and 89 compounds. The highest concentration was of alkanes followed by sugar alcohols, then hydrocarbons, amino acids and fatty acids. Elaidic acid is the novel compound identified in pigs. Other compounds were tridecenol, undecane, hexadecone, eicosane, tetracosane etc. Further, young males (64.86%) were able to get trained. Significant higher (p

ObjectiveOptimizing reproductive efficiency in terms of estrus induction and production performance using simplified hormonal intervention using GnRH, gonadotropins and progesterone at farmers’ field conditions to bred animals with superior quality semen and also to reduce the maintenance cost.MethodThe present study was planned for optimizing reproductive efficiency using four different easily available hormonal agents with simplified protocols at farmers’ field. A total of 126 females were used in the study. Hormonal protocols I, II, III and IV using GnRH + (PMSG+ hCG), (PMSG+ hCG), PMSG alone and prepared progesterone gel respectively were used for estrus induction in gilts and sows.ResultsThe estrus induction/rate was (77.77%, 81.36%, 78.57% and 50% respectively. The corresponding figures for interval (hrs) of heat exhibition from hormonal administration (121.33±4.93, 121.54±3.60, 78.52±4.52 and 192±24), conception rate (%) (72.22%, 81.25%, 68.18% and 33.33%) farrowing rate (55.55%, 68.29%, 68.18% and 33.33 %), total litter size at birth (7.2±0.64, 7.90±0.47, 8.90±0.47 and 7.00±0) and hormonal cost (Rs.) per animal (570, 335, 280 and 250 Rs.) were respectively. The easier to use protocol was III followed by II, I and IV.ConclusionIt was found that protocol II and III are effective and easier so can be used for optimizing reproductive efficiency in pigs at farmers’ field.

Pig husbandry is the most valued and economically sustainable husbandry in the livestock farming system. The performance and productivity of the pig are chiefly dependent on the nutritional factor steered by gut beneficial bacteria. The swine gut microbiome has a direct relationship with feed efficiency. As a consequence, identifying microbial taxonomy and functional capacity is critical for proper nutrient digestion. In the present investigation, eighteen grower pigs aged 3 months and weighing 30±0.55 kg were allocated into three different groups using a randomized block layout and supplemented with QPM maize fodder of 0, 5, and 10% to the basal diet by substituting (wt/wt on DM) the maize grains, and named as T0, T1, and T2to probe the increase in gut beneficial bacteria found in the faecal contents. For comparison with T0, T1, and T2, a random faecal sample designated R was collected from six grower pigs of the same age group and bodyweight fed a maize-soya bean-based diet. The experiment is being carried out to investigate the effect of various maize fodder levels on the metagenomic profiles of pig gut microbiota using the 16S rRNA gene. All of the experimental diets were iso-nitrogenous, with protein content ranging from 18.37 to 18.63 per cent. The data generated by 16S rRNA amplicon analysis was 68, 56, 61, and 39 Mb in R, T0, T1, and T2 samples, respectively. From taxonomic distribution, bacterial phyla namelyFirmicutes, Bacteroidetes, Proteobacteria, andSpirochetesare found in descending order of relative abundance in the R, T0, and T1 groups, respectively, whileSpirochaetes, Proteobacteria, Fibrobacteres, Bacteroidetes, andFirmicutesare found in descending order of relative abundance in the T2 group. The relative profusion ofFibrobacter succinogenesis 0.89% and 16.84% in the T1 and T2 groups. According to the findings, a higher level of maize fodder in the diet of grower pigs promotes the growth of fibre-degrading bacteria in the gut microbiota, particularlyFibrobacter succinogenes. Moreover, feeding green maize has decreased the population of methanobacteria in the gut of pigs, which in turn has limited the production of methane.

Nicobari pig is reared by Nicobarese, a native tribal population of Andaman and Nicobar Islands. Nicobari pig has maintained its genetic identity due to geographical isolation. This communication is the first report on maternal inheritance of Nicobari pigs. DNA polymorphism data showed seven haplotypes. D-loop sequence information and mitogenome analysis were able to earmark Nicobari pigs to Asian clade. The domestication process of pigs and its expansion pattern help to understand human migration pattern. Based on this hypothesis, this communication elucidates the probable origin of Nicobarese. Earlier studies indicated that Nicobarese had genetic affinities to races distributed in China, Malaysia and Thailand. Our data on maternal inheritance of Nicobari pig correlates with the data on migration of Nicobarese. Moreover, we could establish a novel connection of Nicobarese with people of Northeastern parts of India, Philippines and Vietnam through phylogenetic signal and geographical provenance of Nicobari pig. We further concluded that migration of Nicobarese happened during Western route of migration (WRM) ∼4000 years before present. Therefore, we propose one wave hypothesis of peopling of Nicobar based on our study and existence of Ausrtroasiatic language, Mon-Khmer in these islands.

Luteal steroidogenesis is critical to implantation and pregnancy maintenance in mammals. The role of androgen receptors (AR) in the progesterone (P

Improvement in litter traits is the key to profitable pig farming that directly enhances the economic standing of the farmers in developing countries. The present study aimed to explore oestrogen receptor (ESR), epidermal growth factor (EGF), follicle-stimulating hormone beta subunit (FSHβ), prolactin receptor (PRLR) and retinol-binding protein 4 (RBP4) genes as possible candidate genetic markers for litter traits in indigenous pigs of India. The breeds included in the study were Ghungroo, Mali, Niang Megha and Tenyi Vo, and the reproductive traits considered were litter size at birth (LSB), number born alive (NBA), litter weight at birth (LWB), litter size at weaning (LSW) and litter weight at weaning (LWW) at their first parity. PCR-RFLP and primer-based mutation detection methods were used to identify polymorphism, and associations between the genotypes and the traits were analysed using a general linear model. The Ghungroo pigs recorded the best litter performances among the breeds (p

Various training algorithms are used in artificial neural networks for updating the weights during training the network. But, the selection of the appropriate training algorithm is dependent on the input–output mapping of dataset for which the network is constructed. In this paper, a framework has been proposed consisting of five modules to select the optimal training algorithm for predicting pig breeds from their images. The individual pig images from five pig-breeds have been captured using inbuilt camera of mobile phone and the contour of pig has been segmented from each captured image by HUE-based segmentation algorithm. In Statistical Parameter and Color Component retrieval module, parameters like entropy, standard deviation, variance, mean, median, and mode and color properties like hue, saturation, value (HSV) extracted from the content of each segmented image. Values of all extracted parameters have been transferred into Training Algorithm Selection Module. In this module, a fitting neural network with different numbers of hidden neurons has been executed by feeding all extracted values from pig images for mapping their breeds. Ten training algorithms have been applied on the same extracted dataset separately for five epochs each keeping other network parameters constants. The mean square error (MSE) and correlation coefficient ([Formula: see text]) for the validation set have been calculated after adjustment of weights and biases in each connection of the neurons. One training algorithm among 10 and its suitable number of hidden neurons has been selected based on comparative analysis for getting lower MSE and higher [Formula: see text] in the validation set. Then, the fitting network with selected training algorithm has been run on the same extracted datasets until the stopping condition is reached. Then the test set images are fed into the network and the network output has been categorized to class which has been assigned to each breed of pig in Breed Prediction Module. The proposed framework has been able to predict breeds with 96.00% accuracy, achieved by the trial with 50 images of the test set. It may be concluded that the Neuro Statistic Neural Network model may be used for breed prediction of pigs by using images of individual pigs.

In this paper, an attempt has been made to develop a model to decide with precision the breed identity of individual goat by using its image. For image-based multi-class classification tasks, CNNs have been found to be the best tool. But selecting the most efficient CNN model for a particular classification scenario is a very difficult job. To find an optimal CNN model for goat breed prediction, we have compared two of the most popular pre-trained deep-learning-based CNN models (VGG-16 & Inception-v3) based on their performance. Both the models have been fine-tuned using transfer learning on the goat breed database. This goat breed database has been created from goat images of six different breeds, which have been captured from different organized registered goat farms in India and almost two thousand digital images of individual goat have been captured without imposing stress to animals. It has been observed that Inception-v3 has outperformed VGG-16 with higher accuracy and lower training time. To measure the prediction performance of this fine-tuned Inception-v3 model, it has been applied to a test set of pure breed goat images and standardized classification performance evaluation metrics have been used to evaluate the prediction results. From the results, it is established that the proposed method used in this paper is able to accurately classify (recognize) goat breeds with high accuracy. Finally, comparison has been made with prediction accuracies of different technologies used for identification of domestic animals.

Infrared thermography lends countless applications in biology and veterinary science. The popularity of the use of infrared imaging in the detection and mitigation of animal diseases has increased ...

India is home for at least 18 indigenous pig breeds; however, the genetic diversity of Indian pig

Nicobari pig is reared by

Image classification using fully connected neural network is not efficient due to huge number of parameters in each layer. In this paper, we propose a Neuro-Statistic model for classification of five different pig breeds from pig images. The model consists of four sub modules which work together as a layered structure. We captured multiple individual pig images of five different pig breeds from different organized farms to conduct this research, segmented the captured pig images using hue based segmentation algorithm and then calculated the statistical properties like entropy, standard deviation, variance, mean, median, mode and color properties like H.S.V from the content of the individual segmented images. We fed all the extracted properties into Neural Network for Pig Breed (NNPB) to perform pig breed prediction with the classification module and analyzed the best performance, regression error plot, Error histogram and training state of NNPB. The performance of NNPB network was accepted based on error analysis and finally, we used the trained model to predict the breed of 50 pig images and achieved the prediction accuracy of 90%.

Transportation of farm animals is a routine management practice. During transportation, animals experience physiological and psychological stress which has negative consequences on health and welfare of animals. Effect of transportation on pig health and welfare in island ecosystem is not properly known. Here, we report the effect of transportation stress under island ecosystem on serum biochemical parameters, lipid profile, stress biomarkers, and immune parameters in Andaman local pig. Twelve pigs were transported from North and Middle Andaman to South Andaman via road in which two small sea channels have to be crossed in ferry with vehicle on board. Transportation triggered increase in serum levels of total protein and albumin. Elevated levels of aspartate aminotransferase, alanine aminotransferase, alkaline phosphatase, lactate dehydrogenase, and creatine kinase in transported pigs indicated muscular exercise or impaired liver function. Transportation induced dyslipidemia indicated by elevated levels of total cholesterol, low-density lipoprotein cholesterol, and triglycerides and a decreased level of high-density lipoprotein cholesterol. High level of serum total nitric oxide and serum MDA as well as low antioxidant capacity in transported pigs indicated oxidative stress induction. Transportation resulted in activation of stress response and increased levels of serum cortisol and heat shock proteins were recorded in transported pigs. Moreover, increased concentration of pro-inflammatory cytokines (IL-2, IL-6, IL-12, IL-1β, and IFN-γ) and decreased concentration of anti-inflammatory cytokine IL-4 were detected in transported pigs. The results of the study are helpful for better understanding of transportation stress in pigs under island ecosystem.

Background: In the present study, a set of non-linear prediction equation was developed using records of body measurement traits, namely heart girth, punch girth, height at shoulder, height at back, height at fore leg, height at back leg and body length of pigs. Repeated measurement of traits at birth, 15 d, 30 d and weaning (42 d) of 394 piglets were used. Methods: The regression of body weight on body measurement traits showed non-linear relationship based on equation, Y = aXb. Correlation of heart girth with body weight (r2 = 0.968 for male and 0.969 for females; P less than 0.01) was highest among the traits studied. Result: Heart girth was found to be most suited among the traits to predict body weight in an exponential equation, Y = 0.00058 H2.49 and Y = 0.00061 H2.47 for male and females, respectively, explaining 96 percent of variation.

Animal identification is necessary for records, registration, and proof of ownership. The owner of few Black Bengal Goats can identify his goats by sight but it will create a problem for a larger number of goats as they are looking almost similar. A number of identification tools have been used for Black Bengal Goats like ear tag, tattoo, branding, RFID, etc. The Tattoos are permanent identification marking but inconvenient to read after a few months or years. Most of the farmers and breeders have used ear tags, which contain a number for identification of particular goat but may be lost at the time of grazing. Some organized farmers have placed RFID chips in tags but RFID reader is necessary to read the content of chips. In this paper, an effort has been made to identify individual Black Bengal Goat using their iris image like a human. The eye images have been captured preprocessed, enhanced, and irises have been segmented. The template has been generated from each segmented iris and stored in the database. The matching has been performed among different segmented iris images from the same goat and also been performed among iris images captured from different goats. It has been observed that the average Hamming distance among iris images captured at different times from the same goat are different from the average hamming distances among iris images from other goats. Finally, the matching threshold has been decided for the identification of Black Bengal Goat.

In this paper, individual light coloured pig (Yorkshire) has been recognized based on their ear images captured using mobile phones. The ears have been kept parallel to the light source and the images have been captured from the opposite side of the light source. The auricular venation pattern from each captured ear image has been extracted, the template has been generated and stored in a database. The templates of recaptured ear images have been matched with the stored templates of the same pig using average Euclidean distance. The pig has been verified if average Euclidean distances of matching are \({

Convolutional Neural Network (CNN) is widely used as a strong framework for object classification. This framework is suitable for classification of group of objects which carry similar features like animal breeds, plant varieties, etc. In this paper, an attempt has been made to build a model of identifying individual Ghungroo pig (one of the most popular registered pig breeds in India) based on its face image using CNN. Individual Ghungroo pigs look very similar, and it is a very challenging task even for humans to identify them from a group of Ghungroo pigs. Ten Ghungroo pigs from ICAR-Indian Veterinary Research Institute (IVRI) Animal Farm Kalyani (Block B, Kanchrapara, West Bengal 741235) have been captured using a DSLR camera. The pigs have been captured in natural environment without any restriction. The Inception-v3 model with transfer learning has been used to build the individual pig identification model. The captured images have been separated with 90%:10% into training images and test images sets, respectively. It has been observed that the model has predicted individual pigs with 100% accuracy at 0.87 confidence level.

This article reviews the advances in molecular genetics that have led to the genetic improvement in meat quality in pigs. During the past few decades, genes, or markers associated with genes have been identified that affects meat quality. The huge amount of information emerging from genomic studies is opening up new opportunities for the genetic selection of pigs. Several genes that influence meat quality have already been, or are close to being identified. Some of them have already been implemented into breeding programs by marker assisted selection. Fields like functional genomics and proteomics are helping in better understanding of the function and regulation of genes and how these participate in complex networks controlling the phenotypic characteristics of a trait. An integrated approach of genomics and proteomics with bioinformatics tools will further exploit the available molecular genetics information. This will allow animal breeders to make progress more rapidly to meet the demand for high quality pork.

The present study was conducted to ascertain the adaptive capability of pigs to different seasons based on changes in serum cortisol and lactate dehydrogenase (LDH) levels, and peripheral blood mononuclear cell (PBMC) heat shock protein 70 (HSP70) mRNA expression. Based on average THI, the seasons were classified as winter (November–February), spring (March–June), and summer (July–October). Hormone cortisol was found to be influenced by season (p

Visual features associated with cattle and pigs cannot just be used for individual biometric identification, they can also be used to organize the domain into distinct breeds. In this paper, we use cropped muzzle images of pigs for breed identification. Gradient patch density maps are first created, and then the patch density profile distribution tailored to a specific breed is learnt to characterize the feature space for each of the four pig breeds: Duroc, Ghungroo, Hampshire, and Yorkshire. A Maximal Likelihood (ML) inferencing at the patch level followed by a second-tier decision fusion based on majority vote has been used to detect the breed from any query feature computed from an arbitrary muzzle image. Duroc, Ghungroo, and Yorkshire show good classification accuracies of 75.86%, 70.59%, and 100%, respectively, while the accuracy drops for Hampshire to 58.78% on account of the intrinsic white patch diversity in the breed and its similarity to Duroc and Ghungroo on some counts.

Contents The objective of the present study was to investigate the effect of testicular tissue lysate (TTL) on developmental competence of germinal vesicle (GV) stage porcine oocytes. Two types of TTL were prepared through repeated freeze–thaw in liquid nitrogen, one from whole testicular tissue (wTTL) and other from either of four different sections of testes, namely just beneath the tunica albuginea (TA), from the transitional area between the seminiferous cord/tubules and the mediastinum testis (TR) and from the intermediate area (parenchymal tissue origin) and CE (cauda epididymis origin). The whole or section-wise TTL treatments were given for 44 hr during in vitro maturation (IVM). Oocyte maturation was done in either of the two media, namely defined (high-performance basic medium for porcine oocyte maturation, commercially available) and serum containing (TCM199). After maturation, oocytes were co-incubated with fresh spermatozoa for 6 hr and then transferred to embryo culture media. Treatment of GV stage oocytes with wTTL (1 mg/ml) increased the cleavage and morula percentage rate (69.23 ± 6.23 and 48.15 ± 6.77, respectively) than that of their control (58.33 ± 8.08 and 32.54 ± 5.53, respectively) in defined media, and in serum-containing media, cleavage and morula percentage rate were almost equal in both treatment (54.56 ± 7.79 and 34.70 ± 6.78, respectively) and control (59.52 ± 8.21 and 38.52 ± 6.54, respectively). However, effect of wTTL was not significant. In case of section-wise TTL supplements, TR section significantly (p

Assessment of genetic diversity in indigenous animals is an important and essential task for animal genetic improvement studies as well as conservation decision-making. The genetic diversity and evolutionary relationships among geographically and phenotypically distinct three pig breeds/types native to Indo-Burma and Eastern Himalayan global biodiversity hotspots were determined by genotyping with a panel of 22 ISAG recommended microsatellite loci as well as sequencing partial MTRNR1gene. The mean number of alleles per locus, effective number of alleles and observed heterozygosity were found to be 11.27 ± 0.85, 5.29 ± 0.34, and 0.795 ± 0.01, respectively. The moderate FST value (0.115 ± 0.01) indicated a fair degree of genetic differentiation among the native breeds. The Nei's unbiased genetic identity estimates indicated less genetic distance (0.2909) between Niang Megha and Tenyi Vo pigs than the both individually with Ghoongroo breed. The divergence time was also estimated from the microsatellite analysis. Analysis of MTRNR1gene revealed distinct clustering of native Indian pigs with Chinese pigs over European pigs. The study revealed the abundance of genetic variation within native Indian pigs and their relationships as well as genetic distances.

Ghungroo is the first registered pig breed of indigenous origin in India. The work was designed to develop a reference dissection method for carcasses by establishing bi-lateral symmetry and to determine whether or not differences exist between right and left sides of pig carcasses for some precisely measured physical and chemical traits. Carcass evaluation procedures could be simplified if selected measurements from one side accurately reflect the composition or meat quality of the entire carcass. Forty pigs of Ghungroo breed were selected to represent equally two sexes and two market weight groups. The pigs were slaughtered and after the carcasses were chilled they were carefully split into left and right sides. Least correlation coefficient (0.961) was observed for carcass length. The weights of all the five muscles evaluated differed slightly, but the left and right averages were not significantly different. Similarly, the mean difference for total intramuscular fat between left and right units of a muscle pair was not significant for any of the five muscles studied. Thus, the data obtained from left side of a Ghungroo pig carcass apparently was sufficiently accurate for most experimental purposes.

Carcass composition and meat quality were evaluated for Asha, a triple cross pig (Ghungroo x Hampshire x Duroc, G25H25D50), which was developed and released by ICAR-National Research Centre on Pig as a fattener pig variety. A total of 14 gilts and 20 barrows from triple cross pigs were slaughtered at the age of 10 months for evaluating the different parameters. Instrumental colour measurement indicated that the coordinates were in the following range: lightness (L*), 38.91 – 53.75; redness (a*, red ± green), 6.83 – 11.96; and yellowness (b*, yellow ± blue), 11.38 – 18.49. The mineral contents in the M. longissimus thoracis et lumborum were in the following range: potassium, 268 - 334 mg/100g; zinc, 0.59 - 0.83 mg/100g; copper, 0.04 – 0.1 mg/100g; manganese, 0.01 - 0.06 mg/100g and magnesium, 4.53 - 7.74 mg/100g. Significant (P>0.05) differences were not observed in the concentration of any of the estimated amino acids between the sexes. Fatty acid profiling of M. longissimus thoracis et lumborum indicated that saturated and unsaturated fatty acids were in the range of 31.14% - 38.65% and 60.27% - 69.49%, respectively. Results further indicated a concentration of 0.91% – 1.70% omega-3 fatty acids; 15.87% - 22.13% omega-6 fatty acids and 15.66% - 24.17% essential fatty acids in the muscle tissues.

The study was carried out on two different genetic groups of pig viz. Duroc and Hampshire maintained at pig breeding farm of National Research Centre on Pig, Guwahati. Effect of different genetic group and non-genetic factors (year and season of farrowing and parity) were estimated by least squares analysis of variance for different litter production, weight and pre weaning growth rate. Genetic group and parity revealed highly significant (P less than 0.01) effect on all the traits under study. However, effect of year and season of birth was non significant in most of the cases. The pre weaning mortality of Hampshire pigs was found to be less than Duroc. The performance of litter production and weight traits of Hampshire pigs were found to be better than Duroc pigs in the farm.

The present study was aimed to reveal the effect on keeping quality of boar semen on holding or not holding at an elevated temperature than that used for preservation when combined with washing or not washing of seminal plasma. Twenty ejaculates, four from each of five Hampshire boars were used to hold for 0 and 4h in GEPS extender at 22°C and subsequently washed (1500×g for 10min) of seminal plasma or left unwashed and preserved at 15°C for 72h after extending with the same extender. The seminal parameters in terms of sperm motility, live spermatozoa, and live spermatozoa with intact acrosome (LIA) were evaluated at 0h-(immediately after extension) and thereafter at 24h intervals. The mean percentage of sperm motility was significantly (P0.01) higher in unwashed than washed semen at both 0h and 4h of holding irrespective of preservation period. It was significantly (P0.01) higher in semen held for 4h than 0h irrespective of washing and significantly (P0.01) lower in washed than in unwashed semen irrespective of holding during preservation. Irrespective of preservation period the mean percentage of live spermatozoa was significantly (P0.01) higher with 4h than 0h of holding in both unwashed and washed semen and was significantly (P0.01) higher in unwashed than washed semen at both 0h and 4h of holding. It was significantly (P0.01) higher for 4h held semen irrespective of washing and was significantly (P0.01) lower in washed than in unwashed semen irrespective of holding during preservation. The mean percentage of LIA was significantly (P0.01) higher with 4h than with 0h holding in both unwashed and washed semen and was significantly (P0.01) higher in unwashed than in washed semen at both 0h and 4h of holding irrespective of preservation period. It was significantly (P0.01) higher for 4h held as compared to unheld semen irrespective of washing and was significantly (P0.01) lower in washed than unwashed semen irrespective of holding during preservation. The mean percentage of sperm motility, live spermatozoa and LIA decreased significantly (P0.01) in 0h and 4h holding irrespective of washing and in unwashed and washed semen irrespective of holding with increase in preservation period. Among all the treatments unwashed semen held for 4h yielded superior sperm quality on preservation. A total of 32 female pigs were inseminated using preserved semen obtained with the best processing technique found in the study. The conception rate, farrowing rate and litter size at birth were recorded to be 81.25%, 78.13% and 7.96 respectively as compared to 73.38%, 67.57% and 6.68 respectively in the control group. It could be concluded that unwashed Hampshire boar semen held for 4h, extended with GEPS and preserved at 15°C for 72h was conducive to obtain optimum fertility and fecundity in females when used for artificial insemination.

The aim of this study was to set up direct and indirect casual effects between body weight and biometric measurements of breeding gilts at growing and finishing stages of production using path analysis. Body weights of 50 crossbred (Landrace x Large White) female pigs were measured along with four biometric traits (body length, heart girth, flank-to-flank, height-at-withers) on each animal during growing and finishing stages of production. A computed mean of 1150 measurements per biometric trait taken during the entire study was subjected to path coefficient analysis using the correlation matrix approach. High positive and significant correlations (>84.3%) were observed between different biometric measurements. However, path analysis of these traits on body weight of pigs revealed that heart girth is the major contributor to the body weight of the pig with a higher amount of direct effect of 0.6539 (R2 = 95.25). The direct effects of body length and flank-to-flank measurements on body weight of the pigs were less. These traits mostly affect body weight indirectly via heart girth. Finding of the present investigation demonstrated that heart girth was the most important contributor to body weight of grower and finisher pigs and thus was recommended for quick estimation of body weight of breeding gilts under field or market conditions than other biometric traits. In addition, it could also be used for the construction of selection index for breeding gilts at both phases of growth.

The native pigs of North Eastern region have unique traits such as early sexual maturity and quality bristles compared with exotic/ crossbreds. An attempt was made to measure the genetic variation available within Niang Megha and Tenyi Vo pigs using 22 FAO-ISAG microsatellite markers. The analysis of microsatellite data revealed average number of observed alleles as 6.95±0.54 (Niang Megha) and 7.18±0.45 (Tenyi Vo) where as the effective average number of alleles were 3.55±0.33 and 3.81±0.41, respectively. The mean observed heterozygosities were found to be 0.61± 0.04 and 0.68± 0.05, whereas expected values were 0.67±0.03 and 0.69±0.03, for Niang Megha and Tenyi Vo pigs, respectively. Abundant genetic variations were displayed within the native pigs with the PIC values ranged between 0.41 (Sw2008) to 0.86. (S0218) for Niang Megha and between 0.45 (S0026) to 0.88 (S0005) in Tenyi Vo pigs. The mean F value was 0.15±0.05 in Niang Megha which is more than that found in Tevyi Vo. There was no genetic bottleneck observed in the studied population. A total of 23 and 22 private alleles observed in Niang Megha and Tenyi Vo pigs.

Twelve crossbred (Hampshire × Ghungroo) grower pigs (about 3.5 months, 19.31±0.10 kg BW) of either sex were divided into 2 groups of six each in a randomized block design to study the effect of supplementation of Azolla (Azolla carolini) meal on production performance of crossbred pigs. The trial was conducted in two phases i.e. grower stage from 3–5 months of age and finisher stage from 5–8 months of age of the pigs. The treatment groups were T1G (control) and T2G (2% Azolla) in grower stage and T1F (control) and T2F (2% Azolla) in finisher stage. All the diets were iso-nitrogenous and iso caloric. The growth rate and feed conversion ratio, digestibility of nutrients and cost of production were similar in both the groups in two phases.

Cassava tubers are rich in carbohydrate and can be successfully used as an energy source for swine. cassava could be used in pig rations balanced for nutrients especially protein/limiting amino acids at levels of 50–70% in diets for growing finishing pig without adversely affecting production performance as well as carcass characteristics. Cassava tubers could be a cheaper energy source for swine feeding. The economic importance of cassava, its production and the technical aspects of the limitations are also discussed. The opportunities and prospects of cassava feeding in pig are briefly reviewed in this paper.

The effect of changing climate will not only be confined to limited production, and the productivity of agricultural commodities, but will also have far-reaching consequences on dairy, meat, wool and other animal products. The impact of climate change on the livestock sector as a whole will be felt more in tropical countries compared to temperate countries, largely because of the structure of production system and economics. The resultant pressure, both direct and indirect, is likely to result in further dilution of livestock diversity, which would specially affect the nutritional security and livelihood of small and marginal farmers. The challenge is to sustain genetic diversity and productivity by different adaptation strategies like production adjustment, breeding strategies, alteration of management systems, developing appropriate policies, scientific intervention and capacity building of livestock owners. In light of concerns over the impacts of climate change and climate variability, this chapter provides an overview of the opportunities for adaptation and mitigation strategies in tropical climatic conditions.