• Journal of Global Scholars of Marketing Science
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• v.20 no.1
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• pp.89-97
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• 2010

This study researches the effects of common features on a no-choice option with respect to regulatory focus theory. The primary interest is in three factors and their interrelationship: common features, no-choice option, and regulatory focus. Prior studies have compiled vast body of research in these areas. First, the "common features effect" has been observed bymany noted marketing researchers. Tversky (1972) proposed the seminal theory, the EBA model: elimination by aspect. According to this theory, consumers are prone to focus only on unique features during comparison processing, thereby dismissing any common features as redundant information. Recently, however, more provocative ideas have attacked the EBA model by asserting that common features really do affect consumer judgment. Chernev (1997) first reported that adding common features mitigates the choice gap because of the increasing perception of similarity among alternatives. Later, however, Chernev (2001) published a critically developed study against his prior perspective with the proposition that common features may be a cognitive load to consumers, and thus consumers are possible that they are prone to prefer the heuristic processing to the systematic processing. This tends to bring one question to the forefront: Do "common features" affect consumer choice? If so, what are the concrete effects? This study tries to answer the question with respect to the "no-choice" option and regulatory focus. Second, some researchers hold that the no-choice option is another best alternative of consumers, who are likely to avoid having to choose in the context of knotty trade-off settings or mental conflicts. Hope for the future also may increase the no-choice option in the context of optimism or the expectancy of a more satisfactory alternative appearing later. Other issues reported in this domain are time pressure, consumer confidence, and alternative numbers (Dhar and Nowlis 1999; Lin and Wu 2005; Zakay and Tsal 1993). This study casts the no-choice option in yet another perspective: the interactive effects between common features and regulatory focus. Third, "regulatory focus theory" is a very popular theme in recent marketing research. It suggests that consumers have two focal goals facing each other: promotion vs. prevention. A promotion focus deals with the concepts of hope, inspiration, achievement, or gain, whereas prevention focus involves duty, responsibility, safety, or loss-aversion. Thus, while consumers with a promotion focus tend to take risks for gain, the same does not hold true for a prevention focus. Regulatory focus theory predicts consumers' emotions, creativity, attitudes, memory, performance, and judgment, as documented in a vast field of marketing and psychology articles. The perspective of the current study in exploring consumer choice and common features is a somewhat creative viewpoint in the area of regulatory focus. These reviews inspire this study of the interaction possibility between regulatory focus and common features with a no-choice option. Specifically, adding common features rather than omitting them may increase the no-choice option ratio in the choice setting only to prevention-focused consumers, but vice versa to promotion-focused consumers. The reasoning is that when prevention-focused consumers come in contact with common features, they may perceive higher similarity among the alternatives. This conflict among similar options would increase the no-choice ratio. Promotion-focused consumers, however, are possible that they perceive common features as a cue of confirmation bias. And thus their confirmation processing would make their prior preference more robust, then the no-choice ratio may shrink. This logic is verified in two experiments. The first is a $2{\times}2$ between-subject design (whether common features or not X regulatory focus) using a digital cameras as the relevant stimulus-a product very familiar to young subjects. Specifically, the regulatory focus variable is median split through a measure of eleven items. Common features included zoom, weight, memory, and battery, whereas the other two attributes (pixel and price) were unique features. Results supported our hypothesis that adding common features enhanced the no-choice ratio only to prevention-focus consumers, not to those with a promotion focus. These results confirm our hypothesis - the interactive effects between a regulatory focus and the common features. Prior research had suggested that including common features had a effect on consumer choice, but this study shows that common features affect choice by consumer segmentation. The second experiment was used to replicate the results of the first experiment. This experimental study is equal to the prior except only two - priming manipulation and another stimulus. For the promotion focus condition, subjects had to write an essay using words such as profit, inspiration, pleasure, achievement, development, hedonic, change, pursuit, etc. For prevention, however, they had to use the words persistence, safety, protection, aversion, loss, responsibility, stability etc. The room for rent had common features (sunshine, facility, ventilation) and unique features (distance time and building state). These attributes implied various levels and valence for replication of the prior experiment. Our hypothesis was supported repeatedly in the results, and the interaction effects were significant between regulatory focus and common features. Thus, these studies showed the dual effects of common features on consumer choice for a no-choice option. Adding common features may enhance or mitigate no-choice, contradictory as it may sound. Under a prevention focus, adding common features is likely to enhance the no-choice ratio because of increasing mental conflict; under the promotion focus, it is prone to shrink the ratio perhaps because of a "confirmation bias." The research has practical and theoretical implications for marketers, who may need to consider common features carefully in a practical display context according to consumer segmentation (i.e., promotion vs. prevention focus.) Theoretically, the results suggest some meaningful moderator variable between common features and no-choice in that the effect on no-choice option is partly dependent on a regulatory focus. This variable corresponds not only to a chronic perspective but also a situational perspective in our hypothesis domain. Finally, in light of some shortcomings in the research, such as overlooked attribute importance, low ratio of no-choice, or the external validity issue, we hope it influences future studies to explore the little-known world of the "no-choice option."

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.221-241
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• 2018

Deep learning is getting attention recently. The deep learning technique which had been applied in competitions of the International Conference on Image Recognition Technology(ILSVR) and AlphaGo is Convolution Neural Network(CNN). CNN is characterized in that the input image is divided into small sections to recognize the partial features and combine them to recognize as a whole. Deep learning technologies are expected to bring a lot of changes in our lives, but until now, its applications have been limited to image recognition and natural language processing. The use of deep learning techniques for business problems is still an early research stage. If their performance is proved, they can be applied to traditional business problems such as future marketing response prediction, fraud transaction detection, bankruptcy prediction, and so on. So, it is a very meaningful experiment to diagnose the possibility of solving business problems using deep learning technologies based on the case of online shopping companies which have big data, are relatively easy to identify customer behavior and has high utilization values. Especially, in online shopping companies, the competition environment is rapidly changing and becoming more intense. Therefore, analysis of customer behavior for maximizing profit is becoming more and more important for online shopping companies. In this study, we propose 'CNN model of Heterogeneous Information Integration' using CNN as a way to improve the predictive power of customer behavior in online shopping enterprises. In order to propose a model that optimizes the performance, which is a model that learns from the convolution neural network of the multi-layer perceptron structure by combining structured and unstructured information, this model uses 'heterogeneous information integration', 'unstructured information vector conversion', 'multi-layer perceptron design', and evaluate the performance of each architecture, and confirm the proposed model based on the results. In addition, the target variables for predicting customer behavior are defined as six binary classification problems: re-purchaser, churn, frequent shopper, frequent refund shopper, high amount shopper, high discount shopper. In order to verify the usefulness of the proposed model, we conducted experiments using actual data of domestic specific online shopping company. This experiment uses actual transactions, customers, and VOC data of specific online shopping company in Korea. Data extraction criteria are defined for 47,947 customers who registered at least one VOC in January 2011 (1 month). The customer profiles of these customers, as well as a total of 19 months of trading data from September 2010 to March 2012, and VOCs posted for a month are used. The experiment of this study is divided into two stages. In the first step, we evaluate three architectures that affect the performance of the proposed model and select optimal parameters. We evaluate the performance with the proposed model. Experimental results show that the proposed model, which combines both structured and unstructured information, is superior compared to NBC(Naïve Bayes classification), SVM(Support vector machine), and ANN(Artificial neural network). Therefore, it is significant that the use of unstructured information contributes to predict customer behavior, and that CNN can be applied to solve business problems as well as image recognition and natural language processing problems. It can be confirmed through experiments that CNN is more effective in understanding and interpreting the meaning of context in text VOC data. And it is significant that the empirical research based on the actual data of the e-commerce company can extract very meaningful information from the VOC data written in the text format directly by the customer in the prediction of the customer behavior. Finally, through various experiments, it is possible to say that the proposed model provides useful information for the future research related to the parameter selection and its performance.

• Korean Journal of Poultry Science
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• v.35 no.2
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• pp.143-151
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• 2008

This study was conducted to identify the correlation of bacterial phytase ($Transphos^{(R)}$) to the calcium level in feed. Of all 21-week-old 720 HyLine brown laying hens, 2 birds of similar weight were placed on each individual cage. The experiment was conducted by $3{\times}2{\times}3$ factorial design with including 3 different levels of phytase (0, 300, and 1,000 DPU/kg), 2 different levels of calcium (3.5% and 4.0%), and 3 different levels of no NPP addition 0% (0.095 NPP), 0.5% (0.185% NPP), and 1.0% (0.275% NPP). The feeding trial maintained the ME level of 2,800 kcal/kg and 16% for crude protein. The diet was fed ad libitum and 17 hours of lighting was provided throughout the experimental period. Egg production seemed to increase, in the 300 DPU of bacterial phytase added group and the cracked egg tended to reduce in Transphos added group. The egg productivity between treatment groups did not show significant difference by dietary calcium level, whereas non NPP added group (0.095% NPP) was found to be low compared to NPP added groups (P<0.05). The highest mean egg weight and the highest daily egg mass were detected in 300 DPU phytase added group. Although the mean egg weight was significantly higher in treatment groups fed with 3.5% calcium containing feeds (P<0.05), daily egg mass was no among treatment groups. The mean egg weight and daily egg mass were the lowest in non NPP added group (0.095% NPP) compared to other treatment groups (P<0.05). The feed intake showed similar pattern regardless of the bacterial phytase and calcium levels in the diet. However, the treatment groups fed diets containing NPP level of 0.275% and 0.165% showed significantly higher feed intake than the group fed with 0.095% NPP (P<0.05). Although the feed conversion was not affected by calcium and NPP levels in the diet, the most improved result was obtained from 300 DPU phytase added group (P<0.05). The eggshell breaking strength and thickness increased as dietary calcium level increase the level of calcium increases in diet. The treatment groups fed diet containing 0.275% and 0.165% NPP revealed to show improvement in eggshell breaking strength and yolk color index compared to the NPP non added (0.095% NPP) treatment group. The result of the present study suggests that the appropriate level of microbial phytase is 300 DPU and at this level, tricalciumphosphate supplementation in feed can be reduced to 40% of NRC recommendation. Higher calcium level in feed fail to show synergistic effect by adding microbial phytase.

• Clinical and Experimental Reproductive Medicine
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• v.37 no.1
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• pp.49-56
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• 2010

Objective: To investigate assisted reproductive technology (ART) outcomes in women with WHO class I anovulation compared with control group. Design: Retrospective case-control study. Methods: Twenty-three infertile women with hypogonadotropic hypogonadism (H-H) who undertook ART procedure from August 2003 to January 2009 were enrolled in this study. A total of 59 cycles (H-H group) were included; Intra-uterine insemination with super-ovulation (SO-IUI, 32 cycles), in vitro fertilization with fresh embryo transfer (IVF-ET, 18 cycles) and subsequent frozenthawed embryo transfer (FET, 9 cycles). Age and BMI matched 146 cycles of infertile women were collected as control group; 64 cycles of unexplained infertile women for SO-IUI and 54 cycles of IVF-ET and 28 cycles of FET with tubal factor. We compared ART and pregnancy outcomes such as clinical pregnancy rate (CPR), clinical abortion rate (CAR), and live birth rate (LBR) between the two groups. Results: There was no difference in the mean age ($32.7{\pm}3.3$ vs. $32.6{\pm}2.7$ yrs) and BMI ($21.0{\pm}3.1$ vs. $20.8{\pm}3.1kg/m^2$) between two groups. Mean levels of basal LH, FSH, and $E_2$ in H-H group were $0.62{\pm}0.35$ mIU/ml, $2.60{\pm}2.30$ mIU/ml and $10.1{\pm}8.2$ pg/ml, respectively. For ovarian stimulation, H-H group needed higher total amount of gonadotropin injected and longer duration for ovarian stimulation (p<0.001). In SO-IUI cycles, there was no significant difference of CPR, CAR, and LBR between the two groups. In IVF-ET treatment, H-H group presented higher mean $E_2$ level on hCG day ($3104.8{\pm}1020.2$ pg/ml vs. $1878.3{\pm}1197.7$ pg/ml, p<0.001) with lower CPR (16.7 vs. 37.0%, p=0.11) and LBR (5.6 vs. 33.3%, p=0.02) and higher CAR (66.7 vs. 10.0%, p=0.02) compared with the control group. However, subsequent FET cycles showed no significant difference of CPR, CAR, and LBR between the two groups. Conclusion: H-H patients need higher dosage of gonadotropin and longer duration for ovarian stimulation compared with the control groups. Significantly poor pregnancy outcomes in IVF-ET cycles of H-H group may be due to detrimental endometrial factors caused by higher $E_2$ level and the absence of previous hormonal exposure on endometrium.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.57-78
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• 2020

With the development of the Internet, consumers have had an opportunity to check product information easily through E-Commerce. Product reviews used in the process of purchasing goods are based on user experience, allowing consumers to engage as producers of information as well as refer to information. This can be a way to increase the efficiency of purchasing decisions from the perspective of consumers, and from the seller's point of view, it can help develop products and strengthen their competitiveness. However, it takes a lot of time and effort to understand the overall assessment and assessment dimensions of the products that I think are important in reading the vast amount of product reviews offered by E-Commerce for the products consumers want to compare. This is because product reviews are unstructured information and it is difficult to read sentiment of reviews and assessment dimension immediately. For example, consumers who want to purchase a laptop would like to check the assessment of comparative products at each dimension, such as performance, weight, delivery, speed, and design. Therefore, in this paper, we would like to propose a method to automatically generate multi-dimensional product assessment scores in product reviews that we would like to compare. The methods presented in this study consist largely of two phases. One is the pre-preparation phase and the second is the individual product scoring phase. In the pre-preparation phase, a dimensioned classification model and a sentiment analysis model are created based on a review of the large category product group review. By combining word embedding and association analysis, the dimensioned classification model complements the limitation that word embedding methods for finding relevance between dimensions and words in existing studies see only the distance of words in sentences. Sentiment analysis models generate CNN models by organizing learning data tagged with positives and negatives on a phrase unit for accurate polarity detection. Through this, the individual product scoring phase applies the models pre-prepared for the phrase unit review. Multi-dimensional assessment scores can be obtained by aggregating them by assessment dimension according to the proportion of reviews organized like this, which are grouped among those that are judged to describe a specific dimension for each phrase. In the experiment of this paper, approximately 260,000 reviews of the large category product group are collected to form a dimensioned classification model and a sentiment analysis model. In addition, reviews of the laptops of S and L companies selling at E-Commerce are collected and used as experimental data, respectively. The dimensioned classification model classified individual product reviews broken down into phrases into six assessment dimensions and combined the existing word embedding method with an association analysis indicating frequency between words and dimensions. As a result of combining word embedding and association analysis, the accuracy of the model increased by 13.7%. The sentiment analysis models could be seen to closely analyze the assessment when they were taught in a phrase unit rather than in sentences. As a result, it was confirmed that the accuracy was 29.4% higher than the sentence-based model. Through this study, both sellers and consumers can expect efficient decision making in purchasing and product development, given that they can make multi-dimensional comparisons of products. In addition, text reviews, which are unstructured data, were transformed into objective values such as frequency and morpheme, and they were analysed together using word embedding and association analysis to improve the objectivity aspects of more precise multi-dimensional analysis and research. This will be an attractive analysis model in terms of not only enabling more effective service deployment during the evolving E-Commerce market and fierce competition, but also satisfying both customers.

• Journal of Animal Environmental Science
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• v.16 no.1
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• pp.81-92
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• 2010

This study was conducted to evaluate the effects of fermented diets including liquid by-products on nutrient digestibility and nitrogen balance in growing pigs. Treatments were 1) CON (basal diet), 2) F (fermented diet with basal diet), 3) KF (fermented diet with basal diet including 30% kale pomace), 4) AF (fermented diet with basal diet including 30% angelica keiskei pomace), 5) CF (fermented diet with basal diet including 30% carrot pomace) and 6) OF (fermented diet with basal diet including 30% grape pomace). A total of 24 pigs (41.74kg average initial body weight, Landrace $\times$ Yorkshire $\times$ Duroc), were assigned to 6 treatments, 4 replicates and 1 pig per metabolic cage in a randomized complete block (RCB) design. Pigs were housed in $0.5\times1.3m$ metabolic cage in a 17d digestibility trial. During the entire experimental period, Digestibility of dry matter (p<0.05) of treatment CON, F and CF were higher than other treatments. In crude protein digestibility, treatment F was higher than treatment AF and GF (p<0.05). Treatment GF showed the lowest digestibility of crude fiber among all treatments (p<0.05). In ether extract digestibility, treatment AF and CF showed higher than other treatments (p<0.05) except KF treatment. CF treatment showed the best digestibility of ash among all treatments (p<0.05). Whereas, For Ca and P digestibility, CF and OF treatments were improved than other treatments (p<0.05). Energy digestibility (p<0.05) of CON, F and CF treatments were higher than KF, AF and GF treatments. In total essential amino acid digestibility, F treatment was improved than AF, CF and GF treatments (p<0.05). In total non-essential amino acid digestibility, F treatment was higher than CON, AF and GF treatments (p<0.05). In total amino acid digestibility, F treatment was higher than AF and CF treatments (p<0.05) and GF treatment showed the lowest digestibility (p<0.05). In fecal nitrogen excretion ratio, GF treatment was greatest among all treatments (p<0.05) and F treatment was decreased than other treatments (p<0.05). In urinary nitrogen excretion ratio, CON and GF treatments showed the lowest among all treatments (p<0.05). In nitrogen retention ratio, CON treatment showed the high and KF treatment showed the lost among all treatments (p<0.05). Therefore, this experiment suggested that fermented diet could improve nutrient and amino acid digestibilities of growing pigs.

• Journal of Global Scholars of Marketing Science
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• v.18 no.3
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• pp.59-88
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• 2008

Digital Convergence means integration between industry, technology, and contents, and in marketing, it usually comes with creation of new types of product and service under the base of digital technology as digitalization progress in electro-communication industries including telecommunication, home appliance, and computer industries. One can see digital convergence not only in instruments such as PC, AV appliances, cellular phone, but also in contents, network, service that are required in production, modification, distribution, re-production of information. Convergence in contents started around 1990. Convergence in network and service begins as broadcasting and telecommunication integrates and DMB(digital multimedia broadcasting), born in May, 2005 is the symbolic icon in this trend. There are some positive and negative expectations about DMB. The reason why two opposite expectations exist is that DMB does not come out from customer's need but from technology development. Therefore, customers might have hard time to interpret the real meaning of DMB. Time is quite critical to a high tech product, like DMB because another product with same function from different technology can replace the existing product within short period of time. If DMB does not positioning well to customer's mind quickly, another products like Wibro, IPTV, or HSPDA could replace it before it even spreads out. Therefore, positioning strategy is critical for success of DMB product. To make correct positioning strategy, one needs to understand how consumer interprets DMB and how consumer's interpretation can be changed via communication strategy. In this study, we try to investigate how consumer perceives a new product, like DMB and how AD strategy change consumer's perception. More specifically, the paper segment consumers into sub-groups based on their DMB perceptions and compare their characteristics in order to understand how they perceive DMB. And, expose them different printed ADs that have messages guiding consumer think DMB in specific ways, either cellular phone or personal TV. Research Question 1: Segment consumers according to perceptions about DMB and compare characteristics of segmentations. Research Question 2: Compare perceptions about DMB after AD that induces categorization of DMB in direction for each segment. If one understand and predict a direction in which consumer perceive a new product, firm can select target customers easily. We segment consumers according to their perception and analyze characteristics in order to find some variables that can influence perceptions, like prior experience, usage, or habit. And then, marketing people can use this variables to identify target customers and predict their perceptions. If one knows how customer's perception is changed via AD message, communication strategy could be constructed properly. Specially, information from segmented customers helps to develop efficient AD strategy for segment who has prior perception. Research framework consists of two measurements and one treatment, O1 X O2. First observation is for collecting information about consumer's perception and their characteristics. Based on first observation, the paper segment consumers into two groups, one group perceives DMB similar to Cellular phone and the other group perceives DMB similar to TV. And compare characteristics of two segments in order to find reason why they perceive DMB differently. Next, we expose two kinds of AD to subjects. One AD describes DMB as Cellular phone and the other Ad describes DMB as personal TV. When two ADs are exposed to subjects, consumers don't know their prior perception of DMB, in other words, which subject belongs 'similar-to-Cellular phone' segment or 'similar-to-TV' segment? However, we analyze the AD's effect differently for each segment. In research design, final observation is for investigating AD effect. Perception before AD is compared with perception after AD. Comparisons are made for each segment and for each AD. For the segment who perceives DMB similar to TV, AD that describes DMB as cellular phone could change the prior perception. And AD that describes DMB as personal TV, could enforce the prior perception. For data collection, subjects are selected from undergraduate students because they have basic knowledge about most digital equipments and have open attitude about a new product and media. Total number of subjects is 240. In order to measure perception about DMB, we use indirect measurement, comparison with other similar digital products. To select similar digital products, we pre-survey students and then finally select PDA, Car-TV, Cellular Phone, MP3 player, TV, and PSP. Quasi experiment is done at several classes under instructor's allowance. After brief introduction, prior knowledge, awareness, and usage about DMB as well as other digital instruments is asked and their similarities and perceived characteristics are measured. And then, two kinds of manipulated color-printed AD are distributed and similarities and perceived characteristics for DMB are re-measured. Finally purchase intension, AD attitude, manipulation check, and demographic variables are asked. Subjects are given small gift for participation. Stimuli are color-printed advertising. Their actual size is A4 and made after several pre-test from AD professionals and students. As results, consumers are segmented into two subgroups based on their perceptions of DMB. Similarity measure between DMB and cellular phone and similarity measure between DMB and TV are used to classify consumers. If subject whose first measure is less than the second measure, she is classified into segment A and segment A is characterized as they perceive DMB like TV. Otherwise, they are classified as segment B, who perceives DMB like cellular phone. Discriminant analysis on these groups with their characteristics of usage and attitude shows that Segment A knows much about DMB and uses a lot of digital instrument. Segment B, who thinks DMB as cellular phone doesn't know well about DMB and not familiar with other digital instruments. So, consumers with higher knowledge perceive DMB similar to TV because launching DMB advertising lead consumer think DMB as TV. Consumers with less interest on digital products don't know well about DMB AD and then think DMB as cellular phone. In order to investigate perceptions of DMB as well as other digital instruments, we apply Proxscal analysis, Multidimensional Scaling technique at SPSS statistical package. At first step, subjects are presented 21 pairs of 7 digital instruments and evaluate similarity judgments on 7 point scale. And for each segment, their similarity judgments are averaged and similarity matrix is made. Secondly, Proxscal analysis of segment A and B are done. At third stage, get similarity judgment between DMB and other digital instruments after AD exposure. Lastly, similarity judgments of group A-1, A-2, B-1, and B-2 are named as 'after DMB' and put them into matrix made at the first stage. Then apply Proxscal analysis on these matrixes and check the positional difference of DMB and after DMB. The results show that map of segment A, who perceives DMB similar as TV, shows that DMB position closer to TV than to Cellular phone as expected. Map of segment B, who perceive DMB similar as cellular phone shows that DMB position closer to Cellular phone than to TV as expected. Stress value and R-square is acceptable. And, change results after stimuli, manipulated Advertising show that AD makes DMB perception bent toward Cellular phone when Cellular phone-like AD is exposed, and that DMB positioning move towards Car-TV which is more personalized one when TV-like AD is exposed. It is true for both segment, A and B, consistently. Furthermore, the paper apply correspondence analysis to the same data and find almost the same results. The paper answers two main research questions. The first one is that perception about a new product is made mainly from prior experience. And the second one is that AD is effective in changing and enforcing perception. In addition to above, we extend perception change to purchase intention. Purchase intention is high when AD enforces original perception. AD that shows DMB like TV makes worst intention. This paper has limitations and issues to be pursed in near future. Methodologically, current methodology can't provide statistical test on the perceptual change, since classical MDS models, like Proxscal and correspondence analysis are not probability models. So, a new probability MDS model for testing hypothesis about configuration needs to be developed. Next, advertising message needs to be developed more rigorously from theoretical and managerial perspective. Also experimental procedure could be improved for more realistic data collection. For example, web-based experiment and real product stimuli and multimedia presentation could be employed. Or, one can display products together in simulated shop. In addition, demand and social desirability threats of internal validity could influence on the results. In order to handle the threats, results of the model-intended advertising and other "pseudo" advertising could be compared. Furthermore, one can try various level of innovativeness in order to check whether it make any different results (cf. Moon 2006). In addition, if one can create hypothetical product that is really innovative and new for research, it helps to make a vacant impression status and then to study how to form impression in more rigorous way.

• 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 Bio-Environment Control
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• v.5 no.2
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• pp.215-235
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• 1996

The thermal analysis by mathematical model simulation makes it possible to reasonably predict heating and/or cooling requirements of certain greenhouses located under various geographical and climatic environment. It is another advantages of model simulation technique to be able to make it possible to select appropriate heating system, to set up energy utilization strategy, to schedule seasonal crop pattern, as well as to determine new greenhouse ranges. In this study, the control pattern for greenhouse microclimate is categorized as cooling and heating. Dynamic model was adopted to simulate heating requirements and/or energy conservation effectiveness such as energy saving by night-time thermal curtain, estimation of Heating Degree-Hours(HDH), long time prediction of greenhouse thermal behavior, etc. On the other hand, the cooling effects of ventilation, shading, and pad ||||&|||| fan system were partly analyzed by static model. By the experimental work with small size model greenhouse of 1.2m$\times$2.4m, it was found that cooling the greenhouse by spraying cold water directly on greenhouse cover surface or by recirculating cold water through heat exchangers would be effective in greenhouse summer cooling. The mathematical model developed for greenhouse model simulation is highly applicable because it can reflects various climatic factors like temperature, humidity, beam and diffuse solar radiation, wind velocity, etc. This model was closely verified by various weather data obtained through long period greenhouse experiment. Most of the materials relating with greenhouse heating or cooling components were obtained from model greenhouse simulated mathematically by using typical year(1987) data of Jinju Gyeongnam. But some of the materials relating with greenhouse cooling was obtained by performing model experiments which include analyzing cooling effect of water sprayed directly on greenhouse roof surface. The results are summarized as follows : 1. The heating requirements of model greenhouse were highly related with the minimum temperature set for given greenhouse. The setting temperature at night-time is much more influential on heating energy requirement than that at day-time. Therefore It is highly recommended that night- time setting temperature should be carefully determined and controlled. 2. The HDH data obtained by conventional method were estimated on the basis of considerably long term average weather temperature together with the standard base temperature(usually 18.3$^{\circ}C$). This kind of data can merely be used as a relative comparison criteria about heating load, but is not applicable in the calculation of greenhouse heating requirements because of the limited consideration of climatic factors and inappropriate base temperature. By comparing the HDM data with the results of simulation, it is found that the heating system design by HDH data will probably overshoot the actual heating requirement. 3. The energy saving effect of night-time thermal curtain as well as estimated heating requirement is found to be sensitively related with weather condition: Thermal curtain adopted for simulation showed high effectiveness in energy saving which amounts to more than 50% of annual heating requirement. 4. The ventilation performances doting warm seasons are mainly influenced by air exchange rate even though there are some variations depending on greenhouse structural difference, weather and cropping conditions. For air exchanges above 1 volume per minute, the reduction rate of temperature rise on both types of considered greenhouse becomes modest with the additional increase of ventilation capacity. Therefore the desirable ventilation capacity is assumed to be 1 air change per minute, which is the recommended ventilation rate in common greenhouse. 5. In glass covered greenhouse with full production, under clear weather of 50% RH, and continuous 1 air change per minute, the temperature drop in 50% shaded greenhouse and pad ＆ fan systemed greenhouse is 2.6$^{\circ}C$ and.6.1$^{\circ}C$ respectively. The temperature in control greenhouse under continuous air change at this time was 36.6$^{\circ}C$ which was 5.3$^{\circ}C$ above ambient temperature. As a result the greenhouse temperature can be maintained 3$^{\circ}C$ below ambient temperature. But when RH is 80%, it was impossible to drop greenhouse temperature below ambient temperature because possible temperature reduction by pad ||||&|||| fan system at this time is not more than 2.4$^{\circ}C$. 6. During 3 months of hot summer season if the greenhouse is assumed to be cooled only when greenhouse temperature rise above 27$^{\circ}C$, the relationship between RH of ambient air and greenhouse temperature drop($\Delta$T) was formulated as follows : $\Delta$T= -0.077RH＋7.7 7. Time dependent cooling effects performed by operation of each or combination of ventilation, 50% shading, pad ＆ fan of 80% efficiency, were continuously predicted for one typical summer day long. When the greenhouse was cooled only by 1 air change per minute, greenhouse air temperature was 5$^{\circ}C$ above outdoor temperature. Either method alone can not drop greenhouse air temperature below outdoor temperature even under the fully cropped situations. But when both systems were operated together, greenhouse air temperature can be controlled to about 2.0-2.3$^{\circ}C$ below ambient temperature. 8. When the cool water of 6.5-8.5$^{\circ}C$ was sprayed on greenhouse roof surface with the water flow rate of 1.3 liter/min per unit greenhouse floor area, greenhouse air temperature could be dropped down to 16.5-18.$0^{\circ}C$, whlch is about 1$0^{\circ}C$ below the ambient temperature of 26.5-28.$0^{\circ}C$ at that time. The most important thing in cooling greenhouse air effectively with water spray may be obtaining plenty of cool water source like ground water itself or cold water produced by heat-pump. Future work is focused on not only analyzing the feasibility of heat pump operation but also finding the relationships between greenhouse air temperature(T$_{g}$ ), spraying water temperature(T$_{w}$ ), water flow rate(Q), and ambient temperature(T$_{o}$).

• Korean Journal of Agricultural Science
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• v.4 no.2
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• pp.254-282
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• 1977

To obtain information on the inheritance of the quantitative characters related with the vegetative and reproductive growth of rice, the $F_1$ seeds were obtained in 1974 from the all possible combinations of the diallel crosses among five leading rice varieties : Nongbaek, Tongil, Palgueng, Mangyeong and Gimmaze. The $F_1$'s including reciprocals and parents were grown under the standard cultivation method at Chungnam Provincial Office of Rural Development in 1975. The arrangement of experimental plots was randomized block design with 3 replications and 12 characters were used for the analysis. Analytical procedure for genetic components was followed the Griffing's and Hayman's methods and the results obtained are summarized as follows. 1. In all $F_1$'s of Tongil crosses, the longer duration to heading was due to dominant effect of Tongil and each $F_1$ showed high heterosis in delaying the heading time. It was assumed that non-allelic gene action besides dominant gene effect might be involed in days to heading character. However, in all $F_1$'s from the crosses among parents excluding Tongil the shorter duration was due to dominant gene action and the degree of dominance was partial, since dominance effects were not greater than the additive effect. The non-allelic gene interaction was not significant. Considering the results mentioned above, it was regarded that there were two kinds of Significantly different genetic systems in the days to heading. 2. The rate of heterosis was significantly different depending upon the parents used in the crosses. For instance, the $F_1$'s from Togil cross showed high rate of heterosis in longer culm. Compared to short culm, longer culm was due to recesive gene action and short culm was due to recesive gene action. The dominant gene effect was greater than the additive gene effect in culm length. The narrow sense of heretability was very low and the maternal effects as well as reciprocal effects were significantly recognized. 3. The lenght of the of the uppermost internode of each $F_1$ plant was a little lorger than these of respective parental means or same as those of parents having long internodes, indicating partial dominance in the direction of lengthening the uppermost internodes. The additive gene effects on the uppermost internode was greater than the dominance gene effect. The narrow as well as broad sense of heritabilities for the character of the uppermost internode were very high. There were significant maternal and reciprocal effect in the uppermost internode. 4. The gene action for the flag leaf angle was rather dominance in a way of getting narrower angle. However, in the Palgueng combinations, heterosis of $F_1$ was observed in both narrow and wide angles of the flag leaf. The dominant effects were greater than the additive effects on the flag leaf angle. There were observed also a great deal of non-allelic gene interacticn on the inheritance of the flag leaf angle. 5. Even though the dominant gene action on the length and width of flag leaf was effective in increasing the length or width of the flag leaf, there were found various degrees of hetercsis depending upon the cross combination. Over-dominant gene effect were observed in the inheritance of length of the flag leaf, while additive gene effects was found in the inheritance of the width of the flag leaf. High degree of heretabilities, either narrow or broad sense, were found in both length and width of the flag leaf. No maternal and reciprocal effect were found in both characters. 6. When Tongil was used as one parent in the cross, the length of panicle of $F_1$'s was remarkedly longer than that of parents. In other cross comination, the length of panicle of $F_1$'s was close to the parental mean values. Rather greater dominent gene effect than additive gene effect was observed in the inheritance of panicle length and the dominant gene was effective in increasing the panicle length. 7. The effect of dominant genes was effective in increasing the number of panicles. The degree of heterosis was largely dependent on the cross combination. The effect of dominant gene in the inheritance of panicle number was a little greater than that of additive genes, and the inheritance of panicle number was assumed to be due to complete dominant gene effects. Significantly high maternal and reciprocal effects were found in the character studied. 8. There were minus and plus values of heterosis in the kernel number per panicle depending upon the cross combination. The mean dominant effect was effective in increasing the kernel number per panicle, the degree of dominant effect varied with cross combination. The dominant gene effect and non-allelic gene interaction were found in the inheritance of the kernel number per panicle. 9. Genetic studies were impossible for the maturing ratio, because of environmental effects such as hazards delaying heads. The dominant gene effect was responsible for improving the maturing ratio in all the cross combinations excluding Tongil 10. The heavier 1000 grain weight was due to dominant gene effects. The additive gene effects were greater than the dominant gene effect in the 1000 grain weight, indicating that partial dominance was responsible for increasing the 1000 grain weight. The heritabilites, either narrow or broad sense of, were high for the grain weight and maternal or reciprocal effects were not recognized. 11. When Tongil was used as parent, the straw weight was showing high heterosis in the direction of increasing the weight. But in other crosses, the straw weight of $F_1$'s was lower than those of parental mean values. The direction of dominant gene effect was plus or minus depending upon the cross combinations. The degree of dominance was also depending on the cross combination, and apparently high nonallelic gene interaction was observed.