An energy model for the autothermal thermophilic aerobic treatment (ATAT) of human excreta was developed and validated using a full-scale reactor for quantitative interpretation of the self-heating principle. The results showed that the principal heat source was heat generated from microbial oxidation (Q_bio). The specific mean generation rate of Q_bio during self-heating was estimated at 1.190 MJ/h/td5.7 times higher than that after self-heating at 0.208 MJ/h/t. The heating potential of human excreta was estimated on a chemical oxygen demand (COD) basis at 12.1 kJ/g COD. The heat loss from airflow, including sensible heat loss by airflow (Q_air) and latent heat loss by evaporation (Q_vap), was primarily responsible for the decrease in reactor temperature after self-heating.

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The objective of this study was to develop an autonomous navigation system using a laser scanner. A field profile was modeled by investigating range data. A crop row localization method was used to calculate the relative position and direction of crop rows. A steering controller was designed to guide the crop divider to move in an appropriate way. Results showed that the combine harvester had RMS errors of 0.02 m and 0.8° in terms of lateral offset and heading deflection, respectively, under stationary conditions. The corresponding root mean square (RMS) errors were 0.07 m and 3° when the combine harvester autonomously performed soybean harvesting at a speed of 0.97 m/s in the field.

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In order to select significant wavelengths related to winter wheat growth characteristics, field experiments were conducted in three consecutive years. Diffuse reflectance of crop leaves was recorded with other crop variables during growth stages. Multivariate analysis including partial least squares regression (PLSR) and stepwise multiple linear regression (SMLR) procedures were used to determine important wavelengths. The results showed strong relationships between predicted and actual crop variables. The best prediction model built on wavelengths selected by SMLR so that R², root mean square error (RMSR) and relative error (RE) for the validation dataset were 0.85, 1.56 and 3.64% for SPAD, 0.89, 413 and 6.21% for grain yield, and 0.84, 0.56 and 4.85% for protein content.

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Overripe berries cannot be classified from ripe berries of Japanese blue honeysuckle using RGB color imaging analysis since they have the same color appearances. Hyperspectal imaging analysis was thus employed. First, a pixel discrimination function was generated based upon forward stepwise selection to select significant wavebands (751 nm and 420 nm) and linear discriminant analysis, and it was applied to all pixels of segmented berries. Then a majority rule was applied to each berry independently for fruit object classification, and the classification was improved by eroding the fruit edge area. The classification success rates of pixel discrimination and fruit object discrimination tests were 69.7% and 73.9%, respectively. This study showed the potential of identifying overripe berries using hyperspectral imaging analysis.

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The exhaust gas from combustion has been extensively used for greenhouse CO₂ fertilization. However, its toxic gases and thermal energy would generally limit the proper applicability. The aim of this study is to develop a technology to supply toxic gas-free CO₂ and to recover exhaust gas thermal energy. A combustion-type CO₂ generator was manufactured and connected to a heat pump system for greenhouse heating and cooling. Control algorithm for effective operation of the system was also developed and implemented. Greenhouse operation was run at the conditions under which values for CO₂ concentration and indoor temperature were maintained at 1200e1300 ppm and 25–27 °C, respectively. Technical performance of the system was evaluated in cold, moderate and hot seasons.

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The threshing unit of a combine comprises a multiphase flow; therefore, it is essential to consider it on the basis of the flow model. In this study, flight simulation by DEM with fixed wind velocity was carried out. The grain and straw were considered to be ellipsoidal and cuboidal, respectively. A two-dimensional model coupling with a circle element was constructed. Each flight trajectory was reproduced in terms of the initial conditions and changes in winnowing velocity. The average flight velocity of the grain was 0.2 m/s higher than that measured in the experiment. It can simulate to closer phenomenon by mixing different particle mass and straw, analyzing the increase in particles and linking it with fluid analysis.

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Two storage tests (4 years for Kirara 397 and 3 years for Yumepirika) were carried out to investigate long-term storability of rough rice and brown rice under three storage conditions. Super-low temperature storage (below ice point) maintained physiological properties and eating quality of rough rice and brown rice at levels similar to those of raw materials after 2 years of storage. Low temperature storage (below 15°C) minimized the rate of quality deterioration for Kirara 397 but not the rate of quality deterioration for Yumepirika. The results indicated that rice variety also affects the storability of rice. Seed vitality of rough rice and brown rice in room temperature storage showed only minor changes for a period of 10 months.

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This research presents performance evaluation of moss rooftop greening prototype in a confined space using an experimental chamber. The chamber was utilized to simulate performance of prototype in reducing temperature inside a building. Two simulated environments were set as low and high-temperature treatment. Moss plant (Sphagnum sp.) was used. Performance was evaluated by using Lab color, photosynthesis and CO₂ absorption rate. The results concluded that prototype could reduce temperature inside confined space from 1.5 to 2.9 °C. L and b parameters were applicable to detect the color patterns. The high-temperature had no effect on while low-temperature treatment decreased photosynthetic and CO₂ absorption rate. These results concluded that the prototype could be applied as a rooftop greening material in tropical environment of Yogyakarta, Indonesia.

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More and more crops are grown in greenhouses, and crop growth status monitoring is equally important as field-grown crops. An automation system based-on multi-spectral imaging and mobile environmental factor sensing has been developed and operated. To obtain necessary spectral image information of seedling growth status on greenhouse benches, a series of image processing procedures was developed. The study also explored the applications of the radio frequency identification (RFID) system to construct a traceability system for seedling production in greenhouse. Days of seedlings growth can be calculated estimating the PLAI of the plant-oriented multi-spectral images with R² = 0.989. Appropriate irrigation level could be estimated using different indices with environmental factors. Greenhouse cultivation is a site-specific management illustrated by precision integration.

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