Community improvement through resource conservation and development : Q's and A'S.

Issued June 1974.

Evaluation of eight spring onion genotypes, sulphur nutrition and soil-type effects with an electronic nose

Genotype, sulphur (S) nutrition and soil-type effects on spring onion quality were assessed using a 32-conducting polymer sensor E-nose. Relative changes in sensor resistance ratio (% dR/R) varied among eight spring onion genotypes. The % dR/R was reduced by S application in four of the eight genotypes. For the other four genotypes, S application gave no change in % dR/R in three, and increased % dR/R in the other. E-nose classification of headspace volatiles by a two-dimensional principal component analysis (PCA) plot for spring onion genotypes differed for S fertilisation vs. no S fertilisation. Headspace volatiles data set clusters for cv. 'White Lisbon' grown on clay or on sandy loam overlapped when 2.9 [Mahalanobis distance value (D2) = 1.6], or 5.8-(D2 = 0.3) kg S ha-1 was added. In contrast, clear separation (D2 = 7.5) was recorded for headspace volatile clusters for 0 kg S hd-1 on clay vs. sandy loam. Addition of 5.8 kg S ha-1 increased pyruvic acid content (mmole g-1 fresh weight) by 1.7-fold on average across the eight genotypes. However, increased S from 2.9 to 5.8 kg ha-1 did not significantly (P > 0.05) influence % dR/R, % dry matter (DM) or total soluble solids (TSS) contents, but significantly (P < 0.05) increased pyruvic acid content. TSS was significantly (P < 0.05) reduced by S addition, while % DM was unaffected. In conclusion, the 32-conducting polymer E-nose discerned differences in spring onion quality that were attributable to genotype and to variations in growing conditions as shown by the significant (P < 0.05) interaction effects for % dR/R.

Decadal Change in Vegetation and Soil Phosphorus Pattern across the Everglades Landscape

Wetlands respond to nutrient enrichment with characteristic increases in soil nutrients and shifts in plant community composition. These responses to eutrophication tend to be more rapid and longer lasting in oligotrophic systems. In this study, we documented changes associated with water quality from 1989 to 1999 in oligotrophic Everglades wetlands. We accomplished this by resampling soils and macrophytes along four transects in 1999 that were originally sampled in 1989. In addition to documenting soil phosphorus (P) levels and decadal changes in plant species composition at the same sites, we report macrophyte tissue nutrient and biomass data from 1999 for future temporal comparisons. Water quality improved throughout much of the Everglades in the 1990s. In spite of this improvement, though, we found that water quality impacts worsened during this time in areas of the northern Everglades (western Loxahatchee National Wildlife Refuge [NWR] and Water Conservation Area [WCA] 2A). Zones of high soil P (exceeding 700 mg P kg−1 dry wt. soil) increased to more than 1 km from the western margin canal into the Loxahatchee NWR and more than 4 km from northern boundary canal into WCA-2A. This doubling of the high soil P zones since 1989 was paralleled with an expansion of cattail (Typha spp.)-dominated marsh in both regions. Macrophyte species richness declined in both areas from 1989 to 1999 (27% in the Loxahatchee NWR and 33% in WCA-2A). In contrast, areas well south of the Everglades Agricultural Area, including WCA-3A and Everglades National Park (ENP), did not decline during this time. We found no significant decadal change in plant community patterns from 1989 and 1999 along transects in southern WCA-3A or Shark River Slough (ENP). Our 1999 sampling also included a new transect in Taylor Slough (ENP), which will allow change analysis here in the future. Regular sampling of these transects, to verify decadal-scale environmental impacts or improvements, will continue to be an important tool for long-term management and restoration of the Everglades.

Diagnostic Tests and their Application in the Management of Soil- and Water-borne Oomycete Pathogen Species

Oomycete diseases cause significant losses across a broad range of crop and aquaculture commodities worldwide. These losses can be greatly reduced by disease management practices steered by accurate and early diagnoses of pathogen presence. Determinations of disease potential can help guide optimal crop rotation regimes, varietal selections, targeted control measures, harvest timings and crop post-harvest handling. Pathogen detection prior to infection can also reduce the incidence of disease epidemics. Classical methods for the isolation of oomycete pathogens are normally deployed only after disease symptom appearance. These processes are often-time consuming, relying on culturing the putative pathogen(s) and the availability of expert taxonomic skills for accurate identification; a situation that frequently results in either delayed application, or routine ‘blanket’ over-application of control measures. Increasing concerns about pesticides in the environment and the food chain, removal or restriction of their usage combined with rising costs have focussed interest in the development and improvement of disease management systems. To be effective, these require timely, accurate and preferably quantitatve diagnoses. A wide range of rapid diagnostic tools, from point of care immunodiagnostic kits to next generation nucleotide sequencing have potential application in oomycete disease management. Here we review currently-available as well as promising new technologies in the context of commercial agricultural production systems, considering the impacts of specific biotic and abiotic and other important factors such as speed and ease of access to information and cost effectiveness

Raman spectroscopy of some complex arsenate minerals—implications for soil remediation

The application of spectroscopy to the study of contaminants in soils is important. Among the many contaminants is arsenic, which is highly labile and may leach to non-contaminated areas. Minerals of arsenate may form depending upon the availability of specific cations for example calcium and iron. Such minerals include carminite, pharmacosiderite and talmessite. Each of these arsenate minerals can be identified by its characteristic Raman spectrum enabling identification.