Profit optimization theory as a function of investment of the optical equipment is proposed. Since the power cost due to the illumination plays a vital role in the economic management of the plant factory, a unified analysis as a function of the optical investment is formulated. The fixed as well as the variable costs are discussed in terms of investment of optical devices, for a generalized theory of the plant factory. Condition of the maximized profit quantitatively agrees with the practical experience. The result indicates how the optical power efficiency as well as the investment efficiency should be improved. Also, other variable costs than of the electric power should simultaneously be considered in a total systematic design. Discussion on the color rendering property of lamps is also added, to suggest that the conventional PPFD concept may not be sufficient in practice.

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A seed miss detection program for big seeds like pumpkin, melon; and regularly shaped seeds like coated lettuce was reported in the previous paper (part 1) of this study. As the continuation of the study, this paper (part 2) presents seed miss detection using image subtraction algorithm for small seeds like eggplant and tomato. An automatic image correction method was proposed for correcting the distortion of the image taken before and after the seeding operation. The experimental results showed that the proposed image correction method effectively eliminated the difference between the images taken before and after seeding. It was also revealed that the subtraction algorithm incorporated with automatic image correction function could detect the seed miss for green pepper, eggplant, and tomato within two degrees of distortion between images taken before and after seeding. The detection accuracy was 99% for tomato; 100% for eggplant and green pepper seeds. Moreover, the results show that a robot equipped with single suction nozzle could precisely execute the computer commands and follow the signals by dropping the seeds into the empty cavities for the supplemental seeding operation.

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The grading or quality evaluation of chrysanthemum cut flowers is traditionally performed by experts trained in the grading based on their skilled sensibility. In this paper, an attempt was made to draw some quantitative criteria from the traditional evaluation process by scoring the quality of chrysanthemum cut flowers. The pictorial images of forty-five chrysanthemum cut flowers of which morphological features were intentionally varied were recorded on a video tape. The video images were shown to two independent experts who were asked to score those cut flowers based on the video images. Two replications were made. The results revealed that there were significant differences between two sets of scores given by two experts respectively. There were also large difference between the first evaluation and the second one. The results imply that the human evaluation is vague and uncertain. The measurements were taken for cut flower length, length between flower and the uppermost node, main stem diameter, curvature of main stem, average internode length, area of leaves and stems, and sizes of leaves in order to investigate the relationship between physical features of cut flowers and experts' decision criteria. It seemed that the most of measured physical features were related to experts' decision criteria. No straight applications of these physical features to the grading parameters seem to be possible because there was not enough statistical substantiality. There must be some complex combinations between physical features that make experts decide the quality of individual cut flower. One of the well known functions of neural network is a classifier that can handle this type of problem.

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In the previous installment of this series, the relationship between human being's evaluation and morphological features extracted from chrysanthemum cut flower was investigated in order to quantify the vague criteria that has been established based on human sense. It was also found that the individual morphological feature did not co-relate to human evaluation scores. It was considered that some combination of the features might improve the co-relation. The machine learning system such as the neural networks was considered to be usefully to automate the cut flower evaluation process.
In this paper, length of cut flower, stem diameter, leaf area, length between flower and top leaf, leaf length, and, stem bend were selected for input parameters of neural networks whose output parameter was a human evaluation score. The neural networks were trained by KNT (Kalman Neuro Training) method. From the results, it was observed that output value satisfactorily agreed the human evaluation score. The error was less than the human error resulted from the human double check procedure. It was also confirmed that the evaluation by the neural networks with several appropriate features was effective. In addition, a feasibility of automated cut flower evaluation system, which does not involve human error, was found.

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In order to investigate the effect of clinorotation on plant structure, a one-axis clinostat was developed to negate the 1-G earth gravity. Two-week-old leaf plants were transplanted on the plant stage of the clinostat and grown for one week at different clinorotation rates. The plant width and height were measured every day manually using vernier calipers.
The exponential-regression was the best fit for the change in plant dimension with function of time. The coefficient of determination (R²) was 0.998 and the relative change rate was 8.77×10^-2 mm.mm^-1.day^-1 for width under control condition. The corresponding values for the leaf angle were 0.935 and 1.42×10^-2 deg.deg^-1.day^-1, respectively. The leaf angle in-creased with increasing rate of clinorotation. The increase in leaf angle was 39% more for the clinorotated plants than the control at 1 rpm, 50% more at 5 rpm, and 52% more at 25 rpm. Soon after transplanting to the clinostat, an abrupt change in the leaf orientation was observed for a period of 3 to 4 days.

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The effects of growing temperature on flower bud formation were investigated in Chinese kale (Brassica oleracea L. var. alboglabra L. H. Bailey) cultivars with white petals of 'Hakushin', 'Kairan-T', 'Kairan-M', 'Chugoku-kairan', 'Shirobana-kuroba' and 'Kairan-K', cultivars with yellow petals of 'Chugoku-kairan (Y) ' and 'Kibana-kakurin'.
The developmental process of flower bud in Chinese kale was divided into eight stages.
Cultivars with white petals or yellow petals were grown in a phytotron. Flower bud formation of cultivars with white petal occurred earlier and at higher temperatures than that of cultivars with yellow petals. The number of nodes from cotyledon to flower decreased with exposure to low temperatures.
When cultivars with white petals held 3.2-4.1 unfolding leaves, they were transferred to the phytotron rooms. 'Hakushin', 'Kairan-T' and 'Kairan-M' formed flower buds at temperatures below 30°C, 'Chugoku-kairan', 'Shirobana-kuroba' and 'Kairan' formed buds at temperatures below 25°C. The number of nodes from cotyledon to flower decreased with exposure of low temperatures.
These results indicated that cultivars with white petals have a quantitative cold requirement for flower bud initiation in response to low temperatures.

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Sintered materials from sludge dredged from Tagonoura Bay were used as plant growth medium. The materials were sintered at temperatures of 900-1050°C (LT medium), 1050-1120°C (MT medium) and 1120-1160°C (HT medium). Trace element analysis of the elutions of sintered materials showed that the concentrations of elements tended to increase with de-creased sintering temperature. Their concentrations were less than the allowable levels except for vanadium, which showed concentration of about 2μg/g in LT medium. In the preliminary plant growth experiment, lettuce (Lactuca sativa L. cv. Okayama) was grown in LT, MT and HT media. Nutrient solutions passing through the three sintered media had high pH (about 9) 4 days after the beginning of the experiment, followed by a pH of about 7 measured 11 and 18 days after the beginning of the experiment. The dry and fresh weights and leaf area of lettuce were lowest for plants grown in LT medium. Lettuce growth in MT and HT media were also delayed compared with that in rockwool medium. These low growth rates of lettuce grown in sintered media might be related to the trace elements eluting from the media.
Sintering technology should be developed to decrease the trace elements eluting from sintered materials and further research is needed to utilize the sintered materials as plant growth medium.

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A method on uniformity analysis made weed detection in lawn field possible. The method could detect weeds based on their surfaces which were more uniform in gray-scale values compared with lawn surface, regardless of their color. The result of uniformity analysis, however, was far from ready to be used as a target decision for weeding because it was a binary image with many noises and broken parts. Morphological image processing was applied to the result of uniformity analysis to obtain stronger and clearer binary images. In addition, the detected weed center location which was expected to correspond with the main root of the weed, was determined for minimum chemical weeding. The techniques on how to do that was also described in this paper.

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In the present study, amenity effect on human psychology as affected by ornamental foliage plants used as a screen was analyzed by means of electroencephalogram (EEG) and semantic differential technique.
The experiments were carried out in a room at Ehime University in November and December of 1997. The following three conditions concerning the arrangement of ornamental foliage plants or screens around the subject were rated by eleven students.
(a) a screen on each side of the subject
(b) a screen on the one side and three ornamental foliage plants on the other side of the subject
(c) three ornamental foliage plants on each side of the subject
Electroencephalogram of each student were measured in the room. Ratio of alpha wave to beta wave was calculated as an index expressing the degree of amenity. As for semantic differential technique, factor analysis was performed based on nineteen SD scales.
Higher ratio of alpha wave to beta wave was observed in the condition (c). Two factors were extracted by the factor analysis. The factor scores of the condition (b) and the condition (c) were higher than the factor score of the condition (a). These results indicated the amenity effect on human psychology by plants.

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