<div>Background: Freemartinism is a special kind of cell chimerism occuring in female calf born co-twin with male calf. It is one of the most common forms of intersexuality found in cattle, arises as a consequence of vascular anastamosis between fetuses of different genders. Freemartinism causes alterations in the development of female reproductive organs and sterility. However, there were reports of fertile heterosexual twins also. Hence, the present study aimed at early diagnosis of 60, XX/XY chimerism in heterosexual pregnancies to prevent the unnecessary economic losses and preserve valuable genetic material. 
 
Methods: Chromosomal profile of female and male calves were analyzed through short term lymphocyte culture technique. The gene expression levels of ZFX and SRY genes were determined through SYBR green real-time PCR. 
 
Result: Both female and male co-twins were found to possess 60, XX/60, XY chimerism, yielding the PCR products of both the male (SRY) and female (ZFX) specific genes. A real-time PCR revealed higher levels of ZFX gene expression in female (81.66 per cent) and male (88.35 per cent) calves than SRY gene. Combination of karyotyping and real-time PCR gave a confirmative diagnosis of freemartinism, suggesting the early diagnosis soon after birth.</div>

Early Diagnosis of 60, XX/XY Chimerism in Cattle using RT-PCR

Background: An early diagnosis of pregnancy in Sprague Dawley (SD) rats is of great importance for scientific research in reproductive health and perinatology. However, the commonly used methods, vaginal embolus check and vaginal smear for sperms, are not always satisfactory in practical courses. To explore a more convenient method for practice in identifying the pregnant SD rats at an early stage, we hypothesized that differences among weight changes may separate pregnant SD rats from the unpregnant effectively.&nbsp; 
 
Methods: The initial weight (W0) of SD female rats before mating and the weight of them from day 6 to day 12 after mating were recorded, then gained weight (∆W) was calculated. Pregnancy was confirmed when female rats gave birth on day 23 or earlier.&nbsp; 
 
Result: In total, weight changes data of 34 pregnant rats and 49 unpregnant rats were collected. Weight gains of pregnant SD rats on the 6th day were found different from those in unpregnant SD rats significantly and a diagnostic model of ∆W on gestation day 6 (∆W6) has been set up to distinguish pregnant SD rats with 70.00% sensitivity and 100.00% specificity. Diagnostic data models of ∆W7 ~ ∆W12 owned higher sensitivity and specificity respectively. Cut-off values of DW6 ~ DW12 were correspondingly 25.50 g, 23.00 g, 22.50 g, 22.50 g, 31.00 g, 27.00 g and 31.00 g. Practically, diagnostic models of weight gains showed robust potential in affirming the pregnant SD rats at early stage of gestation.

Early Pregnancy Diagnosis by Weight Measurement in the Sprague Dawley Rats: A New Method

<div>This study was designed ability using antibody against buffalo PAG to detect concentration of pregnancy-associated glycoprotein (PAG) in bovine plasma samples. Successful purification of buffalo PAG molecules with high enrichment degree by using Vicia villosa a&ucirc;nity chromatography was recently reported. In this research, the RIA system using novel anti buffalo-PAG was used for bovine pregnancy diagnosis. In a total 437 blood sampling of dairy cow in Belgium were used. Three PAG-RIA systems were undertaken to measure PAG concentration in bovine routine blood samples: AS#497 (or RIA-1) using rabbit antisera against purified bovine PAG67kDa, AS#706 (or RIA-2) using rabbit antisera against caprine PAG55+62kDa and new AS#859 (or RIA-3) using rabbit antisera against buffalo PAG59.5-75.8kDa). The measured PAG concentrations were similar for the systems As#497 and As#859; although the dilution was shown parallel, the measured PAG concentrations were significantly different between systems As#706 and As#859. On the other hand, the coefficients of correlations between concentrations obtained by the use of As#859 and As#497 were highly comparable to those between As#859 and As#706 or As#497 and As#706. In conclusion, the present study clearly shows that antisera against buffalo PAG can be used to develop new PAG-RIA system for bovine pregnancy diagnosis with high comparable results.&nbsp;</div>

<div>Validation of Buffalo PAG Antisera for Early Pregnancy Diagnosis in Bovine&nbsp;</div>

<div>Tuberculosis (TB) is an infectious and contagious disease caused by various strains of Mycobacterium and the foremost leading cause of death of animal and human population worldwide. Currently available conventional and modern diagnostic techniques are useful but they are neither rapid nor cost effective for early and accurate diagnosis, represents a cornerstone to eradicate TB worldwide by 2030. To overcome this awful situation an innovative strategy i.e. nanotechnology is helpful for early diagnosis of tuberculosis in short time with increased sensitivity and specificity through nano sized biomolecular interaction viz. enhanced visualization of fluorescent signals, visual colorimetric signals of amplified DNA product, nanofluidic technology, nuclear magnetic resonance technology (NMR) and prototype miniaturized device etc. Nanotechnology has introduced new paradigms for molecular diagnostics. However, some constraints of nanodiagnostic tool still there that make obstacle in its worldwide diagnostic use for TB.</div>

<div>Prospects and Application of Nanotechnology for Diagnosis of Tuberculosis in Livestock: A Review</div>

Background: Fatty liver is a major metabolic disorder of dairy cows with a high morbidity rate during early lactation. Diagnosis of mild and moderate fatty liver is difficult because affected cows often do not differ clinically from cows with normal liver. The need for the early identification of fatty liver cannot be overemphasized as it appears to be the root cause for occurrence of many post-partum metabolic diseases. A precise diagnosis of the different categories of fatty liver is possible by liver biopsies which entail a minor surgery. Spectral doppler is yet another milestone in identification of fatty infiltration of liver, without causing any trauma to the liver. With this backdrop this research study was carried out to document the ultrasonographic pattern of liver, to evaluate the Spectral Doppler derived indices of portal blood flow in fatty liver syndrome in cattle. 
 
Methods: The study was conducted in clinical cases, presented to Large Animal Medicine Outpatient Unit of Madras Veterinary College Teaching Hospital over a period of 24 months. Dairy cows, with the history of recent calving, postpartum inappetance and brought for other routine check-ups were included for the study. Suspected cases were subjected to further examination. Concurrent diseases presented with Fatty liver syndrome were recorded. Animals were grouped into four categories based on the above investigations as group I, II, III and IV as control, mild fatty liver, moderate fatty liver and severe fatty liver respectively.&nbsp; 
 
Result: B-Mode Ultrasonography was superior in grading the fatty liver, compared to spectral doppler. Spectral Doppler derived indices of portal blood flow in fatty liver syndrome revealed significant reduction in venous pulsatility index in severe cases. But grading the fatty liver was not possible with spectral doppler. Among clinical manifestations, Postparturient inappetance (98.3 per cent), reduced milk yield and weight loss were the prominent in fatty liver syndrome. Major concurrent diseases in fatty liver syndrome were ketosis, haemoprotozoan diseases, repeat breeder and mastitis. The present study will be helpful in field level diagnosis of fatty liver in cattle and supplements the knowledge on concurrent diseases that could influence the prognosis of individual animal. The study also opens gateway to do further research in considering alternates to the liver biopsy and histopathological studies.

Evaluation of Imaging Techniques and Invasive Procedures in Diagnosis of Fatty Liver in Dairy Cows

<div>Background: Proper diagnosis of a foliar disease is a prerequisite to undertaking any crop protection strategy under field conditions. Poor diagnosis and a delay in confirmation in turn decrease the crop yield and increase the cost of plant protection. In this background, advanced machine learning techniques were used for diagnosis of major foliar diseases in black gram using image detection. Casually, black gram yields are highly reduced due to anthracnose and powdery mildew diseases up to 40-67%. To address the issues, the advanced disease identification method of Convolution Neural Network (CNN) is proposed for automated diagnosis in its early stages to assist farmers. 
 
Methods: Disease infected leaf samples and their images were collected from different cultivated areas of Tanjore district, Tamil Nadu, India. The image noises were removed and enhanced to improve the accuracy of the training network. A Convolution Neural Network was built with five layers to work on disease images. The first stage of training is to load the image set for training, establish the learning rate, run the optimizer and compile the training convolution model. The final part is to save the loss and accuracy during the training process and evaluate the accuracy of the model. To improve the training learning rate, the Adam optimizer and RMSprop algorithm are used to dynamically adjust the learning rate. The image dataset holds a total of 2002 images of black gram anthracnose and powdery mildew for evaluation. 
 
Result: The experiment result showed that the accuracy of disease detection in black gram is about 92.50 per cent with a Precision: 97.14 per cent, Recall: 87.17 per cent, F1 score: 91.89 per cent which proves that convolutional neural network has a faster training speed and higher accuracy. In addition, the proposed method is less time consuming, an early detection tool for the farmers to identify the anthracnose and powdery mildew in black gram leaf which is essential for the application of proper disease management strategies and reduction of yield loss and aids in promotion of smart agriculture.</div>

Diagnosis of Major Foliar Diseases in Black gram (Vigna mungo L.) using Convolution Neural Network (CNN)&nbsp;

<div>Background: Canine Leptospirosis is a life-threatening disease and zoonosis. Usually, PCR assay is carried out for early diagnosis but requires a thermal cycler and post-PCR procedures. This limits its use in resource-limited areas. Hence, the isothermal amplification of nucleic acid by recombinase polymerase amplification assay was developed as a versatile alternative for the diagnosis of canine leptospirosis in this study.&nbsp; 
 
Methods: The RPA assay to detect Leptospira DNA was optimized with Leptospira reference strains and its performance characteristics such as analytical, diagnostics and reproducibility were assessed. 
 
Result: The limit of detection of RPA assay was estimated as 102 copies of genomic DNA and specific to amplify the pathogenic Leptospira. Out of 150 dog samples screened, Leptospira DNA was detected in 64 (42.6%) by RPA assay and 67 (44.6%) by PCR. The diagnostic sensitivity and specificity of the RPA assay were 92.5% and 97.59% respectively. The RPA assay has a good diagnostic agreement with a kappa value of 0.905. The reproducibility assessment with the third-party testing laboratory revealed a better agreement with a kappa value of 0.81. The simplicity, rapid and less expensive enable this assay to perform at resource-limited laboratories or point-of-care testing.&nbsp;</div>

Development and Evaluation of Recombinase Polymerase Amplification Assay for Diagnosis of Canine Leptospirosis

<div>Background: In Sri Potti Sriramulu Nellore district of Andhra Pradesh long duration varieties of pigeonpea (160-180 days) is grown during rabi under rainfed conditions. Late or advancement of north east monsoon, prolonged breaks and early cessation of rainfall may have devastating effects on pigeonpea yield in rainfed areas of Sri Potti Sriramulu Nellore district, Andhra Pradesh even if the mean annual rainfall is normal. In this context, there is a need for introduction of suitable super early varieties of pigeonpea which are ideal even under changing climatic situations, with suitable crop geometry to enhance the yields of pigeonpea.&nbsp; 
 
Method: A field experiment was conducted during rabi, 2018-19 and 2019-20 at Agricultural Research Station, Podalakur, Sri Potti Sriramulu Nellore andhra Pradesh, to find out the suitable super early variety of pigeonpea and their response to different crop geometries. The present field experiment was laid out in a split plot design with 4 varieties of pigeonpea (V1: ICPL 20338; V2: ICPL 20325; V3: ICPL 11255; V4: LRG 52) as main plot treatments and 3 crop geometries (S1: 30 cm x 15 cm; S2: 45 cm x 15 cm); S3: 60 cm x 15 cm) as subplot treatments and replicated thrice. 
 
Results: Super early variety ICPL- 20325 recorded the highest mean grain yield (1098 kg ha-1) among the four varieties of pigeonpea tested. Among the three crop geometries tested significantly the highest grain yield (930 kg ha-1) was recorded at 45 cm x 15 cm. Super early varieties ICPL- 20325 (1256 kg ha-1), ICPL- 11255 (930 kg ha-1) and ICPL- 20338 (817 kg ha-1) recorded higher mean grain yield at crop geometry of 45 cm x&nbsp;15 cm. LRG-52 (996 kg ha-1) variety recorded higher grain yield at crop geometry of 60 cm x 15 cm.</div>

Response of Super Early Varieties of Pigeonpea to Crop Geometry under Rainfed Conditions

<div>Background: In view of developing early maturing groundnut that fit in high intensity multiple cropping system the present study was taken up to introgress early maturing traits in the well-established high yielding varieties. 
 
Methods: VRI 8, CO 7, ICGV 07222 and VRI 6 were takenas the variety to be improved and as a source for early maturity and male parent in the study viz., VRI 3, Chico, ICGV 91114 and ICGV 93468 were used. A crossing program was designed using these parent materials and selected crosses were forwarded to the next F2 generation and their backcross populations were also generated. The data recorded were subjected to Generation mean analysis and association analysis. 
 
Result: With consideration of early maturity and high pod yield the genotypes F2 of CO 7 &times; Chico and ICGV 07222 &times; Chico and B2 of ICGV 07222 &times; Chico recorded high mean values for the traits. The presence of duplicate epistasis was observed for, days to accumulation of 25 flowers (DTF) and days to maturity. This indicates that, inter-mating the selected segregating generations could result in the accumulation of favourable genes. The trait pod yield per plant exhibited positively significant correlation with days to accumulation of 25 flowers, days to maturity in all the crosses and the trait days to accumulation of 25 flowers is positively correlated to days to maturity. Thus, the trait-days to accumulation of 25 flowers is the major selection factor for early maturity in groundnut.</div>

Development of Early Maturing Varieties in Groundnut (Arachis hypogaea L.)

<div>Background: Early leaf spot caused by Cercospora arachidicola Hori. is most destructive disease in all the groundnut growing areas of Rajasthan, under severe infestation it cause 30-50% losses in pod yield. Recently, Central Insecticide Board (CIB), Faridabade banned 27 pesticides including some important fungicides which are extensively used in plant disease management. Therefore, in the present investigation, our main emphasis was to find out some new fungicides for management of early leaf spot disease. 
 
Methods: Ten fungicides (hexaconazole 5% EC, difenconazole 25% EC, propiconazole 25% EC, tebuconazole 25.9% EC, trifloxystrobin 25% + tebuconazole 50% WG, mancozeb 50% WP, chlorothalonil 75% WP, carbendazim 50% WP, carbendazim 12% + mancozeb 63% WP and captan 70% + hexaconazole 5% WP) were evaluated against early leaf spot pathogen (C. arachidicola) both in lab as well as in field condition. The experiment was conducted at ARS, SKRAU, Bikaner during Kharif-2019 on most popular cv. HNG-69 in RBD design with the application of foliar spray of ten different fungicides at different concentrations against early leaf spot disease and compared with an untreated control. 
 
Result: Among all the fungicides used in the present investigation, Tebuconazole 25.9% EC was found most effective in inhibiting the mycelial growth of the pathogen followed by trifloxystrobin 25% + tebuconazole 50% WG. Under field condition, it gave maximum (70.73%) disease control with highest pod yield (31.5 q/ha) and net return (Rs 57,500/ha) when applied as foliar spray at 0.1% concentration followed by trifloxystrobin 25% + tebuconazole 50% WG at 0.2%. These treatments can provide an effective and economical management of early leaf spot disease for groundnut cultivators.</div>