Effect of ploughing depth, tractor forward speed, and plough types on the fuel consumption and tractor performance

Cost of fuel has a significant impact on the input costs of agricultural production, especially during primary tillage. It is affected by several parameters including tractor forward speed, depths of ploughing, and plough types. The experiment was performed in a Soil Hall at Harper Adams University, United Kingdom, in April 2015. A Massey Ferguson 8480 4WD tractor was used for investigating objectives of this study. The experiment was performed in a sandy loam soil texture at 11.73% soil moisture content and 1.35 (g/cm3) dry bulk density to study the amount of fuel consumption (l/ha) and the performance of tractor with effect of moldboard and disc ploughs as ploughs type, 15 and 20 cm as ploughing depth and 5 and 7 km/h as tractor forward speeds. The results showed that fuel consumption with a disc plough 5% was higher compared to the moldboard. Fuel consumption decreased approximately 8% when tractor at 7 km/h. Fuel consumption significantly decreased about 34% when ploughing depth increased from 15 to 20 cm. The power requirement to operate moldboard plough was higher by about 14% than a disc. The power requirement at speeds of 7 km/h was higher compared to the speeds of 5 km/h by about 27%. When the depth of ploughing increased from 15 to 20 cm, the power requirement increased by about 1.5%

Fermi pockets and correlation effects in underdoped YBa2Cu3O6.5

The detection of quantum oscillations in the electrical resistivity of YBa2Cu3O6.5 provides direct evidence for the existence of Fermi surface pockets in an underdoped cuprate. We present a theoretical study of the electronic structure of YBa2Cu3O7-d (YBCO) aiming at establishing the nature of these Fermi pockets, i.e. CuO2 plane versus CuO chain or BaO. We argue that electron correlation effects, such as orbital-dependent band distortions and highly anisotropic self-energy corrections, must be taken into account in order to properly interpret the quantum oscillation experiments.Comment: A high-resolution version can be found at http://www.physics.ubc.ca/~quantmat/ARPES/PUBLICATIONS/Articles/YBCO_OrthoII_LDA.pd

Crystallographic and superconducting properties of the fully-gapped noncentrosymmetric 5d-electron superconductors CaMSi3 (M=Ir, Pt)

We report crystallographic, specific heat, transport, and magnetic properties of the recently discovered noncentrosymmetric 5d-electron superconductors CaIrSi3 (Tc = 3.6 K) and CaPtSi3 (Tc = 2.3 K). The specific heat suggests that these superconductors are fully gapped. The upper critical fields are less than 1 T, consistent with limitation by conventional orbital depairing. High, non-Pauli-limited {\mu}0 Hc2 values, often taken as a key signature of novel noncentrosymmetric physics, are not observed in these materials because the high carrier masses required to suppress orbital depairing and reveal the violated Pauli limit are not present.Comment: 8 pages, 8 figure

Dynamic modelling of lettuce transpiration for water status monitoring

Real-time information on the plant water status is an important prerequisite for the precision irrigation management of crops. The plant transpiration has been shown to provide a good indication of its water status. In this paper, a novel plant water status monitoring framework based on the transpiration dynamics of greenhouse grown lettuce plants is presented. Experimental results indicated that lettuce plants experiencing adequate water supply transpired at a higher rate compared to plants experiencing a shortage in water supply. A data-driven model for predicting the transpiration dynamics of the plants was developed using a system identification approach. Results indicated that a second order discrete-time transfer function model with incoming radiation, vapour pressure deficit, and leaf area index as inputs sufficiently explained the dynamics with an average coefficient of determination of . The parameters of the model were updated online and then applied in predicting the transpiration dynamics of the plants in real-time. The model predicted dynamics closely matched the measured values when the plants were in a predefined water status state. The reverse was the case when there was a significant change in the water status state. The information contained in the model residuals (measured transpiration – model predicted transpiration) was then exploited as a means of inferring the plant water status. This framework provides a simple and intuitive means of monitoring the plant water status in real-time while achieving a sensitivity similar to that of stomatal conductance measurements. It can be applied in regulating the water deficit of greenhouse grown crops, with specific advantages over other available techniques

Fermi Surface and Quasiparticle Excitations of overdoped Tl2Ba2CuO6+d by ARPES

The electronic structure of the high-T_c superconductor Tl2Ba2CuO6+d is studied by ARPES. For a very overdoped Tc=30K sample, the Fermi surface consists of a single large hole pocket centered at (pi,pi) and is approaching a topological transition. Although a superconducting gap with d_x^2-y^2 symmetry is tentatively identified, the quasiparticle evolution with momentum and binding energy exhibits a marked departure from the behavior observed in under and optimally doped cuprates. The relevance of these findings to scattering, many-body, and quantum-critical phenomena is discussed.Comment: Revised manuscript, in press on PRL. A high-resolution version can be found at http://www.physics.ubc.ca/~quantmat/ARPES/PUBLICATIONS/Articles/Tl2201_LE.pdf and related material at http://www.physics.ubc.ca/~quantmat/ARPES/PUBLICATIONS/articles.htm

A cost-effective imaging system for monitoring poultry behaviour in small-scale Kenyan poultry sheds

The objective of this paper was to develop a low-cost prototype poultry behaviour imaging and analysis system for monitoring intensively-reared flocks suitable for small-scale Kenyan poultry sheds. An image processing and analysis programme was developed using Python programming language and the OpenCV image processing package. This was tested on overhead images of Ross 308 birds collected over a number of days using a Raspberry Pi V2 camera. A second experiment using toy-chicks was conducted with an angled camera (Wansview W3). Linear transformation (LT) and background subtraction (BS) methods were applied and compared for effectiveness at detecting yellow and brown toy-chicks on woodchip bedding. Perspective transformation (PT) was applied and evaluated for its ability to transform the angled images into two-dimensional views. In the first experiment, where white birds were detected against a dark background, LT object detection successfully detected 99.8% of birds in the sampled images. However, in the second experiment, the LT method was just 56.5% effective at detecting the yellow toy-chicks against the light-coloured background. In contrast, the BS method was more effective, detecting 91.5% of the yellow toy-chicks. The results showed that BS detection success was worse for yellow toy-chicks in the far section, detecting 83% as opposed to 100% of those in the near-section. Edge processing of the image processing algorithm was tested on a Raspberry Pi 3 series B+ computer. This prototype provides a solid foundation for further development and testing of low-cost, automated poultry monitoring systems capable of reporting on thermal comfort inferred from cluster index

Advanced monitoring and management systems for improving sustainability in precision irrigation

Globally, the irrigation of crops is the largest consumptive user of fresh water. Water scarcity is increasing worldwide, resulting in tighter regulation of its use for agriculture. This necessitates the development of irrigation practices that are more efficient in the use of water but do not compromise crop quality and yield. Precision irrigation already achieves this goal, in part. The goal of precision irrigation is to accurately supply the crop water need in a timely manner and as spatially uniformly as possible. However, to maximize the benefits of precision irrigation, additional technologies need to be enabled and incorporated into agriculture. This paper discusses how incorporating adaptive decision support systems into precision irrigation management will enable significant advances in increasing the efficiency of current irrigation approaches. From the literature review, it is found that precision irrigation can be applied in achieving the environmental goals related to sustainability. The demonstrated economic benefits of precision irrigation in field-scale crop production is however minimal. It is argued that a proper combination of soil, plant and weather sensors providing real-time data to an adaptive decision support system provides an innovative platform for improving sustainability in irrigated agriculture. The review also shows that adaptive decision support systems based on model predictive control are able to adequately account for the time-varying nature of the soil–plant–atmosphere system while considering operational limitations and agronomic objectives in arriving at optimal irrigation decisions. It is concluded that significant improvements in crop yield and water savings can be achieved by incorporating model predictive control into precision irrigation decision support tools. Further improvements in water savings can also be realized by including deficit irrigation as part of the overall irrigation management strategy. Nevertheless, future research is needed for identifying crop response to regulated water deficits, developing improved soil moisture and plant sensors, and developing self-learning crop simulation frameworks that can be applied to evaluate adaptive decision support strategies related to irrigation