Autoregulator-dependent Control of Extracellular Polysaccharide Production in Phytopathogenic Bacteria

Extracellular polysaccharides (EPSs) likely provide phytopathogenic bacteria a selective advantage both inside and outside plants. Despite the relatively scant knowledge about EPS biosynthesis in phytopathogenic bacteria, it clearly is a well controlled, complex, energy-intensive process. Unexpectedly, three phytopathogenic bacteria have been found to autoregulate EPS production in response to extracellular signal compounds (pheromones) that they produce. Like many bacteria, Pantoea stewartii subsp. stewartii produces a N-acyl-homoserine lactone (AHL) autoinducer. However, unlike most AHL-dependent autoinduction systems, that in P. stewartii subsp. stewartii somehow represses EPS production in the absence of autoinducer. Instead of an AHL-dependent system (which it also has), Ralstonia solanacearum uses a novel autoregulator identified as 3-hydroxypalmitic acid methyl ester to regulate EPS biosynthesis. A lack of this autoregulator in R. solanacearum results in repression of EPS biosynthesis by a complex two-component sensor/response regulator signal cascade. Xanthomonas campestris pv. campestris has two partially overlapping autoregulatory systems. The autoregulators are incompletely characterized, but one diffusible signal factor (DSF) is thought to be a fatty acid derivative and the other diffusible factor (DF) may be a butyrolactone. The autoregulation pathways in X. campestris pv. campestris are essentially unknown, but EPS production is controlled by both the DSF and DF systems, whereas production of extracellular enzymes and pigment production are regulated independently. In a confined micro-environment, population density and intercellular concentrations of an autoregulator will increase in parallel, so autoregulation is one way that bacteria can coordinate gene expression to synthesize EPS only at high cell density. However, because there is often limited evidence that it is actually cell density that is being detected, researchers should not assume a priori that autoregulation must function for quorum sensing. Some possible reasons for why phytopathogenic bacteria would benefit from delaying EPS production are discussed.     

Physical and biochemical properties of maize hardness and extrudates of selected hybrids

Protein and starch determinants of maize kernel hardness and extruded products were characterized to better define the role of endosperm texture during extrusion. Maize physical properties were correlated with total proteins and zein subclasses (p < 0.01). The extrusion process significantly altered protein solubility and increased protein fragmentation as measured by RP-HPLC and size exclusion chromatography. Harder grits and extrudates demonstrated higher amylose content, lower degree of starch damage, and fragmentation at different screw speeds than softer grits and extrudates. Differences in extrudate expansion ratio, water absorption index, water solubility index, oil absorption capacity, and breaking stress between harder and softer hybrids were related to protein aggregation and fragmentation as well as starch damage and fragmentation.     

Stratospheric memory and skill of extended-range weather forecasts

We use an empirical statistical model to demonstrate significant skill in making extended-range forecasts of the monthly-mean Arctic Oscillation (AO). Forecast skill derives from persistent circulation anomalies in the lowermost stratosphere and is greatest during boreal winter. A comparison to the Southern Hemisphere provides evidence that both the time scale and predictability of the AO depend on the presence of persistent circulation anomalies just above the tropopause. These circulation anomalies most likely affect the troposphere through changes to waves in the upper troposphere, which induce surface pressure changes that correspond to the AO.     

Segregating Hard Red Winter Wheat into Dough Factor Groups Using Single Kernel Measurements and Whole Grain Protein Analysis

In accordance with the Grain Quality Acts of 1986 and 1990, scientists at Kansas State University are studying the feasibility of implementing a quality-based marketing system for hard red winter (HRW) wheat in the Southern Plains. This research addresses the development of a segregation system that uses the single kernel characterization system and the whole grain near-infrared analyzer to evaluate the milling and baking quality of wheat as a single value called “dough factor”. This single value represents the amount of flour-water dough that can be produced from a given unit of wheat. Samples of HRW wheat (≈100 per location) were collected at five Kansas country elevators during the 1995 and 1996 harvests. After the dough factor was measured for individual samples, the samples were composited into seven dough factor groups to establish binning and segregation strategies and to explore the relationship between wheat quality measurements and dough factor groups. Results showed that dough factor groups were significantly different from each other and that dough factor groups were related (P < 0.05) to increases in test weight, single kernel weight, single kernel size, flour yield, and mixing time. Although locations showed year-to-year variability for test weight, kernel weight, and kernel size, the differences among dough factor groups for these characteristics across locations were consistent, indicating that the mean values within dough factor groups are similar regardless of location. The lack of significant differences in protein content among dough factor groups was attributable to high variability within dough factor groups between years. High protein values were present in low and high dough factor groups, indicating that protein content alone is not a good indicator of wheat quality. Patterns of differences in wheat quality characteristics among dough factor groups suggest that the seven groups studied can be reduced to three groups: <107, 107–112.9, ≥113. This study demonstrates that dough factor as a segregation and marketing tool is related to single kernel characteristics, differentiates wheats of varying quality, and reflects the end-use value of wheat.     

Ontology-based simulation of water flow in organic soils applied to Florida sugarcane

An ontology-based simulation (OntoSim) is a unique data modeling environment where soil–plant-nutrient processes are represented as database objects and the user-defined relationships among objects are used to generate computer code (Java) for running the simulation. The aim of this study was to model hydrologic processes of sugarcane-grown organic soils utilizing OntoSim in the Everglades Agricultural Area (EAA) of South Florida. This OntoSim-Sugarcane model describes the complex hydrology of sub-irrigation and open ditch drainage commonly used on Florida farms.Model calibration was conducted by (i) selecting rectangular farm water management units (<12 ha), which are encompassed with farm ditches, from two farms in the EAA, (ii) assembling all relevant input data including water tables (WT) recorded at the monitoring farm well of each unit, and (iii) optimizing the fits between the simulated and observed daily WT during two consecutive water years (WY). By calibrating two site-specific parameters – lateral saturated hydraulic conductivities of soil profiles and vertical saturated hydraulic conductivity of the underlying limestone bedrock – good agreement between simulated and observed daily WT was obtained (Nash–Sutcliffe efficiency coefficient >0.65; coefficient of residual mass <1%) within the units during WY96–97 (May 1995–April 1997). The validation of the model during subsequent WY98–99 at both units also showed Nash–Sutcliffe efficiency >0.55 and coefficient of residual mass <3%. It indicated that OntoSim-Sugarcane is able to simulate daily fluctuations of WT within the farm units and estimate lateral drainage/sub-irrigation and deep seepage that significantly contribute to the water balance at farms in the EAA. Thus, it can be a promising management tool to provide farmers with accurate assessment of water movement in this agricultural area.     

Assessing the effectiveness of a long‐standing rocky intertidal protected area and its contribution to the regional conservation of species,habitats and assemblages

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EFFICIENCY ANALYSIS AND THE EFFECT OF POLLUTION ON SHRIMP FARMS IN THE MEKONG RIVER DELTA

This article investigates the efficiency of intensive, semi-intensive, and extensive shrimp farming practices as well as the difference between the upstream and downstream efficiency of shrimp farms in the Mekong River Delta (MRD), Vietnam. Our article is the first to compare the efficiency of the 3 shrimp practices and investigate the difference between the efficiency of downstream and upstream farms. The efficiency of shrimp farms is measured using group-frontier and meta-frontier analysis on a sample of 292 farms. The results show that, on average, shrimp farms are inefficient; extensive farms are more efficient than intensive and semi-intensive farms; and, controlling for key socio-economic factors, upstream farms are more efficient than downstream farms, suggesting that pollution from upstream farms may influence shrimp farm efficiency. The results give some direction for improvement and some evidence to shrimp farmers and policymakers in the MRD to take the pollution problem seriously and find solutions for more sustainable development.     

Rating fixed film nitrifying biofilters used in recirculating aquaculture systems

Predicting the performance of biofilters is an engineering challenge that is critical to both designers and managers. The task is complicated by the wide variety of water quality expectations and environmental conditions displayed by a recirculating aquaculture system (RAS). A myriad of biofilters designs have been generated reflecting approaches of engineers attempting to maximize specific surface area and oxygen transfer within the context of a biofilm management strategy. A rating strategy is presented for biofilters to facilitate the identification of appropriate matches between biofiltration formats and RAS applications. As a foundation, a previously proposed RAS classification system based upon salinity, temperature and trophic levels is upgraded to create 17 systems classifications. A biofilter classification system identifies seven combinations of trophic level and pH which should be sufficient to serve the RAS demands. Temperature and salinity are neglected as a means of simplifying the approach. An experimental methodology based upon chemical feeds is proposed to represent the steady-state RAS performance of the biofilters. Data is summarized by linear analysis of filter performance for concentration ranges below 1.0 g TAN m⁻³ and simple averaging is proposed for higher trophic levels. Input from the aquacultural engineering community and RAS aquaculturists is required to further refine the approach prior to endorsement.     

Regulatory Concerns with Pesticide Use in Turf

Because of the costs incurred in their development, it is unlikely that pesticides will be developed solely for use in amenity turf. This means that the basic set of data needed to answer regulatory concerns should already be available for the pesticide concerned. The basic controls involved in pesticide registration are described, with the EC being taken as an example. The paper describes the areas where, because of different concerns, more data may need to be generated in order to seek registration of use of a product on amenity turf. In most cases regulatory requirements can be met by reinterpreting the existing data, taking into account the use of pesticides on amenity turf. Other regulatory issues concerning the use of pesticides in amenity turf are discussed.