• Journal of Sericultural and Entomological Science
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• v.16 no.2
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• pp.1-34
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• 1974

These experiments pertain to various factors influencing the quantitative characters of cocoon crops in summer and early autumn seasons. Initially, in order to establish the possible ways of the silkworm rearing more than three times a year in Korea, the author attempted to get further information about the various factors affecting the cocoon crop in every silkworm rearing season. The trials were conducted eleven times a year at four places for three years. The field trial was conducted with 19 typical sericultural farmers who had been surveyed. At the same time the author statistically analyzed the various factors in close relation to tile cocoon crop in autumn season. The effect of guidance on 40 sericultural farmers was analyzed, comparing higher level farmers with lower level farmers ; and the author surveyed 758 non-guided farmers near the guided farmers during both spring and autumn seasons. In addition, another trial on the seasonal change of leaf quality was attempted with artificial diets prepared with leaves grown in each season. It was found that related factors to cocoon crops in summer and early autumn seasons appeared to be leaf quality, and temperature for young and grown larvae. A 2$^4$ factorial experiment was designed in summer season, and another design with one more level of varied temperature or hard leaf added to a 24 factorial experiment was conducted in early autumn. The experimental results can be summarized： 1. Study on the cocoon crops in the different rearing seasons 1) It was shown that earlier brushing of silkworm generally produced the most abundant cocoon crop in spring season, and earlier or later than the conventional brushing season, especially earlier brushing was unfavorable for the abundant cocoon crop in autumn season. 2) The cocoon crop was affected by the rearing season, and decreases in order of sire with spring, autumn, late autumn, summer and early autumn seasons. 3) It was Proved that ordinary rearing and branch rearing were possibles 4 times a year ; in the 1st, 3rd, 8th, and 10th brushing season. But the 11th brushing season was more favorable for the most abundant cocoon crop of branch rearing, instead of the 10th brushing season with ordinary rearing. 2. Study on the main factors affecting the cocoon crop in autumn season 1) Accumulated pathogens were a lethal factor leading to a bad cocoon crop through neglect of disinfection of rearing room and instruments. 2) Additional factors leading to a poor cocoon crop were unfavorable for rearing temperature and humidity, dense population, poor choice of moderately ripened leaf, and poor feeding techniques. However, it seemed that there was no relationship between the cocoon crop and management of farm. 3) The percentage of cocoon shell seemed to be mostly affected by leaf quality, and secondarily affected by the accumulation of pathogens. 3. Study on the effect of guidance on rearing techniques 1) The guided farms produced an average yearly yield of 29.0kg of cocoons, which varied from 32.3kg to 25.817g of cocoon yield per box in spring versus autumn, respectively. Those figures indicated an annual average increase of 26% of cocoon yield over yields of non-guided farmers. An increase of 20% of cocoon yield in spring and 35% of cocoon yield in autumn were responsible. 2) On guided farms 77.1 and 83.7% of total cocoon yields in the spring and autumn seasons, respectively, exceeded 3rd grade. This amounted to increases of 14.1 and 11.3% in cocoon yield and quality over those of non-guided farms. 3) The average annual cocoon yield on guided farms was 28.9kg per box, based on a range of 31.2kg to 26.9kg per box in spring and autumn seasons, respectively. This represented an 8% increase in cocoon yield on farms one year after guidance, as opposed to non-guided farms. This yield increase was due to 3 and 16% cocoon yield increases in spring and autumn crops. 4) Guidance had no effect on higher level farms, but was responsible for 19% of the increases in production on lower level farms. 4. Study on the seasonal change of leaf quality 1) In tests with grown larvae, leaves of tile spring crop incorporated in artificial diets produced the best cocoon crop; followed by leaves of the late autumn, summer, autumn, and early autumn crops. 2) The cocoon crop for young larvae as well as for grown larvae varied with the season of leaf used. 5. Study on factors affecting the cocoon crops in summer and early autumn A. Early autumn season 1) Survival rate and cocoon yield were significantly decreased at high rearing temperatures for young larvae 2) Survival rate, cocoon yield, and cocoon quality were adversely affected by high rearing temperatures for grown larvae. Therefore increases of cocoon quantity and improvement of cocoon quality are dependent on maintaining optimum temperatures. 3) Decreases in individual cocoon weight and longer larval periods resulted with feeding of soft leaf and hard leaf to young larvae, but the survival rate, cocoon yield and weight of cocoon shell were not influenced. 4) Cocoon yield and cocoon quality were influenced by feeding of hard leaf to grown larvae, but survival rate was not influenced by the feeding of soft leaf and hard leaf. 5) When grown larvae were inevitably raised at varied temperatures, application of varied temperature in the raising of both young and grown larvae was desirable. Further research concerning this matter must be considered. B. Summer season 1) Cocoon yield and single cocoon weight were decreased at high temperatures for young larvae and survival rate was also affected. 2) Cocoon yield, survival rate. and cocoon quality were considerably decreased at high rearing temperatures for grown larval stages.

• Journal of Korean Society of Forest Science
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• v.70 no.1
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• pp.7-16
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• 1985

To grasp canonical correlations, their related backgrounds in various growth factors of stem, the characteristics of stem by synthetical dispersion analysis, principal component analysis and canonical correlation analysis as optimum method were applied to Larix leptolepis. The results are as follows; 1) There were high or low correlation among all factors (height ($x_1$), clear height ($x_2$), form height ($x_3$), breast height diameter (D. B. H.: $x_4$), mid diameter ($x_5$), crown diameter ($x_6$) and stem volume ($x_7$)) except normal form factor ($x_8$). Especially stem volume showed high correlation with the D.B.H., height, mid diameter (cf. table 1). 3) (1) Canonical correlation coefficients and canonical variate between stem volume and composite variate of various height growth factors ($x_1$, $x_2$ and $x_3$) are ${\gamma}_{u1,v1}=0.82980^{**}$, $\{u_1=1.00000x_7\\v_1=1.08323x_1-0.04299x_2-0.07080x_3$. (2) Those of stem volume and composite variate of various diameter growth factors ($x_4$, $x_5$ and $x_6$) are ${\gamma}_{u1,v1}=0.98198^{**}$, $\{{u_1=1.00000x_7\\v_1=0.86433x_4+0.11996x_5+0.02917x_6$. (3) And canonical correlation between stem volume and composite variate of six factors including various heights and diameters are ${\gamma}_{u1,v1}=0.98700^{**}$, $\{^u_1=1.00000x_7\\v1=0.12948x_1+0.00291x_2+0.03076x_3+0.76707x_4+0.09107x_5+0.02576x_6$. All the cases showed the high canonical correlation. Height in the case of (1), D.B.H. in that of (2), and the D.B.H, and height in that of (3) respectively make an absolute contribution to the canonical correlation. Synthetical characteristics of each qualitative growth are largely affected by each factor. Especially in the case of (3) the influence by the D.B.H. is the most significant in the above six factors (cf. table 2). 3) Canonical correlation coefficient and canonical variate between composite variate of various height growth factors and that of the various diameter factors are ${\gamma}_{u1,v1}=0.78556^{**}$, $\{u_1=1.20569x_1-0.04444x_2-0.21696x_3\\v_1=1.09571x_4-0.14076x_5+0.05285x_6$. As shown in the above facts, only height and D.B.H. affected considerably to the canonical correlation. Thus, it was revealed that the synthetical characteristics of height growth was determined by height and those of the growth in thickness by D.B.H., respectively (cf. table 2). 4) Synthetical characteristics (1st-3rd principal component) derived from eight growth factors of stem, on the basis of 85% accumulated proportion aimed, are as follows; Ist principal component ($z_1$): $Z_1=0.40192x_1+0.23693x_2+0.37047x_3+0.41745x_4+0.41629x_5+0.33454x_60.42798x_7+0.04923x_8$, 2nd principal component ($z_2$): $z_2=-0.09306x_1-0.34707x_2+0.08372x_3-0.03239x_4+0.11152x_5+0.00012x_6+0.02407x_7+0.92185x_8$, 3rd principal component ($z_3$): $Z_3=0.19832x_1+0.68210x_2+0.35824x_3-0.22522x_4-0.20876x_5-0.42373x_6-0.15055x_7+0.26562x_8$. The first principal component ($z_1$) as a "size factor" showed the high information absorption power with 63.26% (proportion), and its principal component score is determined by stem volume, D.B.H., mid diameter and height, which have considerably high factor loading. The second principal component ($z_2$) is the "shape factor" which indicates cubic similarity of the stem and its score is formed under the absolute influence of normal form factor. The third principal component ($z_3$) is the "shape factor" which shows the degree of thickness and length of stem. These three principal components have the satisfactory information absorption power with 88.36% of the accumulated percentage. variance (cf. table 3). 5) Thus the principal component and canonical correlation analyses could be applied to the field of forest measurement, judgement of site qualities, management diagnoses for the forest management and the forest products industries, and the other fields which require the assessment of synthetical characteristics.