No abstract

Plants in the absence of an innate immune system like animals and being immobile are regularly exposed to a host of stresses, ranging from biotic to abiotic stresses. In response to these, plants have developed a complicated response system like reprogramming gene expressions and emission of secondary metabolites as volatile organic compounds (VOCs) by its various tissues like roots, stems, leaves etc. These VOCs can be used as biomarkers for inspecting plants’ in situ health status. This paper address the usefulness of electronic nose (e-nose) system to sense the VOCs emitted by plants’ leaves to detect the stresses in it. Standard commercial electronic nose (e-nose) system Alfa Mos Fox 3000 has been used here to identify the stressed and non-stressed plants. Fifteen Mandarin orange plants were considered for the study and were subdivided into three categories. Each one was subjected to a different level of water stress. Leaf samples were collected for e-nose analyses from each plant of all three categories on the 15th day and 30th day of induction of water stresses. Dimensionality reduction techniques like kernel Principal Component Analysis (kPCA), Linear Discriminant Analysis (LDA) and classification algorithms like Support Vector Machines (SVC) and Multi-Layer Perceptron Classifier (MLPC) have been used to classify the three categories of plants. The scores obtained from these analyses reveals the feasibility of using an e nose system in discriminating plants based on the status of water stress in them. This paper analyses the applicability of e nose system in stress diagnosis of agricultural and horticultural crops, which would significantly help in controlling the irrigation regime.

The inherent ability of most living organisms to perceive their immediate environment based on sensory responses has immensely contributed to their survival in the harshest of conditions. Animals rely on their olfactory sense to assess the quality of food before intake. This paper addresses a technique of using the electronic nose for distinguishing Khasi Mandarin orange plants infected by a virus called Citrus Tristeza Virus (CTV) in terms of their degree of infection. Leaves from 16 plants were collected and, tested for CTV infection using the standard serological test, Enzyme-linked Immunosorbent Assay (ELISA), prior to electronic nose (e-nose) analysis. Essential oil was extracted from the leaves using hydro distillation and the extracted oils were analyzed with commercial e-nose system Alpha MOSFOX 3000 system. Bootstrapped ensemble of support vector classifier was used for classifying the samples. The classifier model was optimized with the best parameters and a kernel specific performance evaluation was done for finding out the best model for classification. Among the linear, radial basis function and polynomial kernels, the linear kernel of the classifier performed the best among all the kernels with an accuracy of 97.67% and a Cohen's Kappa score of 95.25% . Dimensionality reduction techniques like principle component analysis and linear discriminant analysis were also used for graphical visualization of the classification boundaries. The dimensionally reduced dataset was also fitted to the optimized bootstrap ensemble support vector classifier and the performance of the classifier was analyzed. The performance scores of the classifier models reveal the possibility of using e-nose technique in detecting CTV infected plants.

No abstract

This paper presents a wireless sensor network for monitoring field parameters inside a low cost polyhouse. The micro climate inside a polyhouse differs from that on the outside, which provides a favorable condition for unseasonal crops. The physical parameters associated to the poly house’s microclimate were monitored by a reliable low-cost wireless sensor network, which in turn helps to take decisions for enhancing yield quality and quantity. Sensor network development, signal conditioning, calibration of the soil temperature measurement system and field experience of the installed system are discussed in this paper. The field parameters for the growing period of cucumber (Cucumis sativus) inside the polyhouse are provided in the paper. It showed a significant variations in temperature, relative humidity and wind speed inside the polyhouse to that of the outside. It was also observed that soil temperature, soil moisture in mulched soil differed from that of the open condition. Enhancement of the crop yield was found for mulched soil.