Udompetaikul, Vasu

Preferred name

Udompetaikul, Vasu

Alternative Name

Udompetaikul, V.

Main Affiliation

School of Engineering

vasu.ud@kmitl.ac.th

Now showing 1 - 8 of 8

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Managing the almond and stone fruit replant disease complex with less soil fumigant
(2013-07-01)
Browne, Greg T.
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Lampinen, Bruce D.
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Holtz, Brent A.
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Doll, David A.
;
Upadhyaya, Shrinivasa K.
As much as one-third of California's almond and stone fruit acreage is infested with potentially debilitating plant parasitic nematodes, and even more of the land is impacted by Prunus replant disease (PRD), a poorly understood soilborne disease complex that suppresses early growth and cumulative yield in replanted almond and peach orchards. Preplant soil fumigation has controlled these key replant problems, but the traditional fumigant of choice, methyl bromide, has been phased out, and other soil fumigants are increasingly regulated and expensive. We tested fumigant and nonfumigant alternatives to methyl bromide in multiple-year replant trials. Costs and benefits were evaluated for alternative fumigants applied by shanks in conventional strip and full-coverage treatments and applied by shanks or drip in novel spot treatments that targeted tree planting sites. Short-term sudangrass rotation and prudent rootstock selection were examined as nonfumigant approaches to managing PRD. Trial results indicated that integrations of the treatments may acceptably control PRD with relatively little soil fumigant.
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Tractor-mounted, GPS-based spot fumigation system manages Prunus replant disease
(2013-10-01)
Udompetaikul, V.
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Coates, Robert W.
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Upadhyaya, Shrinivasa K.
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Browne, Greg T.
;
Shafii, Mir
Our research goal was to use recent advances in global positioning system (GPS) and computer technology to apply just the right amount of fumigant where it is most needed (i.e., in a small target treatment zone in and around each tree replanting site) to control Prunus replant disease (PRD). We developed and confirmed the function of (1) GPS-based software that can be used on cleared orchard land to flexibly plan and map all of an orchard's future tree sites and associated spot fumigation treatment zones and 2) a tractor-based GPS-controlled spot fumigation system to quickly and safely treat the targeted tree site treatment zones. In trials in two almond orchards and one peach orchard, our evaluations of the composite mapping and application system, which examined spatial accuracy of the spot treatments, delivery rate accuracy of the spot treatments, and tree growth responses to the spot treatments, all indicated that GPS spot fumigation has excellent potential to greatly reduce fumigant usage while adequately managing the PRD complex.
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Design of a laboratory-scale sugarcane weighing system
(2019-09-09)
Veerasakulwat, S.
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Udompetaikul, V.
;
Hongwiangjan, J.
Recently, sugarcane harvesters have been increasingly used in sugarcane harvesting. Loading trucks were traveling along the harvesters to collect the harvested cane billets. Since cane harvesters are expensive machines, there is an idea of collaborative farming by combining multiple fields from different owners to reduce operating costs and time. However, it is difficult to fairly classify yields from different fields. Site-specific yield monitoring system is not common in typical harvesters. Farmers only know the weight on each truck without its collecting location when selling the sugarcane to the factory. This research was the feasibility study to develop a hydraulic weighing system in laboratory scale for further applying to the side-tipping loading trucks. A low-cost hydraulic weighing system was fabricated. A microcontroller was used to read signals from pressure and gyroscopic sensors and then to calculate the applied load. Accuracy and precision of the system were examined. The coefficient of determination (R2) of the relationship between the actual and determined loads was 0.978. The standard error of prediction (SEP) of the system was 2.348 kg. The results show that there was feasibility to apply the system on farm scale; however, further study with a larger scale should be conducted.
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Determination of field capacity for the sugarcane harvester using GNSS data
(2019-09-09)
Kaewkabthong, A.
;
Udompetaikul, V.
Harvesting is an important activity in the sugar production industry. Due to the labor shortage and time limitation during harvesting season, farmers have adopted cane harvesters to substitute the farm workers in this restless period. Cane harvesters are huge and expensive machines with high field capacity. Because of inappropriate working conditions in Thailand, the actual field capacity is much lower than that in its specification. The objective of this research is to study the factors affecting the field capacity of the sugarcane harvester. A GNSS logging system was used to record the machine's position and traveling speed during operation. Crop yield for each field was also collected. Field dimension and other working parameters such as working time and the number of turns were derived from the GNSS data. A field capacity prediction model was developed. The study shows that the optimal working speed, crop yield, and the number of turns per field area were significant factors to predict the harvester's field capacity. The coefficient of determination (R2 value) of the model was 0.625. It was suggested to include more machine and field variation for further robust model development and uses in the optimization of field operation performance.
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In-line near infrared spectroscopy for the prediction of moisture content in the tapioca starch drying process
(2019-03-01)
Phetpan, Kittisak
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Udompetaikul, Vasu
;
Sirisomboon, Panmanas
Moisture content is an important parameter measured in tapioca starch production as this parameter has been shown to correlate strongly with the quality of the finished product. However, there is currently no in-line sensor which can be used to directly measure the moisture content of the product in real time. The objective of the present work was to study the use of an in-line measurement which can be introduced at the end of the drying process for tapioca starch moisture content evaluation. Either in-line NIR data or at-line NIR data was used to develop the necessary calibration models for evaluating the moisture content. Furthermore, calibration models were also developed by pooling the in-line and at-line data. Its performance was then verified using additional in-line data. The NIR model developed using 100% of the at-line data and 50% of the in-line data was validated using the unused 50% of the inline data. This model was shown to provide better performance in moisture content prediction with an SEP of 0.61% and a bias of 0.001%. In addition, the results showed that the at-line spectrum can also be used for the calibration model development to predict the moisture content of the samples scanned by an in-line spectrometer. However, the in-line spectrometer installation on a pneumatic conveying circular tube where tapioca starch and air mixed was found to be complicated due to significant vibration. This caused additional variation in the data with time. Therefore, it is concluded that the most suitable place for installing a spectrometer would be at a position involving a low pressure, or where the stream flow of a product is steadier in order to avoid the dynamic mixing of the product within the drying tube affecting the uncertainty of NIR scattering during the measurement.
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An online visible and near-infrared spectroscopic technique for the real-time evaluation of the soluble solids content of sugarcane billets on an elevator conveyor
(2018-11-01)
Phetpan, Kittisak
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Udompetaikul, Vasu
;
Sirisomboon, Panmanas
The aim of this research study is to propose a prototype online detection system based on the visible and near-infrared spectroscopic (vis/SW-NIR) technique for the real-time evaluation of the soluble solids content (SSC) of sugarcane billets on an elevator conveyor. The system consisted of two main parts, a cane billet elevator and a spectral acquisition device. An elevator speed of 2 m/s was used for the transfer of sugarcane billets. Spectra acquisition was performed using four 50 W tungsten halogen lamps as a light source in conjunction with vis/SW-NIR spectrometer in reflectance mode. Partial least squares regression (PLSR) was subsequently used to correlate the spectra with the experimentally determined SSC values. The model performance was then assessed using an independent prediction set. The model was found to display a coefficient of determination of prediction (R2) of 0.785, a root mean square error of prediction (RMSEP) of 0.30 and a residual predictive deviation (RPD) of 2.16. The result on the prediction set confirm that the proposed system is suitable for the online SSC measurement of the sugarcane billets on an elevator conveyor.
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Detection of plant water stress using leaf temperature and microclimatic measurements in almond, Walnut, and grape crops
(2014-01-01)
Dhillon, R.
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Udompetaikul, V.
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Rojo, F.
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Roach, J.
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Upadhyaya, S.
A mobile sensor suite was developed and evaluated to predict plant water status by measuring the leaf temperature and microclimatic variables in nut crop trees and grapevines. The sensor suite consists of an infrared thermometer to measure leaf temperature along with other relevant sensors to measure microclimatic variables. The sensor suite was successfully evaluated in commercial orchards in the Sacramento Valley of California on three orchard crops, i.e., almond (Prunus dulcis), walnut (Juglans regia), and grape (Vitis vinifera), for both sunlit and shaded leaves. Stepwise linear regression models developed for shaded leaf temperature yielded coefficient of multiple determination values of 0.90, 0.86, and 0.86 for almond, walnut, and grape crops, respectively. Stem water potential (SWP) was found to be a significant variable in all models. The regression models were used to classify trees into water stressed and unstressed categories. Critical misclassification errors (classifying a water stressed tree as unstressed) for sunlit and shaded leaf models were 8.8% and 5.2% for almond, 5.4% and 6.9% for walnut, and 12.9% and 8.1% for grapevine, respectively. Canonical discriminant analyses were also conducted using the sensor suite data to classify trees into water stressed and unstressed trees with critical misclassification errors for sunlit and shaded leaves of 9.3% and 7.8% for almond, 2.0% and 4.1% for walnut, and 9.6% and 1.6% for grapevine, respectively. These results show the feasibility of the sensor suite to determine plant water status for irrigation management of nut and vineyard crops© 2014 American Society of Agricultural and Biological Engineers.
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Development of an automatic tracking system to determine field efficiency of agricultural machines
(2018-08-14)
Tamrai, Natussapol
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Masarn, Boripun
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Kaewkabthong, Apidul
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Lapcharoensuk, Ravipat
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Sangchan, Songvoot
Field efficiency of machines tells how efficient the farm machines are operating in the field. Measuring of the field efficiency used to be a tedious and laborious work which is not worth to collect for further operational optimization. The objective of this study was to develop an automatic system for monitoring the field activities and then evaluation of the field efficiency of farm machines. The system consisted of a microcontroller to collect working data including position, speed heading, and working status of the machine. The system was installed on a farm tractor with plowing disc to test on two fields with the same size, but in different traveling directions, i.e., lengthwise and crosswise. The results showed lengthwise operation yielded a higher field efficiency due to less number of turning at headlands. The proposed system allowed to collect necessary information for detailed efficiency evaluation of farm machines. This technique enables further utilization of the operational information and benefit to use in the optimization of the farm works.

Udompetaikul, Vasu

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