Hiroshige Nishina

Overexpression of a rice heme activator protein gene (OsHAP2E) confers resistance to pathogens, salinity and drought, and increases photosynthesis and tiller number

Heme activator protein (HAP), also known as nuclear factor Y or CCAAT binding factor (HAP/NF-Y/CBF), has important functions in regulating plant growth, development and stress responses. The expression of rice HAP gene (OsHAP2E) was induced by probenazole (PBZ), a chemical inducer of disease resistance. To characterize the gene, the chimeric gene (OsHAP2E::GUS) engineered to carry the structural gene encoding β-glucuronidase (GUS) driven by the promoter from OsHAP2E was introduced into rice. The transgenic lines of OsHAP2Ein::GUS with the intron showed high GUS activity in the wounds and surrounding tissues. When treated by salicylic acid (SA), isonicotinic acid (INA), abscisic acid (ABA) and hydrogen peroxide (H2 O2 ), the lines showed GUS activity exclusively in vascular tissues and mesophyll cells. This activity was enhanced after inoculation with Magnaporthe oryzae or Xanthomonas oryzae pv. oryzae. The OsHAP2E expression level was also induced after inoculation of rice with M. oryzae and X. oryzae pv. oryzae and after treatment with SA, INA, ABA and H2 O2, respectively. We further produced transgenic rice overexpressing OsHAP2E. These lines conferred resistance to M. oryzae or X. oryzae pv. oryzae and to salinity and drought. Furthermore, they showed a higher photosynthetic rate and an increased number of tillers. Microarray analysis showed up-regulation of defence-related genes. These results suggest that this gene could contribute to conferring biotic and abiotic resistances and increasing photosynthesis and tiller numbers.

Early detection of drought stress in tomato plants with chlorophyll fluorescence imaging–practical application of the speaking plant approach in a greenhouse–

Abstract The chlorophyll fluorescence imaging technique is useful for evaluating photosynthetic functions of plants without actually touching the plant. In our previous study, we developed a chlorophyll fluorescence imaging system for tomato plants cultivated in greenhouses. This imaging system measures the chlorophyll fluorescence induction phenomenon, a dynamic change in chlorophyll fluorescence intensity induced by illuminating a dark-adapted leaf with a stable intensity excitation light, and analyzes the shape of the induction curve, i.e., the temporal course of chlorophyll fluorescence intensity during this phenomenon. The shape of the induction curve is characterized by an initial maximum peak (P), subsequent transient dip (S), and secondary small peak (M). We defined an index, the photosynthetic function index (PFI; fluorescence intensity of P divided by the average fluorescence intensity from S to M), to evaluate the shape of the induction curve. In this study, we applied this system to detect drought stress in tomato plants cultivated in a semi-commercial greenhouse. PFI was clearly lower in stressed plants than in healthy plants. The decreased PFI in stressed plants is probably attributable to photosynthetic dysfunction in these plants.

Computer Integrated Agricultural Production

Abstract Greenhouse production of vegetables has been remarkably developed. Furthermore, vegetables could be cultivated in the factory where such environmental factors as light intensity and temperature are controlled just like in process industries. In the system, many computers are used for environmental control, nutrient control and management of cultivation. Of course, the artificial intelligence is also introduced for the expert system for control and diagnosis of the cultivated vegetables. On the other hand, progress in automated mechanization for seeding and transplanting has made “greenhouse automation” fit for practical use just like “factory automation (FA)” in industries. Now, process industries are rationalized based on the concept of so called “Computer Integrated Manufacture (CIM)”. Therefore, it might be noted that the system in the agricultural production such as the vegetable factory should also be considered based on the concept of CIM. That is the “Computer Integrated Agricultural Production (CIAP)”. In this paper, we examine the vegetable factory from the “CIAP” point of view. Computer network composed of both usual personal computer for environmental control and the special computer for the artificial intelligence is examined. It seems evident that the CIAP discussed in this paper is expected as the most effective system in the coming generation.

Pilot Chamber for the Identification of the Growth Process in a Vegetable Factory

Abstract Recently, vegetables have been cultivated in such a controlled environment as greenhouse and vegetable factory. In vegetable factory, environmental factors are strictly controlled under the optimal condition, while in greenhouse these are controlled based on feedback as affected by the external climate condition. As the vegetable factory becomes popular, more effective method for searching the optimal condition has been expected. In this paper, newly developed pilot chamber for searching the optimal condition is described, which composed of 4 small chambers and integrated microcomputer system for data acquisition of vegetable physiology. Furthermore, the method of searching the optimal process is also described based on the pilot chamber. System identification is found to be very reasonable approach to the problem.

Evapotranspiration Estimate by Heat Balance Equation

A simple heat balance equation for the plant canopy model from which the Penman- Monteith equation was derived is used to estimate evapotranspiration from a plant canopy. Incoming radiation downward and upward, air temperature and wind speed above the canopy are the only four factors to be measured. Estimated evapotranspiration is in good agreement with the values measured by an accurate scale in wet and dry conditions. This method was proven to be simpler and more accurate than that based on the Penman-Monteith equation.

Evaluation of Tomato Fruit Color Change with Different Maturity Stages and Storage Temperatures Using Image Analysis

Abstract The effects of storage duration and temperature on the tomato fruit color change and quality with different maturity stages tomato were investigated in this study. Tomatoes were grown hydroponically in high technology greenhouse. Tomato fruit samples with green to red were stored in cool incubator for 48 h. The storage temperature was adjusted at 15 °C and 20 °C. The maturity stage of tomato fruit was evaluated with chiromaticity by image analysis. Little tomato fruit color change with storage was observed in large maturity stage (red fruit) regardless of storage temperature. Chromaticity in small maturity stage (green fruit) was increased with storage time. The sugar content of fruit was increased and fruit firmness was decreased with storage at both temperatures for 15 °C and 20 °C regardless of maturity stage.

Two approaches to environmental control in greenhouses - heat balance analysis and system identification in heating system with heat pump

Abstract In the greenhouse with heat pump, heat balance analysis, system identification of heating and performance of heat pump system of air-water type were examined. The experiment was carried out in a greenhouse with floor area of 114m 2 in the winter from 1990 to 1991. The results of heat balance analysis and system identification show a good agreement, and it is considered that both heat balance analysis and system identification are effective in analysis of environment in heated greenhouse. Performance of heat pump of air-water type was also made clear.

Control of Air Temperature in Nursery Plants Production System by LQI Control with Kalman Filter

Abstract As an air temperature control system in a nursery plants production system, the authors assumed a linear multivariable system with an input (operation of heater/cooler) and two outputs (air temperature and water temperature). The authors applied a 2nd order AR (auto-regressive) model to the system and designed a LQI (Linear Quadratic Integrating) control with Kalman filter. The control experiments were carried out, changing the values of the weight coefficients in the quadratic type performance index and the covariance matrix of the observation noise and the system noise. The results indicates that LQI control with Kalman filter is effective for environment control in greenhouse systems.

Development of a Multi-Operation System for Intelligent Greenhouses

Abstract To resolve the problem of declination of Japanese agriculture, plant factories with automation, quality control, robotization and speaking plant approach are necessary. The multi operation system described in this paper has running unit with automatic position sensing. Growth environment measurement unit has transpiration, photosynthesis, distance and temperature sensors to obtain plant growth information. The pest control unit uses the antiseptic effect of ozone water. The harvesting unit is used for cucumbers that grow fast; recognition of cucumbers ready to be harvested is achieved through distance information gathered by an attached photo interrupter and distance sensors. The development of multi-operation robot is continued by developing controlling program that can change the operating pattern by sharing the contents by each controlling and operating unit.

Plant Diagnosis by Monitoring Plant Smell: Detection of Russet Mite Damages on Tomato Plants

Abstract Sensor-based plant diagnosis techniques to monitor plant physiological status are important for agricultural production in highly sophisticated greenhouses. Plants emit a broad range of volatile organic compounds and its emission profile changes depending on the plants physiological status. We demonstrated a detection of tomato russet mite damages occurred on stems of tomato plants grown in a semi-commercial greenhouse with an inexpensive- and handy- gas analysis instrument. The results proved that the tomato russet mite damage significantly decreased the amount of terpenes stored in trichomes on the main stem.