Effects of Selection on Morphological Characteristics in \u3ci\u3eSetaria sphacelata\u3c/i\u3e (Schumach.) Moss

Cattle production in Florida is limited by the lack of available warm-season forages adapted to the cool winters of the region. Setaria (S. sphacelata) has demonstrated green growth during cool conditions in subtropical climates around the world, and has the potential to fill this niche in cattle production in Florida. Four populations were selected in Gainesville and Ona, Florida: two cycles of selection for increased head number, one cycle for increased leaf width and one cycle for grazing tolerance. The objectives of this research were to compare these populations morphologically to determine changes due to selection. Selection for leaf width increased this trait while maintaining other morphological characteristics constant. Selection for head number decreased plant height and increased head number in each cycle, and decreased leaf width and inflorescence length in the second cycle. Selection for grazing regrowth resulted in reduced plant height and inflorescence length. Concern regarding susceptibility of Setaria to chinch bug and possible winter killing in Florida remain to be resolved before this species may be commercialized in Florida

Development of a Bahiagrass \u3cem\u3ePaspalum Notatum\u3c/em\u3e Flugge With Increased Short-Day Biomass

Low herbage productivity of subtropical grasses during the short-day winter months of October through to March can place a severe burden on livestock producers in Southeastern U.S. Researchers at the University of Florida (Sinclair et al., 2001) hypothesised that the decrease in forage production might result from physiological dormancy induced by short day length. A study using artificial lights to extend the day length demonstrated that maintaining the day length at 15 hr during the short-day length period increased \u27Pensacola\u27 bahiagrass P. notatum Flugge saure Parodi forage yield 122% when compared with normal photoperiod (Mislevy et al., 2001). A Pensacola-derived bahiagrass population was selected for increased vegetative growth under short-day length using restricted recurrent phenotypic selection for three cycles (UF Cycle 3) to increase forage yield. Plants that comprise this population were less sensitive to short photoperiod and produced increased forage mass during the short days. The objective of this clipping study was to evaluate forage production and forage nutritive value of UF Cycle 3 compared with selected standard entries during short and long day length periods

Extended Daylength to Increase Fall/Winter Yields of Warm-Season Perennial Grasses

Low forage production in fall/winter months is a severe limitation for dairy and beef cattle producers in the southeastern U.S. It was hypothesized that shrt daylengths during these months induce a physiological dormancy in grasses. Four grasses [Pensacola bahiagrass, Paspalum notatum Flugge; Tifton 85 and Florakirk bermudagrass, Cynodon dactylon (L.); Florona stargrass, C. nlemfuensis Vanderyst var. nlemfuensis] were subjected to extended daylengths during the winter/fall months in a field test. Pensacola bahiagrass and Tifton 85 bermudagrass showed especially dramatic increases in forage yield during the fall/winter season under the extended daylength. Genetic elimination of daylength sensitivity in these grasses appears to be a viable option for increasing year-round forage production

Prediction of N Fractions of Warm-Season Grasses with Near-Infrared Reflectance Spectroscopy

Warm-season (C4), the most common forage for beef production in much of the U.S.A., although having a higher productivity than temperate forages are of a lower quality. Current feeding standards (NRC, 1996) have adapted the Cornell Net Carbohydrate and Protein System (Sniffen et al., 1992) to more accurately characterize forage quality. As these procedures are tedious, data is limited on genetic and management factors influencing quality parameters in C4 species. The objective of this research was to determine if near-infrared reflectance spectroscopy (NIRS) could be used to predict the various N fractions in three C4 grasses

Influence of Grazing Frequency on Biomass Production Using Several Selected Tropical Grasses

To provide commercial growers with forage grasses that produce well throughout the year, there is a constant need for screening and testing new germplasm. Two rhodesgrasses (Chloris gayana cv. Rhods and Callide), four stargrasses (Cynodon nlemfuensis Vanderyst var. nlemfuensis cv. Florona, Zimbabwe, Okeechobee, and Rhodesian No. 2), one bermudagrass (C. dactylon var. dactylon cv. Jiggs), and one creeping signalgrass (Brachiaria humidicola CIAT 6369) were tested under a mob-grazing system. Dry biomass yield increased linearly as grazing frequency (GF) was delayed from 2 to 7 weeks. The cultivars, Florona, Zimbabwe and Okeechobee stargrasses and Jiggs bermudagrass, yielded best during the warm season regardless of GF. However, during the cool season Rhods rhodesgrass, Florona stargrass and Jiggs bermudagrass were generally most productive. These grasses were also the most persistent, averaging better than 97% ground cover after 3 years of grazing

Photoperiod Response in Pensacola Bahiagrass

Photoperiod response has been found to influence the growth and development of \u3ePensacola\u27 derived bahiagrass (Paspalum notatum Flugge var. saure Parodi). Four selection cycles [\u3ePensacola= (Cycle 0), Cycle 4, \u3eTifton 9\u27 (Cycle 9) and Cycle 23] resulting from recurrent restricted phenotypic selection (RRPS) of spaced-plants, were field grown in 1999 and 2000, to study photoperiod sensitivity among genotypes. Two day-length treatments were imposed on the field grown plants. One treatment, used only natural light. The second treatment imposed an extended day-length treatment using Quartz-halogen lamps, installed in the field during the fall and winter, to extend day-length to15 hours. The top growth of individual plants was harvested three times during the fall and winter seasons and stolon spread was measured in mid February, 2000. Top growth was increased by the extended day-length treatment for Pensacola and RRPS Cycle 4 in all three harvest dates. Top growth of Tifton 9 was unaffected by the extended light for the September harvest, but increased in the late October and late January harvests. RRPS Cycle 23 plants grown under natural light, out-yielded the plants grown under extended light treatment, for the first two harvests. There were no differences in yields of RRPS Cycle 23 plants from extended or natural light from the January harvest. The later cycles, Tifton 9 and RRPS Cycle 23, were less sensitive to day-length, than RRPS Cycles 0 and 4. Extended daylength, for all cycles, dramatically reduced stolon spread by nearly half that of the plants grown under natural light. Results from this experiment demonstrate a high sensitivity in growth and development of Pensacola-derived bahiagrass to day-length

Technology enhanced assessment in complex collaborative settings

Building upon discussions by the Assessment Working Group at EDUsummIT 2013, this article reviews recent developments in technology enabled assessments of collaborative problem solving in order to point out where computerised assessments are particularly useful (and where non-computerised assessments need to be retained or developed) while assuring that the purposes and designs are transparent and empowering for teachers and learners. Technology enabled assessments of higher order critical thinking in a collaborative social context can provide data about the actions, communications and products created by a learner in a designed task space. Principled assessment design is required in order for such a space to provide trustworthy evidence of learning, and the design must incorporate and take account of the engagement of the audiences for the assessment as well as vary with the purposes and contexts of the assessment. Technology enhanced assessment enables in-depth unobtrusive documentation or ‘quiet assessment’ of the many layers and dynamics of authentic performance and allows greater flexibility and dynamic interactions in and among the design features. Most important for assessment FOR learning, are interactive features that allow the learner to turn up or down the intensity, amount and sharpness of the information needed for self-absorption and adoption of the feedback. Most important in assessment OF learning, are features that compare the learner with external standards of performance. Most important in assessment AS learning, are features that allow multiple performances and a wide array of affordances for authentic action, communication and the production of artefacts

A hierarchical latent response model for inferences about examinee engagement in terms of guessing and item‐level non‐response

In low‐stakes assessments, test performance has few or no consequences for examinees themselves, so that examinees may not be fully engaged when answering the items. Instead of engaging in solution behaviour, disengaged examinees might randomly guess or generate no response at all. When ignored, examinee disengagement poses a severe threat to the validity of results obtained from low‐stakes assessments. Statistical modelling approaches in educational measurement have been proposed that account for non‐response or for guessing, but do not consider both types of disengaged behaviour simultaneously. We bring together research on modelling examinee engagement and research on missing values and present a hierarchical latent response model for identifying and modelling the processes associated with examinee disengagement jointly with the processes associated with engaged responses. To that end, we employ a mixture model that identifies disengagement at the item‐by‐examinee level by assuming different data‐generating processes underlying item responses and omissions, respectively, as well as response times associated with engaged and disengaged behaviour. By modelling examinee engagement with a latent response framework, the model allows assessing how examinee engagement relates to ability and speed as well as to identify items that are likely to evoke disengaged test‐taking behaviour. An illustration of the model by means of an application to real data is presented

Exploratory Analysis in Learning Analytics

This article summarizes the methods, observations, challenges and implications for exploratory analysis drawn from two learning analytics research projects. The cases include an analysis of a games-based virtual performance assessment and an analysis of data from 52,000 students over a 5-year period at a large Australian university. The complex datasets were analyzed and iteratively modeled with a variety of computationally intensive methods to provide the most effective outcomes for learning assessment, performance management and learner tracking. The article presents the research contexts, the tools and methods used in the exploratory phases of analysis, the major findings and the implications for learning analytics research methods