Agricultural Research Management Information System

Home
Research Summary
Search
About Us
- ARMIS
- Brochure
Contact Us
Report
User Request
Data Input
Help
- Operation Manual
  - PDF
  - Video
- Program Area & Commodity
We have reached 37600 number of research entries at this moment.

- Logout

Research Detail

Home
Research
Detail

Novel Technology for Lai and Yield Prediction of Crops: an Application to Oil Palm

M A Awal
Dept. of FPM, BAU, Mymensingh

Abstract/ Executive Summary:

Leaf Area Index (LAI) is an important index which is related to crop growth, crop metabolism, accumulation of dry matter and yield. It is also related to crop quality and maturity. Accurate and fast non-destructive measurements of LAI of crop canopies are essential to environmental applications such as water and carbon cycle modeling and growth monitoring. Direct methods are time consuming, difficult, laborious, and costly. Indirect methods for determining are generally less time consuming as well as non-destructive. In the past few years, a number of systems for making indirect canopy structural estimates have become commercially available. However, all these instrument either expensive or give inaccurate results of oil palm LAI. The capability to predict the yield of crops allows producers, farm manager, economic agencies, and buyers to make decisions with respect to crop management, pricing, and available markets. The concept of yield prediction from leaf area index measurement and incorporated with computer simulation model is a new and challenging perception for agricultural engineers. Computer simulation models have become an alternative source of information and replacing or enhancing information derived from costly and arduous field experiments, specially like oil palm where filed experiment are expensive, time consuming and laborious. A computer simulation model was developed using Visual C++ for simulation of leaf area index and yield of oil palm. Leaf area index and growth were modelled based on OPSIM approach. A significantly relationship was found between the simulated leaf area index (LAI) and simulated yield, and actual LAI. The simulated LAI could be integrated with the photographic LAI for forecasting the oil palm yield. Based on this complex simulation results, a new smart computer vision system was developed incorporated with web came and special lens. Developed robust user friendly software is attached with macro PC for this system. This Smart Vision System would be potential for measuring Leaf Area Index (LAI) as well as could be used to estimate Gap Fraction (GF) and future yield of crops

Keywords: Novel technology, Lai, Yield, Prediction of crops, Oil palm

Location: BAU, Mymensingh

Start Date:

End Date:

Program Area: Crop-Soil-Water Management

Commodity: Palm oil

Objectives:

To develop a computer algorithm with GUI for LAI and yield prediction of oil palm.

Methodology:

Solar radiation is the major driven factor for physical growth and development of the Oil Palm. The physical yield of an oil palm can be determined by dry matter production, dry matter distribution and the dry matter content of the harvest able organs. Dry matter production is driven by physiological processes, such as gross photosynthesis, maintenance respiration and conversion of assimilate into biomass. In the short term, environmental conditions affect these processes in different ways: light influences gross photosynthesis and temperature affects mostly maintenance respiration. Leaf area is an important determinant of light interception. Growth of the leaves is a function of the total dry matter production and the fraction of dry matter partitioned into the leaves. The growth of the oil palm can be divided into two parts such as, vegetative growth and reproductive growth. In other words, total dry matter consists of vegetative dry matter and bunch dry matter, which is consider as a yield of oil palm. Fresh fruit bunch (FFB) consist of kernel, mesocarp oil and non-oil part, which are usually sold on a fresh weight basis. A dynamic model is presented to simulate the growth and development of the oil palm. The growth and development of oil palm was simulated based on the quantification of physiological processes and environmental factors. It is assumed that the oil palm growth is the difference between photosynthetic gains and respiratory losses. The photosynthetic gains were calculated from light absorption and leaf photosynthesis parameters using a computer algorithm. Consequently, respiration losses were estimated separately for maintenance of existing biomass and losses from the transportation and subsequent conversion of remaining assimilates into structural dry matter. The most important component in the oil palm carbon budget, which is also the most difficult component to estimate, particularly in perennials crop where there is an accumulation of metabolically inactive stem tissue. A new software was developed for hemispherical image analysis by using Visual Basic. This software was incorporated with newly design instrument. This study shows the schematic parts of the new instrument for LAI and yield estimation of oil palm. The instrument consists of high mega pixel web camera, special lens (fish-eye), macro pc with touch screen and necessary other accessories.

Source of Information: Joumal ol Agricultural Engineerirng,The lnstitution of Engineers, Bangladesh, Vol. 34/AE, June 2008

Article Link (Online Journal):

Funding Source:

Total Budget (Tk.) :

Achievement/Findings:

The model, developed in this study was a physiological model, explaining the processes of growth and yields formation in oil palm from the underlying processes of photosynthesis, respiration and assimilates partitioning. These explanatory models are primarily tools in research on the influence of environmental factors and plant characteristics on crop growth and yield. This model (software) could be a research tool, teaching tool and prediction of future yield. The software also could be useful for referencing LAI and yield values. However, there is a good opportunity to future improve the model by including other factors that greatly affect LAI and yield. There is an opportunity to use this technology in various field crops, industrial crops and forest research in Bangladesh. The developed instrument and software need to verification and validation by filed experiment in Bangladesh condition.

Knowledge Management: Journal