Chitin mixed in potting soil alters lettuce growth, the survival of zoonotic bacteria on the leaves and associated rhizosphere microbiology

Chitin is a promising soil amendment for improving soil quality, plant growth, and plant resilience. The objectives of this study were twofold. First, to study the effect of chitin mixed in potting soil on lettuce growth and on the survival of two zoonotic bacterial pathogens, Escherichia colt O157:H7 and Salmonella enterica on the lettuce leaves. Second, to assess the related changes in the microbial lettuce rhizosphere, using phospholipid fatty acid (PLFA) analysis and amplicon sequencing of a bacterial 16S rRNA gene fragment and the fungal ITS2. As a result of chitin addition, lettuce fresh yield weight was significantly increased. S. enterica survival in the lettuce phyllosphere was significantly reduced. The E. coli O157:H7 survival was also lowered, but not significantly. Moreover, significant changes were observed in the bacterial and fungal community of the lettuce rhizosphere. PLFA analysis showed a significant increase in fungal and bacterial biomass. Amplicon sequencing showed no increase in fungal and bacterial biodiversity, but relative abundances of the bacterial phyla Acidobacteria, Verrucomicrobia, Actinobacteria, Bacteroidetes, and Proteobacteria and the fungal phyla Ascomycota, Basidiomycota, and Zygomycota were significantly changed. More specifically, a more than 10-fold increase was observed for operational taxonomic units belonging to the bacterial genera Cellvibrio, Pedobacter, Dyadobacter, and Streptomyces and to the fungal genera Lecanicillium and Mortierella. These genera include several species previously reported to be involved in biocontrol, plant growth promotion, the nitrogen cycle and chitin degradation. These results enhance the understanding of the response of the rhizosphere microbiome to chitin amendment. Moreover, this is the first study to investigate the use of soil amendments to control the survival of S. enterica on plant leaves

A novel Arabidopsis pathosystem reveals cooperation of multiple hormonal response-pathways in host resistance against the global crop destroyer Macrophomina phaseolina.

Dubbed as a "global destroyer of crops", the soil-borne fungus Macrophomina phaseolina (Mp) infects more than 500 plant species including many economically important cash crops. Host defenses against infection by this pathogen are poorly understood. We established interactions between Mp and Arabidopsis thaliana (Arabidopsis) as a model system to quantitatively assess host factors affecting the outcome of Mp infections. Using agar plate-based infection assays with different Arabidopsis genotypes, we found signaling mechanisms dependent on the plant hormones ethylene, jasmonic acid and salicylic acid to control host defense against this pathogen. By profiling host transcripts in Mp-infected roots of the wild-type Arabidopsis accession Col-0 and ein2/jar1, an ethylene/jasmonic acid-signaling deficient mutant that exhibits enhanced susceptibility to this pathogen, we identified hundreds of genes potentially contributing to a diverse array of defense responses, which seem coordinated by complex interplay between multiple hormonal response-pathways. Our results establish Mp/Arabidopsis interactions as a useful model pathosystem, allowing for application of the vast genomics-related resources of this versatile model plant to the systematic investigation of previously understudied host defenses against a major crop plant pathogen

Centers for the commercial development of space

In 1985, NASA initiated an innovative effort called Centers for the Commercial Development of Space (CCDS). The CCDS program was designed to increase private-sector interest and investment in space-related activities, while encouraging U.S. economic leadership and stimulating advances in promising areas of research and development. Research conducted in the Centers handling the following areas is summarized: materials processing; life sciences; remote sensing; automation and robotics; space propulsion; space structures and materials; and space power

Aquaculture Asia, vol. 8, no. 4, pp.1-52, October - December 2003

CONTENTS: Freshwater prawn, Macrobrachium nobilii a promising candidate for rural nutrition, by Pitchimuthu Mariappan, P. Balamurugan, and Chellam Balasundaram. Snapshots of a clean, innovative, socially responsible fishfarm in Sri Lanka, by Pedro Bueno. Introduction of rainbow trout Onchorynchus mykiss in Nepal: Constraints and prospects, by Tek Bahadur Gurung, Sadhu Ram Basnet. Tilapia seed production in Ho Chi Minh City, Southern Vietnam, by H. P. V. Huy, A. MacNiven, N. V. Tu, Ram C. Bhujel and David C. Little. Seaweed Mariculture: Scope And Potential In India, by Sajid I. Khan and S. B. Satam. Growth enhancement of carp and prawn through dietary sodium chloride supplementation, by P.Keshavanath, B. Gangadhara and Savitha Khadri. Fertilization, soil and water quality management in small-scale ponds, by S. Adhikari Shrimp harvesting technology on the south west coast of Bangladesh, by S. M. Nazmul Alam, Michael J. Phillips and C. K. Lin. The “Gher Revolution”, by M.C. Nandeesha [Farmers as Scientists series] Aquaculture Compendium – case study component, by Peter Edwards. Rice-Fish Culture in China, by Fang Xiuzhen. Exercising responsibilities to tackle aquatic animal diseases, by CV Mohan. Application of immunostimulants in larviculture: Feasibility and challenges, by ZhouJin. Marine Finfish Sectio

Enteric diseases in pigs from weaning to slaughter

The general aim of this thesis was to study enteric diseases in growing pigs, with special reference to diseases caused by Brachyspira hyodysenteriae and Lawsonia intracellularis. The occurrence of enteric diseases in “growers” is a problem of increasing importance in Sweden and an understanding of the mechanisms by which the microorganisms causes enteric diseases is essential to develop good prophylactic measures. The most important microorganisms involved in enteric diseases in grower pigs were identified as Lawsonia intracellularis and Brachyspira pilosicoli, as determined by necropsy, microbiological and histopathological examinations performed on representative growing pigs from good and poor performing herds. Diagnostic methods based on polymerase chain reaction for L. intracellularis in tissue or faecal samples were established and the results related to those obtained by necropsy and serology. An internal control, a mimic, was constructed to demonstrate inhibition of the PCR reactions and to evaluate different preparation methods. The methods for the demonstration of L. intracellularis in tissue samples were sensitive and specific, and the bacteria were reliably identified in faeces from pigs with overt disease. A number of factors interacting in the clinical expression of swine dysentery were evaluated. In this work, group-housing of pigs and the addition of 50% soybean meal in feed was shown to predispose for infection. A model was developed that enabled the sequential monitoring of disease in single animals by repeated endoscopy and biopsy sampling through a caecal cannula. This reduced the number of experimental animals required and increased the accuracy of the study. The general condition of the animal was not affected. The model was used to study the development of experimentally induced swine dysentery and the sequential development of lesions was characterised by histopathology and immunohistochemistry. An increase in the acute phase proteins serum amyloid A and haptoglobin and in monocytes was seen when haemorrhagic dysentery occurred

Handbook of Computational Intelligence in Manufacturing and Production Management

Artificial intelligence (AI) is simply a way of providing a computer or a machine to think intelligently like human beings. Since human intelligence is a complex abstraction, scientists have only recently began to understand and make certain assumptions on how people think and to apply these assumptions in order to design AI programs. It is a vast knowledge base discipline that covers reasoning, machine learning, planning, intelligent search, and perception building. Traditional AI had the limitations to meet the increasing demand of search, optimization, and machine learning in the areas of large, biological, and commercial database information systems and management of factory automation for different industries such as power, automobile, aerospace, and chemical plants. The drawbacks of classical AI became more pronounced due to successive failures of the decade long Japanese project on fifth generation computing machines. The limitation of traditional AI gave rise to development of new computational methods in various applications of engineering and management problems. As a result, these computational techniques emerged as a new discipline called computational intelligence (CI)