Ion mass spectrometer

An ion mass spectrometer is described which detects and indicates the characteristics of ions received over a wide angle, and which indicates the mass to charge ratio, the energy, and the direction of each detected ion. The spectrometer includes a magnetic analyzer having a sector magnet that passes ions received over a wide angle, and an electrostatic analyzer positioned to receive ions passing through the magnetic analyzer. The electrostatic analyzer includes a two dimensional ion sensor at one wall of the analyzer chamber, that senses not only the lengthwise position of the detected ion to indicate its mass to charge ratio, but also detects the ion position along the width of the chamber to indicate the direction in which the ion was traveling

Detecting Weed Infestations in Soybean Using Remote Sensing.

Can weed distribution maps be developed from remote sensed reflectance data? When are the appropriate times to collect these data during the season? What wavebands can be used to distinguish weedy from weed- free areas? This research examined if and when reflectance could be used to distinguish between weed-free and weed-infested (mixed species) areas in soybean and to determine the most useful wavebands to separate crop, weed, and soil reflectance differences. Treatments in the two-year study included no vegetation (bare soil), weed-free soybean, and weed-infested soybean and, in one year, 80% corn residue cover. Reflectance was measured at several sampling times from May through September in 2001 and 2002 using a hand-held multispectral radiometer equipped with band-limited optical interference filters (460 - 1650 nm). Pixel resolution was 0.8-m. Reflectance in the visible spectral range (460 to 700 nm) generally was similar among treatments. In the near-infrared (NIR) range (\u3e700 to 1650 nm), differences among treatments were observed from soybean growth stage V-3 (about 4 weeks after planting) until mid-July to early August depending on crop vigor and canopy closure (76 cm row spacing in 2001 and 19 cm row spacing in 2002). Reflectance rankings in the NIR range when treatments could be differentiated were consistent between years and, from lowest to highest reflectance, were soil \u3c weed-free \u3c weed-infested areas. Increased reflectance from weed-infested areas was most likely due to increased biomass and canopy cover. Residue masked differences between weed-free and weed- infested areas during the early stages of growth due to high reflectance from the residue and reduced weed numbers in these areas. These results suggest that NIR spectral reflectance collected prior to canopy closure can be used to distinguish weed-infested from weed-free areas

Development of a Method for Evaluating the Yield Goal Approach

Yield goals have been used to determine N recommendations in South Dakota, North Dakota, and western Minnesota. However, some states, such as Wisconsin and Iowa have eliminated yield goals from N recommendations because of poor correlation between yield and economically optimum N rates. The objective of this study was to determine the feasibility of switching from a yield goal approach to a non-yield goal approach in South Dakota. Field experiments were conducted in Aurora, South Dakota between 2002 and 2003. Treatments were natural rainfall and natural rainfall + irrigation and four N rates (0, 60, 120, 180 kg N /ha). Plant samples were analyzed for 13C discrimination (Δ) and total N. Research results showed that; (i) adding N rates increased yield and Δ; (ii) applying supplemental irrigation increased yield and decreased Δ; (iii) yields were not influenced by an interaction between water and nitrogen; and (iv) δ15N values increased with irrigation and decreased with increasing N. These results suggest that nitrogen and water stress had independent impact on yield, and irrigation increased N mineralization. These findings partially support the hypothesis that fertilizer rates should be independent of yield goal. Research needs to be conducted to determine the long term impact of changing the recommendation approach on soil N levels

Best Management Practices for Corn Production in South Dakota: Soil Fertility

Corn requires sufficient amounts of at least 14 nutrients for optimal production (fig. 7.1). Soil fertility strategies should consider soil residual plant nutrients, cost of fertilizer relative to the value of corn, and management techniques that increase efficiency

Growth and Fecundity of Several Weed Species in Corn and Soybean

Do weeds that emerge later in the season justify additional control costs\u27? If crop yield is not reduced or few or no seeds arc added to the soil seed hank, then no control may he needed. Eight weed species were sown in corn (Zea mays L.) and soybean I Glycine max (L.) Mcrr.l (i) before crop emergence, (ii) at crop emergence, (iii) at V-1, and (iv) at V-2 stages of crop growth in 2002 and 2003. Weed seed was sown close to the crop row and thinned to 1.3 plants m 2• Weed growth and fecundity were influenced by species, time of planting, and year. Only barnyarclgrass (Echinochloa crus-galli L.), rcclroot pigwced (Amaranthus retniflexus L.), and vclvetlcaf (Abutilon theophrasti L.) survived to produce seed. Plants from the pre-emergence seeding had the largest canopy and produced the most seeds. Harnyardgrass had maximum canopy cover in early .July in corn and late .Inly in soybean hut only produced seed in corn. Rcclroot pigweecl and vclvctleaf had maximum canopy cover in late August or midSeptember, and some plants from most seeding elates survived and produced seed in both corn and soybean. However, plants that grew from seed sown at V-1 and V-2 crnp grnwth stages did not reduce yield or biomass of adjacent crop plants, had low fecundity, and may not warrant treatment. Control may be necessary, however, to prevent yield losses if weeds arc present at high densities or to prevent establishment of uncommon species

Breeding Season Survival and Reproduction in a High-Density Bobwhite Population: A case study

The demographic behavior of northern bobwhite (Colinus virginianus; hereafter, bobwhite) populations at high densities could provide important insights into why bobwhite populations fluctuate. Therefore, we documented breeding season demographics of bobwhites to understand how prebreeding density influenced reproductive effort and postbreeding density on an intensively managed property in Leon County, Florida, USA, 2002–2006. We estimated prebreeding bobwhite density each April using multi-observer strip-transects and postbreeding densities each November using covey call grid surveys. We radio-tagged 217 bobwhites in March and located bobwhites at least 5 days/week, 15 April–30 September to determine vital rates. Prebreeding density ranged from 1.5–8.6 birds/ha, peaking in 2002, declining through 2005, then increasing in 2006. Breeding season survival was 0.55, 0.17, 0.20, and 0.59, and nesting rate was 0.47, 0.67, 0.80 and 0.89, 2002–2005, respectively. Postbreeding density ranged from 5.2–13.6 birds/ha, also peaking in 2002 and declining through 2004 before increasing beginning in 2005 and 2006. High breeding season survival and nesting success (\u3e0.55) resulted in greater chick production during periods of population growth. Nesting rate was inversely related to prebreeding density. Declines in bobwhite nesting rate at high prebreeding densities appeared to regulate population growth near population peaks. Lower adult survival and nesting success appeared to cause population declines. We suggest density-dependent intraspecific competition limited population growth at high bobwhite densities by reducing nesting rate while predation of adults and nests explained population fluctuations

Factors Influencing Northern Bobwhite Hunting Success on Two South Georgia Plantations

Success of wild northern bobwhite (Colinus virginianus) management programs on private lands is most often measured by the rate of coveys pointed during the hunting season. Thus, managers of these properties are keenly interested in factors that influence hunting success. We examined how coveys pointed/hour, a measure of hunting success, was influenced by time of hunting season, time of day, weather parameters, and supplemental feeding on 2 intensively-managed plantations over 4 years. There were significant annual differences in the number of coveys pointed/hour among the 4 study years, but hunting success did not vary during the hunting season. Afternoon hunts had consistently higher success rates than morning hunts; however, the effect size was variable from year to year. The selected weather model indicated an interaction between 12-hr barometric pressure change and starting air pressure; hunting success increased with a rapid pressure increase that resulted in a high pressure value at the start of the hunt. A secondary weather model documented a negative relationship between starting air temperature and hunting success. The number of days since supplemental feed was spread had no significant effect on hunting success in 5 of 6 years for the 2 plantations over 3 years. Knowledge of how these variables influence hunting success should improve hunting and provide realistic expectations of hunt success for a given set of circumstances

Field Scale Variability of Nitrogen and δ15N in Soil and Plants

Understanding the factors that influence soil and plant nitrogen (N) spatial variability may improve our ability to develop management systems that maximize productivity and minimize environmental hazards. The objective of this study was to determine the field (65 ha) scale spatial variability of N and δ15N in soil and corn (Zea mays). Soil, grain, and stover samples were collected from grids that ranged in size from 30 by 30 m to 60 by 60 m. Plant samples, collected following physiological maturity in 1995, were analyzed for total N and δ15N. Soil samples, collected prior to planting in the spring of 1995 and 1996, were analyzed for inorganic‐N, total N, and δ15N. All parameters showed strong spatial relationships. In an undrained portion of the field containing somewhat poorly and poorly drained soils there was a net loss of 95 kg N ha‐1, while in an adjacent area that was tile drained there was a net gain of 98 kg N ha‐1. Denitrification and N mineralization most likely were responsible for losses and gains, respectively. Differences between the N balances of these areas (193 kg N ha‐1) provide a relative measure of the impact of tile drainage on plant N availability and greenhouse gas production in a wet year