An improved steel bullock cart (2.0 tones capacity) of INSDAG (Institute of Steel Development and Growth, Kolkata) design has been evaluated after putting rubber liner on its wheels as a modification, with a view to study its suitability in preventing the surface of rural roads. The cart with and without rubber liner was tested in the tar road of animal test track existed in the premises of OUAT, Bhubaneswar, Odisha during the year 2012 with a pair of non-descript small size bullocks having a pair body weight of 420 kg. The results indicated that the small size bullocks could sustain pulling a pay load of 1200 kg continuously for three hours with rubber liner with the work rest cycle of 1 hour work + 15 min rest + 1 hour work + 20 min rest + 1 hour work as against 900 kg without rubber liner in tar road.&nbsp;

Studies on draftability and enhanced utilization of small size bullocks&nbsp;of Odisha for pulling improved steel cart on tar road

Background: Further research is needed to estimate the marketable live weight of lambs with high accuracy and reliability while minimizing contact and measurement. This study aimed to estimate the 120th-day marketing weight of Morkaraman lambs by different machine learning algorithms, considering the variables of dam age, sex, birth type, birth weight, as well as 30th day, 60th day and 90th day live weights.&nbsp; 
 
Methods: Artificial neural networks (ANN), classification and regression trees (CART), support vector machines with radial basis function kernel (SVMR) and Random Forest (RF) algorithms for estimation of the marketing weight were performed for training (75%) and testing (25%) datasets. Models used in this study were compared based on mean absolute error (MAE), root mean squared error (RMSE) and mean absolute per cent error (MAPE) performance metrics. The most significant predictor of the marketing live weight in all models was the 90th day live weight, whereas the birth weight, birth type and dam age were the least important predictors. The correlation coefficients between live weight values estimated by the SVMR, CART, RF and ANN models and the actual marketing live weight were determined as 0.82, 0.82, 0.82 and 0.84, respectively. 
 
Result: The best prediction for the marketing live weight of Morkaraman lambs in the 4th month was obtained from the ANN model. Using artificial neural networks to determine the marketing weight of lambs can save time and labor because of the reduced number of weighings. It may improve decisions made in flock management.

Estimation of Marketing Live Weight of Lambs by Different Machine Learning Algorithms

Domestic work animals exist in all regions of the world. In India, the energy for ploughing two-thirds of the cultivated area comes from animal power and they haul up to 15 per cent of the total freight in the available 14 million animal drawn carts. Thus the stock of 60 million working cattle and buffaloes were used for various agricultural operations, saving fossil fuel worth Rs 60 billion, annually. With nearly 83 million land holding (more than 75% of the land holding) being less than 2 ha in size, the animal power can play a very important role in Indian agriculture. But the cropping season in India generally lasts for only 30 days during kharif and 30 days in during rabi or a total of 60 days in a year. Atleast 200 days of work was necessary to get the breakeven point considering the cost of maintenance and market hire rate for draught animals. The annual use of Draught Animal Power should be expanded through haulage and rotary mode of operation for agro processing and electricity generation and the new research findings should be communicated to the farmers through training.

Studies on draftability and enhanced utilization of small size bullocks of Odisha for pulling improved steel cart on tar road

Estimation of Marketing Live Weight of Lambs by Different Machine Learning Algorithms

Relevance of draught cattle power and its future prospects in India : A review