Browsing by Author "Bundit Jarimopas"

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    An automatic trimming machine for young coconut fruit
    (2009) Bundit Jarimopas; Nuttapong Ruttanadat; Anupun Terdwongworakul
    A prototype automatic young coconut fruit trimming machine was designed, constructed, tested and evaluated. The mechanism used features a sharp inclined knife which operates in translation motion in a vertical plane to trim the fruit, which is clamped tightly and rotates about a vertical axis. Machine components include a main frame, a body-trimming station, a shoulder-trimming station, a base-cutting station, a rotary base, three fruit holders, an electrical connection slip ring, a power drive and programmable electronic control. In experiments, the untrimmed fruit was continuously fed into three separate fruit holders. These in turn conveyed the coconut through the body-trimming, shoulder-trimming and base-cutting stations. The fruit holders continuously travelled in a circle encompassing every station in sequence. Optimal settings included (a) feeding rate of 86 fruit h 1, (b) 300 rpm rotation of the trimmed fruit, and (c) a shoulder knife height of 180 mm. Average loss rates were 0.35%, for the fibrous area, 2.5% for fruit damage and 14.5% for the untrimmed green area. The optimally trimmed fruit was accepted by growers and traders.
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    Development and testing of a husking machine for dry betel nut (Areca Catechu Linn.)
    (2009) Bundit Jarimopas; Suttiporn Niamhom; Anupun Terdwongworakul
    A prototype betel nut husking machine was designed, constructed, tested and evaluated. The design concept was to tear-off the husk of the dry betel nut by exerting differing dynamic friction forces on opposite sides of the nut via normal pressure. The prototype featured a hopper into which dry betel nuts were fed, a husking mechanism, and a power drive. The husking mechanism was composed of two identical husking wheels mounted in series. Each husking wheel consisted of a rubber tyre and a concave sieve constructed from steel rods. The dry betel nut was fed into the space between the running tyre surface and the sieve surface of the husking mechanism. When the nut passed through the first wheel, the combined compression and friction force crushed the nut husk and loosened the nut. The husk and nut were further separated by repeating the operation with a second tyre. Results showed that (a) the optimum machine settings, identified by the greatest production score (PS), were characterised by a tyre pressure of 138 kPa, a tyre speed of 440 rpm, and a 15mm spacing between the surfaces of the tyre and the sieve; (b) the optimal betel nut fruit moisture content was 6.31% w.b. Performance testing of the prototype based on the optimum settings produced the following results: optimally husked full nuts (64.4%); broken nuts (15.2%); unhusked nuts (20.5%). Thus, the PS was 76.9%
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    Physical properties of fresh young Thai coconut for maturity sorting
    (2009) Anupun Terdwongworakul; Songtham Chaiyapong; Bundit Jarimopas; Weerakul Meeklangsaen
    Young mature coconut is a widely consumed fruit consisting of soft white flesh and sweet white transparent aromatic juice. Judging the maturity of young coconut is difficult and thus a harvested crop typically features fruit of varying levels of maturity, which currently require manual grading. In an attempt to help reduce the time and costs associated with the grading process, the correlations between the physical, mechanical, physiological and acoustic properties of coconuts and their maturity levels were investigated. The analyses showed that specific gravity, husk rupture force and husk firmness showed a decreasing trend with progressing days after pollination. Other properties including resonant frequency, shell rupture force, shell firmness, total soluble solids, flesh thickness, wet flesh weight and dry flesh weight indicated an increase in values with days after pollination. The flesh thickness was the parameter best correlated with days after pollination. Maturity index based on the flesh thickness can be quantitatively predicted by multivariate partial least squares model. The best model used a combination of husk rupture force, shell firmness, shell rupture force, wet flesh weight and husk firmness (R2 ¼ 0.991, standard error of prediction of 0.133 and bias of 0.004). A non-destructive model based on resonant frequency gave relatively good accuracy of prediction with R2 ¼ 0.927, standard error of prediction 0.386 and bias of 0.034