Galacturonosyltransferases (GalATs) are required for the synthesis of pectin, a family of complex polysaccharides present in the cell walls of all land plants. We report the identification of a pectin GalAT (GAUT1) using peptide sequences obtained from Arabidopsis thaliana proteins partially purified for homogalacturonan (HG) α-1,4-GalAT activity. Transient expression of GAUT1 cDNA in the human embryonic kidney cell line HEK293 yielded uridine diphosphogalacturonic acid:GalAT activity. Polyclonal antibodies generated against GAUT1 immunoabsorbed HG α-1,4-GalAT activity from Arabidopsis solubilized membrane proteins. blast analysis of the Arabidopsis genome identified a family of 25 genes with high sequence similarity to GAUT1 and homologous genes in other dicots, in rice, and in Physcomitrella . Sequence alignment and phylogenetic Bayesian analysis of the Arabidopsis GAUT1-related gene family separates them into four related clades of GAUT and GAUT-like genes that are distinct from the other Arabidopsis members of glycosyltransferase family 8. The identification of GAUT1 as a HG GalAT and of the GAUT1-related gene family provides the genetic and biochemical tools required to study the function of these genes in pectin synthesis.

The effects of land use on the relationships among denitrification, NO3 2 -N, dissolved organic C (DOC), and other environmental parameters were examined in 9 headwater streams (3 each in forested, agricultural, and urban-dominated subwatersheds) in the Kalamazoo River Water- shed, Michigan. Sediment denitrification rates were determined using the chloramphenicol-amended acetylene inhibition technique. Agricultural streams had high concentrations of NO3 2 -N, DOC, soluble reactive P, and NH4 1 -N, whereas forested streams had the lowest concentrations of these nutrients, and urban streams generally exhibited intermediate concentrations. Sediment denitrification rates were highest in agricultural streams and lowest in forested streams throughout the study period. Availability of NO3 2 -N was the dominant environmental predictor of sediment denitrification rates, limiting denitrification when NO3 2 -N concentrations were below a calculated threshold of 0.4 mg NO 3 2 -N/L. Other potential controlling variables (e.g., DOC, dissolved O2, water temperature, and sediment organic matter content) influenced denitrification rates secondarily. Despite higher denitri- fication rates in agricultural and urban streams compared to forested streams, sediment denitrifica- tion removed a smaller proportion of the stream NO3 2 -N load in agricultural and urban streams relative to forested streams.

Cotton (Gossypium hirsutum) provides the world9s dominant renewable textile fiber, and cotton fiber is valued as a research model because of its extensive elongation and secondary wall thickening. Previously, it was assumed that fibers elongated as individual cells. In contrast, observation by cryo-field emission-scanning electron microscopy of cotton fibers developing in situ within the boll demonstrated that fibers elongate within tissue-like bundles. These bundles were entrained by twisting fiber tips and consolidated by adhesion of a cotton fiber middle lamella (CFML). The fiber bundles consolidated via the CFML ultimately formed a packet of fiber around each seed, which helps explain how thousands of cotton fibers achieve their great length within a confined space. The cell wall nature of the CFML was characterized using transmission electron microscopy, including polymer epitope labeling. Toward the end of elongation, up-regulation occurred in gene expression and enzyme activities related to cell wall hydrolysis, and targeted breakdown of the CFML restored fiber individuality. At the same time, losses occurred in certain cell wall polymer epitopes (as revealed by comprehensive microarray polymer profiling) and sugars within noncellulosic matrix components (as revealed by gas chromatography-mass spectrometry analysis of derivatized neutral and acidic glycosyl residues). Broadly, these data show that adhesion modulated by an outer layer of the primary wall can coordinate the extensive growth of a large group of cells and illustrate dynamic changes in primary wall structure and composition occurring during the differentiation of one cell type that spends only part of its life as a tissue.

The triple-bottom-line approach to sustainability in agriculture requires multi- and inter-disciplinary expertise and remains a major design and implementation challenge. Tools are needed to link extension agents, development workers, farmers, and other agriculture decision-makers to information related to practices that improve sustainability across agricultural landscapes. The digital age has brought many new cloud-based and mobile device–accessible software applications (apps) targeted at farmers and others in the agriculture sector; however, the effectiveness of these tools for advancing sustainability goals is unknown. Here, we review apps for agriculture in order to identify gaps in information provisioning and sharing for tools that connect decision-makers to knowledge in support of sustainable agricultural landscapes. The major findings are (1) Agricultural apps can be categorized as supporting regulatory compliance, equipment optimization, farming simulator games, information management, agronomic reference information, product tracking, pest identification, emissions accounting, or benchmarks for marketing claims. (2) Many apps are developed to link specific products for single solutions, such as GPS-guided crop implementation or sensors within Internet-of-things connectivity. (3) While pilots, prototypes, and case studies are available in both Apple and Android digital markets, public mobile apps to improve multidirectional agriculture knowledge exchange are limited and poorly documented. (4) There remains a need for apps emphasizing knowledge exchange and resource discovery, rather than simply information delivery, to help farmers identify evidence-based practices that improve indicators of sustainability. (5) Development of a digital decision support tool requires early and ongoing interactions with targeted end users to clarify app performance objectives and social networking preferences, ensure reliability of scientific input and business management plans, and optimize the user experience.

There is widespread consensus about the need for landscape sustainability but little agreement about how to define or measure it.