Quantitative nuclear magnetic resonance (QNMR) spectroscopy for assessing the purity of technical grade agrochemicals: 2,4-dichlorophenoxyacetic acid (2,4-D) and sodium 2,2-dichloropropionate (Dalapon sodium)

Comparison of quantitative NMR spectroscopy (QNMR) with chromatographic methods such as gas chromatography (GC) or high-pressure liquid chromatography (HPLC) for the determination of the purity of and impurities in technical grade agrochemicals, 2,4-dichlorophenoxyacetic acid (2,4-D), 1, and Dalapon sodium (sodium 2,2-dichloropropionate), 10, has revealed that QNMR is more precise and accurate than the chromatographic methods. Quantitative impurity profiling of technical grade 1 is rapid and accurate using 600 MHz (1)H NMR. Extra dispersion at the relatively high frequency allowed full assignment of the NMR spectrum of 1 and its related organic impurities in technical samples. The percentage purity of 1 was measured by the difference QNMR method, which involves summing the amounts of impurities and subtracting from 100%. Results are superior in consistency to those obtained by chromatographic methods. The percentage purity of Dalapon sodium, 10, in technical grade batches is readily obtained by (1)H QNMR, using either the difference method or the internal standard method, using dimethyl sulfone (DMSO2) internally as a reference material, that is chemically unrelated to the analyte. The latter method also allows the simultaneous identification and quantification of impurities, many of which are either not accessible to or detectable by the chromatographic methods. Uncertainty budgets for the QNMR method are presented and demonstrate that the major contributors to uncertainty lie in the weighing of the chemicals and in purity of the standard reference material prior to the QNMR experiment.     

Engineering enzyme specificity by "substrate-assisted catalysis"

A novel approach to engineering enzyme specificity is presented in which a catalytic group from an enzyme is first removed by site-directed mutagenesis causing inactivation. Activity is then partially restored by substrates containing the missing catalytic functional group. Replacement of the catalytic His with Ala in the Bacillus amyloliquefaciens subtilisin gene (the mutant is designated His64Ala) by site-directed mutagenesis reduces the catalytic efficiency (kcat/Km) by a factor of a million when assayed with N-succinyl-L-Phe-L-Ala-L-Ala-L-Phe-p-nitroanilide (sFAAF-pNA). Model building studies showed that a His side chain at the P2 position of a substrate bound at the active site of subtilisin could be virtually superimposed on the catalytic His side chain of this serine protease. Accordingly, the His64Ala mutant hydrolyzes a His P2 substrate (sFAHF-pNA) up to 400 times faster than a homologous Ala P2 or Gln P2 substrate (sFAAF-pNA or sFAQF-pNA) at pH 8.0. In contrast, the wild-type enzyme hydrolyzes these three substrates with similar catalytic efficiencies. Additional data from substrate-dependent pH profiles and hydrolysis of large polypeptides indicate that the His64Ala mutant enzyme can recover partially the function of the lost catalytic histidine from a His P2 side chain on the substrate. Such "substrate-assisted catalysis" provides a new basis for engineering enzymes with very narrow and potentially useful substrate specificities. These studies also suggest a possible functional intermediate in the evolution of the catalytic triad of serine proteases.     

Biological Control of Yellow Nutsedge with the Indigenous Rust Fungus Puccinia canaliculata

Yellow nutsedge (Cyperus esculentus L.) is a serious weed problem in the United States and other countries. An indigenous rust fungus [Puccinia canaliculata (Schw.) Lagerh.], pathogenic on yellow nutsedge, was released in early spring as a potential biological control agent. The fungus inhibited nutsedge flowering and new tuber formation. The fungus also dehydrated and killed nutsedge plants. The successful control of yellow nutsedge by a rust epiphytotic under experimental conditions demonstrates the potential use of the rust in an integrated weed management system.     

The composite genome of the legume symbiont Sinorhizobium meliloti

The scarcity of usable nitrogen frequently limits plant growth. A tight metabolic association with rhizobial bacteria allows legumes to obtain nitrogen compounds by bacterial reduction of dinitrogen (N2) to ammonium (NH4+). We present here the annotated DNA sequence of the alpha-proteobacterium Sinorhizobium meliloti, the symbiont of alfalfa. The tripartite 6.7-megabase (Mb) genome comprises a 3.65-Mb chromosome, and 1.35-Mb pSymA and 1.68-Mb pSymB megaplasmids. Genome sequence analysis indicates that all three elements contribute, in varying degrees, to symbiosis and reveals how this genome may have emerged during evolution. The genome sequence will be useful in understanding the dynamics of interkingdom associations and of life in soil environments.     

Predicting Cotton Lint Yield Maps from Aerial Photographs

It is generally accepted that aerial images of growing crops provide spatial and temporal information about crop growth conditions and may even be indicative of crop yield. The focus of this study was to develop a straightforward technique for creating predictive cotton yield maps from aerial images. A total of ten fields in southern Georgia, USA, were studied during three growing seasons. Conventional (true color) aerial photographs of the fields were acquired during the growing season in two to four week intervals. The aerial photos were then digitized and analyzed using an unsupervised classification function of image analysis software. During harvest, conventional yield maps were created for each of the fields using a cotton picker mounted yield monitor. Classified images and yield maps were compared quantitatively and qualitatively. A pixel by pixel comparison of the classified images and yield maps showed that spatial agreement between the two gradually increased in the weeks after planting, maintained spatial agreement of between 40% and 60% during weeks eight to fourteen, and then gradually declined again. The highest spatial agreement between a classified image and a yield map was 78%. The highest average agreement was 52% and occurred 9.9 weeks after planting. The visual similarity between the classified images and the yield maps were striking. In all cases, the dates with the best visual agreement occurred between eight and ten weeks after planting, and generally, during July for southern Georgia. This method offers great potential for offering cotton farmers early-season maps that predict the spatial distribution of yield. Although these maps can not provide magnitudes, they clearly show the resulting yield patterns. With inherent knowledge of past performance, farmers can use this information to allocate resources, address crop growth problems, and, perhaps, improve the profitability of their farm operation. These maps are well suited to be offered to farmers as a service by a crop consultant or a cooperative.     

Galactose toxicity in the chick: hyperosmolality

Galactose-fed chicks have been found to develop severe hyperosmolar dehydration. Although biochemical abnormalities have been observed in the brain of the galactose-toxic chick, the observed physiologic alteration of serum osmolality could be the major factor responsible for the galactose toxicity syndrome in the chick.