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In closed hydroponics, fast and continuous measurement of individual nutrient concentrations is necessary to improve water-and nutrient-use efficiencies and crop production. Ion-selective electrodes (ISEs) could be one of the most attractive tools for hydroponic applications. However, signal drifts over time and interferences from other ions present in hydroponic solutions make it difficult to use the ISEs in hydroponic solutions. In this study, hybrid signal processing combining a two-point normalization (TPN) method for the effective compensation of the drifts and a back propagation artificial neural network (ANN) algorithm for the interpretation of the interferences was developed. In addition, the ANN-based approach for the prediction of Mg concentration which had no feasible ISE was conducted by interpreting the signals from a sensor array consisting of electrical conductivity (EC) and ion-selective electrodes (NO 3 , K, and Ca). From the application test using 8 samples from real greenhouses, the hybrid method based on a combination of the TPN and ANN methods showed relatively low root mean square errors of 47.2, 13.2, and 18.9 mg·L −1 with coefficients of variation (CVs) below 10% for NO 3 , K, and Ca, respectively, compared to those obtained by separate use of the two methods. Furthermore, the Mg prediction results with a root mean square error (RMSE) of 14.6 mg·L −1 over the range of 10-60 mg·L −1 showed potential as an approximate diagnostic tool to measure Mg in hydroponic solutions. These results demonstrate that the hybrid method can improve the accuracy and feasibility of ISEs in hydroponic applications.

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Plant factory can control artificially the environments for crop cultivation, so they can produce high quality agricultural products all year round. This study was carried to select suitable kohlrabi cultivar for hydroponics in a closed-type plant factory system. We used three cultivars of red kohlrabi, 'Asac kohl', 'Kolibri', and 'Purple king' as plant materials. The artificial light source was LED light, light intensity and photoperiod were 249µmol•m -2 •s -1 and 12/12 hours (day/night period), respectively. Hydroponic cultivation type was used circulating deep flow technique. At 43 days after transplanting, fresh weight of whole plant and tuber and leaf area were not significantly different among cultivars. Shoot dry weight and tuber dry weight were highest in 'Asac kohl' cultivar, and number of leaves was highest in 'Purple king' cultivar. Sugar content and yield were highest in 'Asac kohl' cultivar. Considering the growth and marketable yields, 'Asac kohl' was the optimal kohlrabi cultivar for hydroponic cultivation in a closedtype plant factory system.

When designing a plant production system, it is crucial to perform advanced estimation of growth and productivity in relation to cultivation factors. In this study, we developed Planting-density Growth Harvest (PGH) charts to facilitate the estimation of crop growth and harvest factors such as growth rate, relative growth rate, shoot fresh weight, harvesting time, marketable rate, and marketable yield for quinoa (Chenopodium quinoa Willd.) and sowthistle (Ixeris dentata Nakai). The plants were grown in a nutrient film technique (NFT) system in a closed-type plant factory under fluorescent lamps with three-band radiation under a light intensity of 140 μmol·m -2 ·s -1, with a 12-h/12-h (day/night) photoperiod. We analyzed the growth and yield of quinoa and sowthistle grown in nutrient solution at EC 2.0 dS·m -1 under four planting densities: 15 cm between rows with a within-row distance of 15 × 10 cm (67 plants/m 2 ), 15 × 15 cm (44 plants/m 2 ), 15 × 20 cm (33 plants/m 2 ), and 15 × 25 cm (27 plants/m 2 ). Crop growth rate, relative growth rate, and lost time were closely correlated with planting density. We constructed PGH charts based on the growth data and existing models. Using these charts, growth factors could easily be determined, including growth rate, relative growth rate, and lost time, as well as harvest factors such as shoot fresh weight, marketable yield per area, and harvesting time, based on at least two parameters, for instance, planting density and shoot fresh weight.

The objective of this study was to make growth and yield models for common ice plant (Mesembryanthemum crystallinum L.) using expolinear functional equations in a closed-type plant production system. Three-band radiation type fluorescent lamps with a 12-hours photoperiod were used, and the light intensity was 200 μmol･m-2 ･s-1. Nutrient film systems with three layers were used for plant growth. Environmental conditions, such as air temperature, relative humidity and CO2 concentration were controlled by an ON/OFF operation. Leaf area, shoot fresh and dry weights, light use efficiency of common ice plant as function of days after transplanting, accumulative temperature and accumulative radiation were analyzed. Leaf area, shoot fresh and dry weights per area were described using an expolinear equation. A linear relationship between shoot dry and fresh weights was observed. Light use efficiency of common ice plant was 3.3 g･MJ-1 at 30 days after transplanting. It is concluded that the expolinear growth model can be a useful tool for quantifying the growth and yield of common ice plant in a closed plant production system.

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