G.V. Prasanna Kumar

Noise exposure in oil mills.

Context: Noise of machines in various agro-based industries was found to be the major occupational hazard for the workers of industries. The predominant noise sources need to be identified and the causes of high noise need to be studied to undertake the appropriate measures to reduce the noise level in one of the major agro-based industries, oil mills. Aims: To identify the predominant noise sources in the workrooms of oil mills. To study the causes of noise in oil mills. To measure the extent of noise exposure of oil mill workers. To examine the response of workers towards noise, so that appropriate measures can be undertaken to minimize the noise exposure. Settings and Design: A noise survey was conducted in the three renowned oil mills of north-eastern region of India. Materials and Methods: Information like output capacity, size of power source, maintenance condition of the machines and workroom configurations of the oil mills was collected by personal observations and enquiry with the owner of the mill. Using a Sound Level Meter (SLM) (Model-824, Larson and Davis, USA), equivalent SPL was measured at operators ear level in the working zone of the workers near each machine of the mills. In order to study the variation of SPL in the workrooms of the oil mill throughout its operation, equivalent SPL was measured at two appropriate locations of working zone of the workers in each mill. For conducting the noise survey, the guidelines of Canadian Centre for Occupational Health and Safety (CCOHS) were followed. Grid points were marked on the floor of the workroom of the oil mill at a spacing of 1 m × 1 m. SPL at grid points were measured at about 1.5 m above the floor. The direction of the SLM was towards the nearby noisy source. To increase accuracy, two replications were taken at each grid point. All the data were recorded for 30 sec. At the end of the experiment, data were downloaded to a personal computer. With the help of utility software of Larson and Davis, USA, equivalent SPL and noise spectrum at each reading was obtained. Noise survey map of equivalent SPL was drawn for each oil mill by drawing contour lines on the sketch of the oil mill between the points of equal SPL. The floor area in the oil mill where SPL exceeded 85 dBA was identified from the noise survey map of each oil mill to determine the causes of high level of noise. Subjective assessment was done during the rest period of workers and it was assessed with personal interview with each worker separately. Demographic information, nature of work, working hours, rest period, experience of working in the mill, degree of noise annoyance, activity interference, and psychological and physiological effects of machine noise on the worker were asked during the interview. These details were noted in a structured form. Statistical Analysis Used: Nil. Results: The noise survey conducted in three renowned oil mills of north-eastern region of India revealed that about 26% of the total workers were exposed to noise level of more than 85 dBA. Further, 10% to 30% floor areas of workrooms, where oil expellers are provided have the SPL of more than 85 dBA. The noise in the oil mills was dominated by low frequency noise. The predominant noise sources in the oil mills were seed cleaner and power transmission system to oil expellers. Poor maintenance of machines and use of bamboo stick to prevent the fall of belt from misaligned pulleys were the main reason of high noise. Noise emitted by the electric motor, table ghani and oil expellers in all the oil mills was well within 85 dBA. Subjective response indicated that about 63% of the total workers felt that noise interfered with their conversation. About 16% each were of the opinion that noise interfered in their work and harmed their hearing. About 5% of workers stated that the workroom noise gave them headaches. Conclusions: The workers engaged in the workrooms of the oil mills are exposed to high noise, which will have detrimental effect on their health. The poor maintenance of drive system was found to be the main reason for high noise level.

Volume of Vermicompost-Based Potting Mix for Vegetable Transplants Determined Using Fuzzy Biomass Growth Index

Good quality transplants are necessary so that plants will survive and produce at acceptable levels. The efficacy of vermicompost for vegetable transplant development needs to be clarified. An investigation was conducted to identify the mix and volume of vermicompost-based potting mixes required for production of good quality transplants of tomato (Solanum lycopersicum L.), eggplant (S. melongena L.), and chili pepper (Capsicum frutenscens L.) in paper pots. Five levels of potting mix made of vermicompost:sand:topsoil with the vermicompost proportion ranging from 20% to 50% were used. Paper pots made of 50 g·m−2 recycled newspaper with volumes of 51, 65, 81 and 100 cc were tested. Transplant quality was evaluated using a fuzzy logic based biomass growth index (BGI). The performance of the BGI and root:shoot ratio representing morphology of seedlings just prior to transplanting was compared. Seedlings could be better categorized using BGI than the root:shoot ratio. Paper pots of 65 cc in volume filled with a mix of 25% vermicompost, 100 cc in volume filled with a mix of 50% vermicompost, and 81 cc in volume filled with a mix of 33% vermicompost, in combination with equal parts of sand and top soil were most suitable for production of good quality transplants of tomato, eggplant, and chili pepper, respectively.

Vegetable Transplanters for Use in Developing Countries—A Review

ABSTRACT Developing countries contribute 72% of the total vegetable production in the world. The transplanting operation is one of the most labor intensive in vegetable production. It is largely done by hand in India and most developing countries and incurs large investments in labor, time, and cost. This article presents the details of construction of vegetable transplanters in addition to recent advances in their development. Performance of transplanters under actual field conditions is discussed.

IDENTIFICATION OF OPTIMUM COMBINATION OF PROPORTION OF VERMICOMPOST IN THE SOIL-BASED POTTING MIX AND POT VOLUME FOR THE PRODUCTION OF PAPER POT SEEDLINGS OF VEGETABLES

An investigation was conducted to identify the best combination of proportion of vermicompost in soil-based potting mix and pot volume for the production of paper pot seedlings suitable for mechanical transplanting. The best combination of the potting mix and pot volume is the one that produces seedlings with high growth of root and shoot biomasses at the end of seedling stage, low in cost and light in weight. Cubical shaped paper pots of 50 cm3 volume filled with potting mix of 25% vermicompost and 75% soil and sand in equal proportion by volume was found to be best for the large scale production of paper pot seedlings of tomato, eggplant, and chili peppers. The paper pots were found to be firm at the end of seedling stage and variations in their dimensions could be accommodated in fully automatic transplanters with horizontal chain conveyor type seedling feeding and metering devices.

Development of artificial neural network models for the performance prediction of an inclined plate seed metering device

Seed planting equipment with inclined plate seed metering devices is the most commonly used equipment for planting of peanut crop in India. For obtaining the high yield, it is very essential to drop the peanut seeds in rows maintaining accurate seed rate and seed spacing with minimum damage to seeds during metering. This mainly depends on the forward speed of the planting equipment, rotary speed of the metering plate and the area of cells on the plate. The relationship between these factors and the performance parameters viz., seed rate, seed spacing and percent seed damage can be established using regression analysis. But they may not be very accurate and consistent throughout the solution space. Hence, an attempt has been made in this paper to develop the feed forward artificial neural network (ANN) models for the prediction of the performance parameters of an inclined plate seed metering device. The data were generated in the laboratory by conducting experiments on a sticky belt test stand provided with a seed metering device and an opto-electronic seed counter. The generated data was used to develop both statistical and neural network models. The optimum architecture of the neural network models was determined using genetic algorithm (GA) as a single objective constrained optimization problem. The performance of the developed models was compared among themselves for 4 randomly generated test cases. The results show that the ANN model predicted the performance parameters of the seed metering device better than the statistical models. It is possible to determine the optimum levels of the input parameters to obtain the desired performance parameters of the seed metering device by performing reverse mapping of the developed ANN models.

Standardization of Potting Mix and Pot Volume for the Production of Vegetable Seedlings in Paper Pot

Effect of four different proportions of farmyard manure (FYM) in a soil based mix and three different pot volumes on growth of tomato, eggplant and chili peppers in paper pots were studied. Recycled newspaper (density 50 g m−2) was used to prepare pots of volume 45, 82, and 126 cm3. Potting mixes made up of FYM, sand and soil with the FYM proportion ranging from 20% to 80% in equal proportion of sand and top soil were used. Seedling height and dry weight were measured at the end of the seedling stage. The best combination of potting mix and pot volume for the large scale production of seedlings was identified using non-dominated sorting technique. Paper pots of volume 82 cm3 filled with a mix of 80% FYM and rest 20% with equal proportions of sand and top soil were found to be the best option for the large scale production of paper pot seedlings.

Production of Soil Block Seedlings in Plug Trays for Mechanical Transplanting

ABSTRACT Establishing vegetables in the field using mechanical transplanters with only plant metering devices requires transplants with heavy soil blocks around the roots. An investigation was conducted to study the effects of amount of vermicompost in a soil-based potting mix and initial compaction of the mix on growth of seedlings and soil block strength for mechanical transplanting. Seedlings of Tomato (Solanum lycopersicum L.), Eggplant (S. melongena L.), and Chili pepper (Capsicum frutenscens L.) were produced in two seasons in plastic plug trays with a potting medium in which vermicompost made up 20%–50% by volume in 60 and 100 cc tray cells. Potting mix with 20% vermicompost by volume in soil in 100 cc cells produced good growth of tomato and chili pepper transplants in season 1. Potting mix containing 20%–30% and 20%–40% vermicompost in soil in 100 cc cells produced good growth of tomato and chili pepper transplants, respectively, in season 2. Potting mix with 30%–40% and 30% vermicompost by volume in soil in 100 cc cells produced good growth of eggplant seedlings in seasons 1 and 2, respectively. The effects of initial compaction of potting mix on water requirement, plant height, and soil block strength was studied for the production of tomato seedlings. Potting mix with 30% vermicompost in 100 cc tray cells and initially compacted to the dry density of 0.88–0.90 g·cm−3 was most suitable for production of seedlings of sufficient height and soil block strength for mechanical transplanting.

Development of a Hopper-Type Planting Device for a Walk-Behind Hand-Tractor-Powered Vegetable Transplanter

Purpose: In order to ensure that vegetable seedlings (with a soil block around their roots) are planted in an upright orientation after metering in a vegetable transplanter, they need to be dropped freely from a certain height. The walk-behind hand-tractor-powered machines do not have sufficient space to drop the seedlings from that height. In the present work, a hopper-type planting device was developed for the walk-behind hand-tractor-powered vegetable transplanter to ensure that the soil block seedlings are planted in an upright orientation. Methods: Various dimensionless terms were developed based on the dimensional analysis approach, and their effect on the planting of soil block seedlings in an upright orientation (planting efficiency) was studied. The optimum design dimensions of the hopper-type planting device were identified by the Taguchi method of optimization. Results: The ratio of the height of free fall to the sliding distance of the seedling on the surface of the hopper had the highest influence on planting efficiency. The planting efficiency was highest for plants with a height . The plant handling Froude number, in interaction with the design of the hopper-type planting device, also significantly affected the planting efficiency. Of the hopper design factors, the length of the slide of the seedlings on the surface of the hopper was most important, and induced sufficient velocity and rotation to cause the seedling to fall in an upright orientation. An evaluation of the performance of the planting device under actual field conditions revealed that the planting efficiency of the developed planting device was more than 97.5%. Conclusions: As the seedlings were fed to the metering device manually, an increase in planting rate increased missed plantings. The planting device can be adopted for any vegetable transplanter in which the seedlings are allowed to drop freely from the metering device.

Hand-Fed Vegetable Transplanter for Use with a Walk-Behind-Type Hand Tractor

ABSTRACT In smallholdings and market gardens in India and other Asian countries, walk-behind hand-controlled tractors are the major source of farm power. Conventional manual transplanting of bare root vegetable seedlings is labor intensive and time consuming, and there exists a need for mechanical transplanting using a hand-controlled tractor as the source of power. A two-row vegetable transplanter for transplanting soil block seedlings was developed as matching equipment for a walk-behind hand tractor. Field performance, quality of work, cost of operation, and yield were compared with conventional manual transplanting of bare root seedlings using a row marker and hand hoe. Soil block seedlings were placed on a metering conveyor of the transplanter by two laborers who also maneuvered the hand tractor. Seedlings were carried by the horizontal chain conveyor to a hopper-type planting device that planted seedlings in an upright orientation. The planting rate of the transplanter was 31 plants·min−1 with a maximum of 2.75% missed plantings and 3.38% tilted plantings. The field capacity of the transplanter was 0.045 ha·h−1 for transplanting Tomato (Solanum lycopersicum L) and Chilli Pepper (Capsicum annuum L.) at an inter- and within-row spacing of 45 cm and 0.06 ha·h−1 for transplanting Eggplant (S. melongena L.) in an inter- and within-row spacing of 60 cm. The vegetable transplanter was efficient for planting soil block seedlings of tomato, eggplant, and chilli pepper with plant heights of 13–17, 11–15, and 10–14 cm with 8–10, 4–6, and 8–10 leaves, respectively. Cost of soil block seedlings accounted for 77%–83% of total cost of mechanical transplanting. The vegetable transplanter has the potential of saving 83%–85% of time involved with seedling establishment and 66%–69% labor involved in conventional transplanting in market gardens. Mechanical transplanting decreased number of days to harvest, with total yield slightly higher than that of conventional transplanting. The vegetable transplanter holds promise for use in market gardens and smallholdings for faster transplanting, earlier growth, and higher yield of vegetables.

Forward and reverse mapping of extreme learning machine model of a precision planter

The extreme learning machine (ELM) regression model was developed to predict the performance parameters of a pneumatic planter. The diameter of the metering disc hole, suction and peripheral speed of the disc were the independent parameters, and miss index, multiple index and precision is seed spacing were the dependent parameters. Single hidden layer of 15 nodes with sigmoid activation function in the hidden layer and linear function in the output layer was taken. The ELM predicted the performance of the pneumatic planter with mean square error of 0.708. The ELM developed was reverse mapped to identify the optimum levels of independent parameters to achieve the lowest miss and multiple indices, and precision in seed spacing. The reverse mapping of the ELM resulted in 3 solutions, and they can be adopted in the actual precision planter. The forward and reverse mapping of the ELM regression model was found to be effective in prediction of performance and optimization of the design and operational parameters of the planting equipment.