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Simulation of Harvesting Schedule for Large Scale Tomato Cultivation

Fatima Rukshana
Graduate Student
Department of Farm Power and Machinery, Bangladesh Agricultural University, Mymensingh, Bangladesh

A. T. M. Ziauddin
Professor
Department of Farm Power and Machinery, Bangladesh Agricultural University, Mymensingh, Bangladesh

Abstract/ Executive Summary:

A harvesting model was developed to get the optimum harvesting schedule of tomato ("Ratan" variety). Tomato harvesting system can be represented as a process of several interrelated operations. Tomato spoilage due to delay of harvest, farm productivity, laborer wages and price of tomato has highly significant effects on this process. The model consists of two major components, Tomato Spoilage Sub-model and Harvesting Cost Sub-model. The Tomato Spoilage Sub-model simulates the amount of total tomato spoilage due to delay of harvest. The harvesting cost of the entire harvesting season was calculated by the Harvesting Cost Sub-model. The total cost minimization technique was used as an optimization criterion of the model. The optimum harvest intervals for "Ratan" variety of tomato during early harvest, peak harvest and late harvest period were obtained at 4, 2 and 2 days, respectively.

Keywords: Harvesting, Large scale, Model, Cultivation, Tomato

Location: Sultana Razia Hall, Bangladesh Agricultural University, Mymensingh

Start Date: 00-10-1997

End Date: 00-04-1998

Program Area: Postharvest and Agro-processing

Commodity: Tomato

Objectives:

1. To determine the spoilage characteristics of "Ratan" variety of tomato,

2. To develop a harvesting model and

3. To determine the optimal harvesting schedule for "Ratan" variety of tomato.

Methodology:

The experiment was conducted inside the fallow land of Sultana Razia Hall of Bangladesh Agricultural University. Mymensingh during the period from October 1997 to April 1998. The soil of the experimental area was sandy loam in texture and belongs to the Rrahmaputra alluvium tract. The selected land was opened on 12 October 1997. The land was prepared by a spade. All weeds and stables were removed and the land was finally prepared through addition of biomass fertilizer (cowdung). The size of the experimental plot was 10 m x 2.6 m where "Ratan" variety of tomato seedlings was transplanted on the same day. One hundred healthy seedlings were transplanted in the experimental plot in the afternoon of 27 October 1997, maintaining row to row distance of 0.65 m and plant to plant distance of 0.50 m. After transplantation, the seedlings were properly watered. Arrangement was trade to protect the seedlings from sunshine using paper sheets. When the plants were well established, the soil around the base of each plant was pulverized. Mechanical support was given to the growing plants by bamboo sticks to keep them erect. Three times weeding and two times light irrigation were practiced as and when found necessary. The tomato plants and the tomatoes were kept under careful observation regularly. Everyday, during experimentation, the matured and unmatured condition was observed and the amount of damaged tomato was recorded. The maturity of tomato was determined on the basis of light reddish coloring of it. The first day of harvest Season was considered here as the day when a mature tomato turned for the first time in to light reddish color. When the tomatoes were found light red, the time was considered for harvesting of tomato and record was maintained. When the tomatoes were over ripped or damaged due to bird and insect infestation or fallen from plant on the ground, these tomatoes were collected, weighted and recorded for the day. Individual tomato weight (gm), yield of tomato per plant (kg/tree), yield per hectare, and loss of tomato per hectare were also calculated. Data collection was started on 17 February and was completed by 28 April 1998. A model is a simplified representation of a real system. The following assumptions have been made in modeling of the harvesting system of tomato. 1. The effect of unfavorable weather on tomato harvesting system was neglected. 2. Laborer was readily available for harvest. 3. The harvesting season was divided into three sections -- early harvest, peak harvest and late harvest periods. The model consists of two major components; Tomato Spoilage Sub-model and Harvesting Cost Sub-model. The Tomato Spoilage Sub-model simulates the value of total tomato spoilage due to delay of harvest. The harvesting cost of the entire harvesting season was calculated by the Harvesting Cost Sub-model. The total harvesting cost and the value of total tomato spoilage depends on harvesting frequency. The Tomato Spoilage Sub-model simulates the amount of tomato spoilage due to delay of harvest during the harvesting season. The tomato spoilage depends largely on proper time of harvest, drop out, bird and insect infestation. It was observed during the field experiment that the total tomato harvesting period was 68 days. From first day of the harvesting season 1 to 32 days, 33 to 55 days, 56 to 68 days were considered as Labor cost is the most significant cost element of the Harvesting Cost Sub-model. The harvesting cost mainly depends on harvest interval, productivity of the farm, area of the farm and labor wage and time required to harvest a certain area by a single laborer. The complete model was coded in the QUICK BASIC language and was complied, loaded and run on a micro computer. Number of days in the harvesting season, labor cost, productive area of the farm, time required to harvest the area, price of tomato and harvest interval were the important input data of the model. The computer program of the model was run for different values of harvest interval until the minimum total harvesting cost was obtained.

Source of Information: Journal of the Institution of Engineers, Bangladesh; Agricultural Engineering Division, Vol. 25/AE. No.1, Dec.1998

Article Link (Online Journal):

Funding Source:

Total Budget (Tk.) :

Achievement/Findings:

The Tomato harvesting model adequately represents the tomato harvesting system. It could be used to determine the optimal harvesting schedule for medium and large scale tomato farms. The model can also be successfully used in harvest planning of crops like lettuce, chilli, brinjal, cauliflower etc., with a minor modification of the model

Knowledge Management: Journal