Here we report the discovery through activation tagging and subsequent characterization of the BIG LEAF (BL) gene from poplar. In poplar, BL regulates leaf size via positively affecting cell proliferation. Up and downregulation of the gene led to increased and decreased leaf size, respectively, and these phenotypes corresponded to increased and decreased cell numbers. BL function encompasses th...

Predicting the quality of software modules prior to testing or system operations allows a focused software quality improvement endeavor. Decision trees are very attractive for classification problems, because of their comprehensibility and white box modeling features. However, optimizing the classification accuracy and the tree size is a difficult problem, and to our knowledge very few studies ...

Cement powder size classification efficiency significantly affects quality of final product and extent of energy consumption in clinker grinding circuits. Static and dynamic or high efficiency air separators are being used widely in closed circuit with multi-compartment tube ball mills, High Pressure Grinding Rolls (HPGR) and more recently Vertical Roller Mills (VRM) units in cement plants ...

Plant stoichiometry in relation to the structure and function of biological systems has been investigated at multiple scales. However, few studies have focused on the roles of stoichiometry for a given species. In this study, we determined leaf N and P stoichiometry, leaf shape and plant size in three Quercus acutissima common gardens with different climatic and site conditions. In the three co...

1. Recent work shows that large leaves tend to require higher biomass investments per unit leaf area than small leaves. As a consequence, specific leaf area (SLA), which is a focus trait for a bulk of physiological and ecological research programs, is dependent on leaf size variation. Here, we address whether size dependency alters the outcome of research dealing with SLA responses to environme...

In this paper, we propose advanced leaf recognition based on leaf contour and centroid for plant classification. Further, frequency domain data was used by performing Fast Fourier transform (FFT) in order to have advanced leaf recognition. Twenty leaf features were extracted for leaf recognition. To verify the validity of the approach, images of 1907 leaves were used to classify 32 kinds of pla...

In hierarchical classification, class label is structured in that each label value corresponds to one non-root node in a tree, where the inter-class relationship for classification is specified by directed paths of the tree. In such a situation, the focus has been on how to leverage the inter-class relationship to enhance the performance of flat classification ignoring such dependency. This is ...

We propose a novel tree classification system called Treelogy, that fuses deep representations with hand-crafted features obtained from leaf images to perform leaf-based plant classification. Key to this system are segmentation of the leaf from an untextured background, using convolutional neural networks (CNNs) for learning deep representations, extracting hand-crafted features with a number o...

The main focus of the study is to implement and evaluates the DCT based plant leaf disease recognition using subtractive clustering for automatic recognition and classification. The proposed methodology of the study includes image processing and recognition by classification. The method consists of four phases: First, capturing plant leaf disease images and perform color space transformation, i...