Between-tree variation in fruit quality and fruit mineral concentrations of Hass avocados

Inconsistent internal fruit quality in Hass avocados affects consumer confidence. To determine the influence of individual trees on fruit quality, Hass avocado fruit were harvested from adjacent trees of similar external appearance in 3 commercial orchards in 1998 and 1 orchard in 1999. The trees in each orchard were grown with similar commercial practices and in similar soil types. Within each location, there were significant (P < 0.05) differences in the mean ripe fruit quality between trees with respect to fruit body rot severity ( mainly anthracnose) with and without cold storage, internal disorders severity due to diffuse discolouration and vascular browning ( after cold storage), days to ripen, percentage dry matter, and the percentage of the skin area with purple-black colour when ripe. These effects were also noted in the same orchard in 1999. There were significant (P < 0.05) differences in fruit flesh calcium, magnesium, potassium, boron and zinc concentrations between trees. Significant (P < 0.05) correlations were observed between average fruit mineral concentrations in each tree ( particularly calcium, magnesium and potassium) and body rot severity, percentage dry matter and fruit mass. There was little conclusive evidence that characteristics such as the growth of the non-suberised roots or the degree of scion under- or overgrowth was involved in these tree effects; however, differences between trees with respect to other rootstock characteristics may be involved. The inconsistency of the correlations across sites and years suggested that other factors apart from tree influences could also affect the relationship between fruit minerals and fruit quality.

Coconut revival: new possibilities for the 'tree of life'

Proceedings of the International Coconut Forum held in Cairns, Australia, 22-24 November 2005. Coconut is one of the most important crops grown in the humid tropics, with more than 11 million farmers, mostly smallholders with low income, growing the palm in 90 countries. These proceedings document the vast range of topics covered in the forum, including R&D, business and government, and regional and international agency interests.

Seasonal dynamics and operational monitoring of hedgerow olive tree transpiration in response to applied water

We used 2012 sap flow measurements to assess the seasonal dynamics of daily plant transpiration (ETc) in a high-density olive orchard (Olea europaea L. cv. ‘Arbequina’) with a well-watered (HI) control treatment A to supply 100 % of the crop water needs, and a moderately (MI) watered treatment B that replaced 70% of crop needs. To assure that treatment A was well-watered, we compared field daily ETc values against ETc obtained with the Penman-Monteith (PM) combination equation incorporating the Orgaz et al. (2007) bulk daily canopy conductance (gc) model, validated for our non-limiting conditions. We then tested the hypothesis of indirectly monitoring olive ETc from readily available vegetation index (VI) and ground-based plant water stress indicator. In the process we used the FAO56 dual crop coefficient (Kc) approach. For the HI olive trees we defined Kcb as the basal transpiration coefficient, and we related Kcb to remotely sensed Soil Adjusted Vegetation Index (SAVI) through a Kcb-SAVI functional relationship. For the MI treatment, we defined the actual transpiration ETc as the product of Kcb and the stress reduction coefficient Ks obtained as the ratio of actual to crop ETc, and we correlated Ks with MI midday stem water potential (ψst) values through a Ks-ψ functional relationship. Operational monitoring of ETc was then implemented with the ETc = Kcb(SAVI)Ks(ψ)ETo relationship stemmed from the FAO56 approach and validated taking as inputs collected SAVI and ψst data reporting to year 2011. Low validation error (6%) and high goodness-of-fit of prediction were observed (R2 = 0.94, RSME = 0.2 mm day-1, P = 0.0015), allowing to consider that under field conditions it is possible to predict ETc values for our hedgerow olive orchards if SAVI and water potential (ψst) values are known.

K-tree : large scale document clustering

We introduce K-tree in an information retrieval context. It is an efficient approximation of the k-means clustering algorithm. Unlike k-means it forms a hierarchy of clusters. It has been extended to address issues with sparse representations. We compare performance and quality to CLUTO using document collections. The K-tree has a low time complexity that is suitable for large document collections. This tree structure allows for efficient disk based implementations where space requirements exceed that of main memory.

How is a fruit tree like you? Using artistic metaphors to explore and develop emotional competence in children

Counselling children often requires the use of supplementary strategies in order to interest and engage the child in the therapeutic process. One such strategy is the Metaphorical Fruit Tree (MFT); an art metaphor suited to exploring and developing self-concept. Quantitative and qualitative data was used to explore the relationships between children’s ability to use metaphor, age, gender, and level of emotional competence (N = 58). Quantitative and qualitative analyses revealed a significant negative relationship between self-reported emotional competence and ability to use the MFT. It is proposed that children rely on different processes to understand self and as children’s ability to cognitively report on their emotional capabilities via the Emotional Competence Questionnaire (ECQ) increases, their ability to report creatively on those capabilities via the MFT is undermined. It is suggested that the MFT may be used, via creative processes and as an alternative to cognitive processes, to increase understanding and awareness of intrapersonal and interpersonal concepts of self in the child during counselling.

Document clustering with K-tree

This paper describes the approach taken to the XML Mining track at INEX 2008 by a group at the Queensland University of Technology. We introduce the K-tree clustering algorithm in an Information Retrieval context by adapting it for document clustering. Many large scale problems exist in document clustering. K-tree scales well with large inputs due to its low complexity. It offers promising results both in terms of efficiency and quality. Document classification was completed using Support Vector Machines.

Towards automatic tree crown detection and delineation in spectral feature space using PCNN and morphological reconstruction

The application of object-based approaches to the problem of extracting vegetation information from images requires accurate delineation of individual tree crowns. This paper presents an automated method for individual tree crown detection and delineation by applying a simplified PCNN model in spectral feature space followed by post-processing using morphological reconstruction. The algorithm was tested on high resolution multi-spectral aerial images and the results are compared with two existing image segmentation algorithms. The results demonstrate that our algorithm outperforms the other two solutions with the average accuracy of 81.8%.

Random Indexing K-tree

Random Indexing K-tree is the combination of two algorithms suited for large scale document clustering.