Why does low intensity, long-day lighting promote growth in Petunia, Impatiens, and tomato?

Numerous reports demonstrate that low intensity, long-day (LD) lighting treatments can promote growth. However, there are conflicting suggestions as to the mechanisms involved. This study examines the responses of Petunia, Impatiens, and tomato to LD lighting treatments and concludes that no single mechanism can explain the growth promotion observed in each case. Petunia showed the most dramatic response to photoperiod; up to a doubling in dry weight (DW) as a result of increasing daylength from 8 h d–1 to 16 h d–1.This could be explained by an increase in specific leaf area (SLA) comparable to that seen with shading. At low photosynthetic photon flux densities (PPFD), the increased leaf area more than compensated for any loss in photosynthetic capacity per unit leaf area. In Petunia, the response may, in part, have also been due to changes in growth habit. Impatiens and tomato showed less dramatic increases in DW as a result of LD lighting, but no consistent effects on SLA or growth habit were observed. In tomato, increased growth was accompanied by increased chlorophyll content, but this had no significant effect on photosynthesis. In both species, increased growth may have been due to a direct effect of LD lighting on photosynthesis. This is contrary to the generally held view that light of approx. 3 – 4 μmol m–2 s–1 is unlikely to have any significant impact on net photosynthesis. Nevertheless, we show that the relationship between PPFD and net photosynthesis is non-linear at low light levels, and therefore low intensity LD lighting can offset respiration very efficiently. Furthermore, a small increase in photosynthesis will have a greater impact when ambient light levels are low

The effects of day and night temperature on Chrysanthemum morifolium: investigating the safe limits for temperature integration

The impact of day and night temperatures on pot chrysanthemum (cultivars ‘Covington’ and ‘Irvine’) was assessed by exposing cuttings, stuck in weeks 39, 44, and 49, to different temperature regimes in short-days. Glasshouse heating setpoints of 12°, 15°, 18°, and 21°C, were used during the day, with venting at 2°C above these set-points. Night temperatures were then automatically manipulated to ensure that all of the treatments achieved similar mean diurnal temperatures. Plants were grown according to commercial practice and the experiment was repeated over 2 years. Increasing the day temperature from approx. 19°C to 21°C, and compensating by reducing the night temperature, did not have a significant impact on flowering time, although plant height was increased.This suggests that a temperature integration strategy which involves higher vent temperatures, and exploiting solar gain to give higher than normal day temperatures, should have minimal impact on crop scheduling. However, lowering the day-time temperature to approx. 16°C, and compensating with a warmer night, delayed flowering by up to 2 weeks. Therefore, a strategy whereby, in Winter, more heat is added at night under a thermally-efficient blackout screen may result in flowering delays.Transfers between the temperature regimes showed that the flowering delays were proportional to the amount of time spent in a low day-time temperature regime. Plants flowered at the same time, irrespective of whether they were transferred on a 1-, 2-, or 4-week cycle

Systematic Uncertainties In Constraining Dark Matter Annihilation From The Cosmic Microwave Background

Anisotropies of the cosmic microwave background (CMB) have proven to be a very powerful tool to constrain dark matter annihilation at the epoch of recombination. However, CMB constraints are currently derived using a number of reasonable but yet un-tested assumptions that could potentially lead to a misestimation of the true bounds. In this paper we examine the potential impact of these systematic effects. In particular, we separately study the propagation of the secondary particles produced by annihilation in two energy regimes; first following the shower from the initial particle energy to the keV scale, and then tracking the resulting secondary particles from this scale to the absorption of their energy as heat, ionization, or excitation of the medium. We improve both the high and low energy parts of the calculation, in particular finding that our more accurate treatment of losses to sub-10.2 eV photons produced by scattering of high-energy electrons weakens the constraints on particular DM annihilation models by up to a factor of two. On the other hand, we find that the uncertainties we examine for the low energy propagation do not significantly affect the results for current and upcoming CMB data. We include the evaluation of the precise amount of excitation energy, in the form of Lyman-alpha photons, produced by the propagation of the shower, and examine the effects of varying the Helium fraction and Helium ionization fraction. In the recent literature, simple approximations for the fraction of energy absorbed in different channels have often been used to derive CMB constraints: we assess the impact of using accurate versus approximate energy fractions. Finally we check that the choice of recombination code (between RECFAST v1.5 and COSMOREC), to calculate the evolution of the free electron fraction in the presence of dark matter annihilation, introduces negligible differences.Comment: 29 pages, 21 figure

The effects of long-day lighting and removal of young leaves on tomato yield

While low intensity long-day (LD) lighting has been shown to enhance the growth of young plants under low light levels, its effect on the yield of a long-season glasshouse tomato crop has not been previously examined. LD were provided by the use of tungsten lamps (2.8 μmol m-2 s-1 at approx. 0.5 m from the ground) between 04.00 h to sunrise and from sunset until 20.00 h (GMT). LD lighting increased leaf chlorophyll contents, and the numbers of flowers and fruits set per truss when the plants were young. However, this treatment did not affect the total yield of tomatoes. Different leaf removal treatments were applied within each glasshouse compartment. A previous experiment had shown that reducing the leaf area index (LAI) from 5.2 to 2.6, by removing old leaves, did not affect yield. It was also thought that removal of young leaves reduced the total vegetative sink-strength and favoured assimilate partitioning into the fruit. Therefore, removal of young leaves could increase fruit yield. In the present experiments, one-third of the leaves were removed in March (those immediately below each truss) and, subsequently, every third leaf was removed at an early stage of its development. This reduced the LAI from 4.1 to 2.9 and resulted in a loss of yield from 3 – 4 weeks after leaf removal until the end of the experiment, at which point there was an 8% loss of cumulative yield due to a reduction in the average number of fruits set per truss and in mean fruit weight. We postulate that the light which would have been intercepted by young photosynthetically-efficient leaves at the top of the canopy was intercepted instead by older leaves which were less efficient, reducing overall net canopy photosynthesis

Status report on MicroSat data telemtery

The intent of this project was to test and evaluate a new data collection concept; that of utilizing a "store and forward" message system in a low earth orbiting satellite, and to determine its suitabilty for oceanographic data telemetry. This new generation of satellites, dubbed "MicroSats" because of their small size (a 9 in. cube), was developed by the Amateur Radio Satellite Corporation (AMSAT) to complement the existing HF and VHG terrestral Packet data switching networks.Funding was provided by the Office of Naval Research under Contract No. N00014-90-0013

A note on the application of wazewski’s topological method to an integro: differential equation of volterra type

The purpose of this note is to generalize the Wazewski’s Topological Method 11, originally stated for ordinary differential equations, to the integro – differential equation of Volterra type (1), under suitable conditions on the functions involved.Fil: Napoles Valdes, Juan Eduardo. Universidad Nacional del Nordeste. Facultad de Ciencias Exactas y Naturales y Agrimensura. Departamento de Matemática; ArgentinaFil: Velázquez, José R.. Universidad Nacional del Nordeste; ArgentinaFil: Lugo, Luciano Miguel. Universidad Nacional del Nordeste. Facultad de Ciencias Exactas y Naturales y Agrimensura. Departamento de Matemática; ArgentinaFil: Guzmán, Paulo Matias. Universidad Nacional del Nordeste. Facultad de Ciencias Exactas y Naturales y Agrimensura. Departamento de Matemática; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

Using Machine Learning to Predict Swine Movements within a Regional Program to Improve Control of Infectious Diseases in the US.

Between-farm animal movement is one of the most important factors influencing the spread of infectious diseases in food animals, including in the US swine industry. Understanding the structural network of contacts in a food animal industry is prerequisite to planning for efficient production strategies and for effective disease control measures. Unfortunately, data regarding between-farm animal movements in the US are not systematically collected and thus, such information is often unavailable. In this paper, we develop a procedure to replicate the structure of a network, making use of partial data available, and subsequently use the model developed to predict animal movements among sites in 34 Minnesota counties. First, we summarized two networks of swine producing facilities in Minnesota, then we used a machine learning technique referred to as random forest, an ensemble of independent classification trees, to estimate the probability of pig movements between farms and/or markets sites located in two counties in Minnesota. The model was calibrated and tested by comparing predicted data and observed data in those two counties for which data were available. Finally, the model was used to predict animal movements in sites located across 34 Minnesota counties. Variables that were important in predicting pig movements included between-site distance, ownership, and production type of the sending and receiving farms and/or markets. Using a weighted-kernel approach to describe spatial variation in the centrality measures of the predicted network, we showed that the south-central region of the study area exhibited high aggregation of predicted pig movements. Our results show an overlap with the distribution of outbreaks of porcine reproductive and respiratory syndrome, which is believed to be transmitted, at least in part, though animal movements. While the correspondence of movements and disease is not a causal test, it suggests that the predicted network may approximate actual movements. Accordingly, the predictions provided here might help to design and implement control strategies in the region. Additionally, the methodology here may be used to estimate contact networks for other livestock systems when only incomplete information regarding animal movements is available

The genetic contribution to severe post-traumatic osteoarthritis

Objective: to compare the combined role of genetic variants loci associated with risk of knee or hip osteoarthritis (OA) in post-traumatic (PT) and non-traumatic (NT) cases of clinically severe OA leading to total joint replacement. Methods: A total of 1590 controls, 2168 total knee replacement (TKR) cases (33.2% PT) and 1567 total hip replacement (THR) cases (8.7% PT) from 2 UK cohorts were genotyped for 12 variants previously reported to be reproducibly associated with risk of knee or hip OA. A genetic risk score was generated and the association with PT and NT TKR and THR was assessed adjusting for covariates. Results: For THR, each additional genetic risk variant conferred lower risk among PT cases (OR=1.07, 95% CI 0.96 to 1.19; p=0.24) than NT cases (OR 1.11, 95% CI 1.06 to 1.17; p=1.55×10−5). In contrast, for TKR, each risk variant conferred slightly higher risk among PT cases (OR 1.12, 95% CI 1.07 to 1.19; p=1.82×10−5) than among NT cases (OR 1.08, 95% CI 1.03 to 1.1; p=0.00063). Conclusions: Based on the variants reported to date PT TKR cases have at least as high a genetic contribution as NT cases