• Journal of Korean Society of Forest Science
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• 제70권1호
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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.

• KOREAN JOURNAL OF CROP SCIENCE
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• 제17권
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• pp.1-44
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• 1974

These studies were made at Suwon in 1972 and at Suwon, Iri, and Kwangju in 1973 to investigate grain filling process and variation of grain quality of NB 68513 and Caprock as hard red winter wheat, Suke ＃169 as soft red winter wheat variety and Yungkwang as semi-hard winter variety, grown under-three different fertilizer levels and seeding dates. Other experiments were conducted to find the effects of temperature, humidity and light intensity on the grain filling process and grain quality of Yungkwang and NB 68513 wheat varieties. These, experiments were conducted at Suwon in 1973 and 1974. 1. Grain filling process of wheat cultivars: 1) The frequency distribution of a grain weight shows that wider distribution of grain weight was associated with large grain groups rather than small grain group. In the large grain groups, the frequency was mostly concentrated near mean value, while the frequency was dispersed over the values in the small grain group. 2) The grain weight was more affected by the grain thickness and width than by grain length. 3) The grain weight during the ripening period was rapidly increased from 14 days after flowering to 35 days in Yungkwang and from 14 days after flowering to 28 days in NB 68513. The large grain group, Yungkwang was rather slowly increased and took a longer period in increase of endosperm ratio of grain than the small grain group, NB 68513. 4) In general, the 1, 000 grain weight was reduced under high temperature, low humidity, while it was increased under low temperature and high humidity condition, and under high temperature and humidity condition. The effect of shading on grain weight was greater in high temperature than in low temperature condition and no definite tendency was found in high humidity condition. 5) The effects of temperature, humidity and shading on 1, 000 grain weight were greater in large-grain group, Yungkwang than in small grain group, NB 68513. Highly significant positive correlation was found between 1, 000 grain weight and days to ripening. 6) The 1, 000 grain weight and test weight were increased more or less as the fertilizer levels applied were increased. However, the rate of increasing 1, 000 grain weight was low when fertilizer levels were increased from standard to double. The 1, 000 grain weight was high when planted early. Such tendency was greater in Suwon than in Kwangju or Iri area. 2. Milling quality: 7) The milling rate in a same group of varieties was higher under the condition of low temperature, high humidity and early maturing culture which were responsible for increasing 1, 000 grain weight. No definite relations were found along with locations. 8) In the varieties tested, the higher milling rate was found in large grain variety, Yungkwang, and the lowest milling rate was obtained from Suke ＃ 169, the small grain variety. But the small grained hard wheat variety such as Caprock and NB 68513 showed higher milling rate compared with the soft wheat variety, Suke ＃ 169. 9) There were no great differences of ash content due to location, fertilizer level and seeding date while remarkable differences due to variety were found. The ash content was high in the hard wheat varieties such as NB 68513, Caprock and low in soft wheat varieties such as Yungkwang and Suke ＃ 169. 3. Protein content: 10) The protein content was increased under the condition of high temperature, low humidity and shading, which were responsible for reduction of 1, 000 grain weight. The varietal differences of protein content due to high temperature, low humidity and shading conditions were greater in Yungkwang than in NB 68513. 11) The high content of protein in grain within one to two weeks after flowering might be due to the high ratio of pericarp and embryo to endosperm. As grains ripen, the effects of embryo and pericarp on protein content were decreased, reducing protein content. However, the protein content was getting increased from three or four weeks after flowering, and maximized at seven weeks after flowering. The protein content of grain at three to four weeks after flowering increased as the increase of 1, 000 grain weight. But the protein content of matured grain appeared to be affected by daily temperature on calender rather than by duration of ripening period. 12) Highly significant positive correlation value was found between the grain protein content and flour protein content. 13) The protein content was increased under the high level of fertilizers and late seeding. The local differences of protein content were greater in Suwon than in Kwangju and Iri. 14) Protein content in the varieties tested were high in Yungkwang, NB 68513 and Caprock, and low in Suke ＃ 169. However, variation in protein content due to the cultural methods was low in Suke ＃ 169. 15) Protein yield per unit area was increased in accordance with increase of fertilizer levels and early maturing culture. However, nitrogen fertilizer was utilized rather effectively in early maturing culture and Yungkwang was the highest in protein yield per unit area. 4. Physio-chemical properties of wheat flour: 16) Sedimentation value was higher under the conditions of high temperature, low humidity and high levels of fertilizers than under the conditions of low temperature, high moisture and low levels of fertilizers. Such differences of sedimentation values were more apparent in NB 68513 and Caprock than Yungkwang and Suke ＃ 169. The local difference of sedimentation value was greater in Suwon than in Kwangju and Iri. Even though the sedimentation value was highly correlated with protein content of grain, the high humidity was considered one of the factors affecting sedimentation value. 17) Changes of Pelshenke values due to the differences of cultural practices and locations were generally coincident with sedimentation values. 18) The mixing time required for mixogram was four to six minutes in NB 68513, five to seven minutes in Cap rock. The great variation of mixing time for Yungkwang and Suke ＃ 169 due to location and planting conditions was found. The mixing height and area were high in hard wheat than in soft wheat. Variation of protein content due to cultural methods were inconsistent. However, the pattern of mixogram were very much same regardless the treatments applied. With this regard, it could be concluded that the mixogram is a kind of method expressing the specific character of the variety. 19) Even though the milling property of NB 68513 and Caprock was deteriorated under either high temperature and low humidity of high fertilizer levels and late seeding conditions, baking quality was better due to improved physio-chemical properties of flour. In contrast, early maturing culture deteriorated physio-chemical properties, milling property of grain and grain protein yield per unit area was increased. However, it might be concluded that the hard wheat production of NB 68513 and Caprock for baking purpose could be done better in Suwon than in Iri or Kwangju area. 5. Interrelationships between the physio-chemical characters of wheat flour: 20) Physio-chemical properties of flour didn't have direct relationship with milling rate and ash content. Low grain weight produced high protein content and better physio-chemical flour properties. 21) In hard wheat varieties like NB 68513 and Caprock, protein content was significantly correlated with sedimentation value, Pelshenke value and mixing height. However, gluten strength and baking quality were improved by the increased protein content. In Yungkwang and Suk ＃ 169, protein content was correlated with sedimentation value, but no correlations were found with Pelshenke value and mixing height. Consequently, increase of protein content didn't improve the gluten strength in soft wheat. 22) The highly significant relationships between protein content and gluten strength and sedimentation . value, and between Pelshenke value, mixogram and gluten strength indicated that the determination of mixogram and Pelshenke value are useful for de terming soft and hard type of varieties. Determination of sedimentation value is considered useful method for quality evaluation of wheat grain under different cultural practices.

• Journal of Sericultural and Entomological Science
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• 제8권
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• pp.11-25
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• 1968

Various formulae for estimation of leaf production in mulberry trees were investigated and obtained. Four varieties of mulberry trees were used as the materials, and seven characters namely branch length. branch diameter, node number per branch, total branch weight, branch weight except leaves, leaf weight and leaf area, were studied. The formulae to estimate the leaf yield of mulberry trees are as follows: 1. Varietal differences were appeared in means, variances, standard devitations and standard errors of seven characters studied as shown in table 1. 2. Y$_1$=a$_1$X$_1$${\times}$P$_1$......(l) where Y$_1$ means yield per l0a by branch number and leaf weight determination. a$_1$.........leaf weight per branch. X$_1$.......branch number per plant. P$_1$........plant number per l0a. 3. Y$_2$=(a$_2$${\pm}$S. E.${\times}$X$_2$)+P$_1$.......(2) where Y$_2$ means leaf yield per l0a by branch length and leaf weight determination. a$_2$......leaf weight per meter of branch length. S. E. ......standard error. X$_2$....total branch length per plant. P$_1$........plant number per l0a as written above. 4. Y$_3$=(a$_3$${\pm}$S. E${\times}$X$_3$)${\times}$P$_1$.....(3) where Y$_3$ means of yield per l0a by branch diameter measurement. a$_3$.......leaf weight per 1cm of branch diameter. X$_3$......total branch diameter per plant. 5. Y$_4$=(a$_4$${\pm}$S. E.${\times}$X$_4$)P$_1$......(4) where Y$_4$ means leaf yield per 10a by node number determination. a$_4$.......leaf weight per node X$_4$.....total node number per plant. 6. Y$\sub$5/= {(a$\sub$5/${\pm}$S. E.${\times}$X$_2$)Kv}${\times}$P$_1$.......(5) where Y$\sub$5/ means leaf yield per l0a by branch length and leaf area measurement. a$\sub$5/......leaf area per 1 meter of branch length. K$\sub$v/......leaf weight per 100$\textrm{cm}^2$ of leaf area. 7. Y$\sub$6/={(X$_2$$\div$a$\sub$6/${\pm}$S. E.)}${\times}$K$\sub$v/${\times}$P$_1$......(6) where Y$\sub$6/ means leaf yield estimated by leaf area and branch length measurement. a$\sub$6/......branch length per l00$\textrm{cm}^2$ of leaf area. X$_2$, K$\sub$v/ and P$_1$ are written above. 8. Y$\sub$7/= {(a$\sub$7/${\pm}$S. E. ${\times}$X$_3$)}${\times}$K$\sub$v/${\times}$P$_1$.......(7) where Y$\sub$7/ means leaf yield estimates by branch diameter and leaf area measurement. a$\sub$7/......leaf area per lcm of branch diameter. X$_3$, K$\sub$v/ and P$_1$ are written above. 9. Y$\sub$8/= {(X$_3$$\div$a$\sub$8/${\pm}$S. E.)}${\times}$K$\sub$v/${\times}$P$_1$.......(8) where Y$\sub$8/ means leaf yield estimates by leaf area branch diameter. a$\sub$8/......branch diameter per l00$\textrm{cm}^2$ of leaf area. X$_3$, K$\sub$v/, P$_1$ are written above. 10. Y$\sub$9/= {(a$\sub$9/${\pm}$S. E.${\times}$X$_4$)${\times}$K$\sub$v/}${\times}$P$_1$......(9) where Y$\sub$7/ means leaf yield estimates by node number and leaf measurement. a$\sub$9/......leaf area per node of branch. X$_4$, K$\sub$v/, P$_1$ are written above. 11. Y$\sub$10/= {(X$_4$$\div$a$\sub$10/$\div$S. E.)${\times}$K$\sub$v/}${\times}$P$_1$.......(10) where Y$\sub$10/ means leaf yield estimates by leaf area and node number determination. a$\sub$10/.....node number per l00$\textrm{cm}^2$ of leaf area. X$_4$, K$\sub$v/, P$_1$ are written above. Among many estimation methods. estimation method by the branch is the better than the methods by the measurement of node number and branch diameter. Estimation method, by branch length and leaf area determination, by formulae (6), could be the best method to determine the leaf yield of mulberry trees without destroying the leaves and without weighting the leaves of mulberry trees.