Forest growth models form one of several important prerequisites for sustainable management. The complexity of tropical moist forest means that there is often little objective information to classify sites and species for growth modelling and yield prediction. Classification based on observable morphological characteristics may be a useful surrogate for, or supplement to, other alternatives. Th...

In this research, identification and classification of cotton diseases is done. The pattern of disease is important part where some features like the colour of actual infected image are extracted from image. There are so many diseases occurred on cotton leaf so the leaf color is different for different diseases. This paper uses k-mean clustering with Discrete Wavelet Transform for efficient pla...

Plant has plenty use in foodstuff, medicine and industry, and is also vitally important for environmental protection. So, it is important and urgent to recognize and classify plant species. Plant classification based on leaf images is a basic research of botanical area and agricultural production. Due to the high nature complexity and high dimensionality of leaf image data, dimensional reductio...

PREMISE OF THE STUDY In dioecious species, selection should favor different leaf sizes in males and females whenever the sexes experience distinct environments or constraints such as different costs of reproduction. We took advantage of a long-term experimental study of Ocotea tenera (Lauraceae), a dioecious understory tree in Monteverde, Costa Rica, to explore leaf size differences between gen...

We examined open-grown Acer mono Maxim. trees of different sizes to test the hypotheses that (1) hydraulic limitation increases with tree size, thereby reducing photosynthesis, and (2) photosynthetic water- and nitrogen-use efficiencies change with tree size. Maximum net assimilation rate per unit dry mass was significantly lower in large trees than in small trees, whereas leaf nitrogen concent...

There are a lot of techniques relevant for the purpose automated leaf recognition for plant classification. Many algorithms have been introduced in the past decade and achieved good performance. Efforts have focused upon many other fields but properties of features have not been well investigated. A group of features is selected in advance but important feature properties are not well used to f...

BACKGROUND AND AIMS Corner's rule states that thicker twigs bear larger leaves. The exact nature of this relationship and why it should occur has been the subject of numerous studies. It is obvious that thicker twigs should support greater total leaf area ([Formula: see text]) for hydraulical and mechanical reasons. But it is not obvious why mean leaf size ([Formula: see text]) should scale pos...

BACKGROUND AND AIMS Leaves expand during a given period of time until they reach their final size and form, which is called determinate growth. Duration of leaf expansion is stable when expressed in thermal-time and in the absence of stress, and consequently it is often proposed that it is controlled by a robust programme at the plant scale. The usual hypothesis is that growth cessation occurs ...

The allocation and recognition of cotton leaf diseases are of the major importance as they have a cogent and momentous impact on quality and production of cotton. This paper presents a modus operandi for automatic classification of cotton leaf diseases through feature extraction of leaf symptoms from digital images. Otsu’s segmentation method is used for extracting color and shape features. Sup...

Leaf expansion in the fast-growing tree, Populus x euramericana was stimulated by elevated [CO(2)] in a closed-canopy forest plantation, exposed using a free air CO(2) enrichment technique enabling long-term experimentation in field conditions. The effects of elevated [CO(2)] over time were characterized and related to the leaf plastochron index (LPI), and showed that leaf expansion was stimula...