In this paper, a method to extract textural features from Colour Co-occurrence Matrix (CCM) and also a method to select relevant textural features for predicting water content of Sunagoke moss (Rhacomitrium japonicum) are proposed. The aim of this paper is to construct machine vision-based precision irrigation system. The objective of this paper is to propose Neural-Discrete Hungry Roach Infestation Optimization (N-DHRIO) algorithm to find the most significant set of textural features suitable for predicting water content of cultured Sunagoke moss using machine vision. N-DHRIO is an optimization algorithm for feature selection that is inspired by the social behaviour of cockroaches. The performance of the proposed feature selection method here was compared with Neural-Genetic Algorithms (N-GAs), Neural-Discrete Particle Swarm Optimization (N-DPSO) and Neural-Simulated Annealing (N-SA). Textural features consisted of 120 textural features extracted from gray, RGB, HSV, HSL and L*a*b* colour spaces. Non-linear relationships between textural features and water content were identified by Back-Propagation Neural Network (BPNN). The results showed significant statistical improvement between methods using feature selection and methods without feature selection. Experimental results also indicated the superiority of N-DHRIO among other feature selection methods, since it achieved better prediction performance as the objective of this research.
For sustainable production of high-quality plants, information about kinetics of root absorptive functions responding to change in environmental condition is essential. A system for measuring rates of water absorption, ion absorption and respiration in intact roots was developed, and the system performance was found to be reliable with a relative error less than 3.5% and applicable under different root zone temperatures and dissolved O2 concentrations. Furthermore, the simultaneous measurements of rates of water and ion absorption enabled the evaluation of ion concentration in the xylem sap. The root absorptive functions were enhanced with increase in root zone temperature, and root respiration was depressed by the low dissolved O2 under the high root zone temperature of 35°C. In addition, the absorbed water diluted the xylem sap, and this dilution effect on the concentration of each ion in the xylem sap appeared in different patterns. These results suggest that the system developed is applicable for the analyses of the absorptive functions of intact roots responding to change in environmental condition.
Welsh onion plants (Allium fistulosum L.cv. Koutou) were grown under the different conditions of root zone temperature and dissolved O2 concentration. The absorptive functions in intact roots were analyzed by evaluating rates of water absorption, ion absorption, respiration and ion concentration in xylem sap simultaneously by applying the measurement system newly developed in the precedent study. The root water and ion absorption were activated with increase in root zone temperature, and the long term treatment with the high temperature and the low dissolved O2 concentration in the root zone significantly depressed water and ion absorption, while ion concentration in the xylem sap was not significantly affected by the root zone temperature. These suggest that the temperature dependence observed in root ion absorption is brought mainly through the temperature dependence of water absorption. A concentration-dependent model based on the theory of enzyme kinetics was applicable to kinetics of the root ion absorption responding to the root zone environment. The effects of root zone temperature and ion concentration on the root ion absorption were represented well by the concentration-dependent model which involves two parameters sensitive to changes in conditions of plants and the environment.
Meteorological elements such as radiation, air temperature, humidity and wind velocity can affect root ion absorption through change in transpiration. A kinetic model of root ion absorption integrated with transpiration was proposed in relation to the ion mass flow to root cell membranes driven by transpiration. The ion absorption model integrated with transpiration represented well rates of root ion absorption measured under the different conditions of ion concentration, light intensity and transpiration. The rate of root ion absorption increased with the rate of ion mass flow to root cell membranes, but this increase was leveled off under the conditions with the higher rates of the ion mass flow. This dependency of root ion absorption on the ion mass flow was characterized by differences in the two parameters involved in the transpiration integrated model proposed.
Although it is known that tuberous root growth in sweetpotato (Ipomoea batatas (L.) Lam.) is strongly inhibited by O2 deprivation, the time course of hypoxia-induced growth inhibition remains unclear. To study the growth pattern of the tuberous root, we measured the change in root diameter in response to hypoxia. The thickening rate of the tuberous root decreased to almost zero after 1 h of hypoxia treatment, and this strong growth-inhibition pattern was maintained during the 24-h hypoxia treatment period. After the treatment, the growth rate slowly returned to the normal value in approximately 10 h. Thus, tuberous root growth rapidly responded to the reduction in O2 concentration, and it reversibly recovered from short-term hypoxia-induced growth inhibition in half a day.