Performance of machinery in potato production in one growing season

Statistics on the machinery performance are essential for farm managers to make better decisions. In this paper, the performance of all machineries in five sequential operations, namely bed forming, stone separation, planting, spraying and harvesting in the potato production system, were investigated during one growing season. In order to analyse and decompose the recorded GPS data into various time and distance elements for estimation of the machinery performance, an automatic GPS analysis tool was developed. The field efficiency and field capacity were estimated for each operation. Specifically, the measured average field efficiency was 71.3% for bed forming, 68.5% for stone separation, 40.3% for planting, 69.7% for spraying, and 67.4% for harvesting. The measured average field capacities were 1.46 ha/h, 0.53 ha/h, 0.47 ha/h, 10.21 ha/h, 0.51 ha/h, for the bed forming, stone separation, planting, spraying, and harvesting operations, respectively. These results deviate from the corresponding estimations calculated based on norm data from the American Society of Agricultural and Biological Engineers (ASABE). The deviations indicate that norms provided by ASABE cannot be used directly for the prediction of performance of the machinery used in this work. Moreover, the measured data of bed forming and stone separation could be used as supplementary data for the ASABE which does not provide performance norms for these two operations. The gained results can help farm managers to make better management and operational decisions that result in potential improvement in productivity and profitability as well as in potential environmental benefits

Agricultural machinery selection and scheduling of farm operations

The procedure of calculating annual machinery ownership costs from the discounted cash flows of the mortgaged capital cost, the repair and insurance charges and the resale income is extended to include the effect of loan rate and loan period on interest charges, the effect of capital allowances taking account of the actual balancing charges at the end of the period of ownership, and the effect of tax relief on the interest charges, repair costs and insurance premiums. The concept of marginal holding cost is applied to determine the optimum ownership period.The selection of tractor- plough combinations is based on the prediction of soil characteristics such as moisture content, strength, and workability, all of which influencing the assessment of plough draught and tractor power. A number of filters are used to select the appropriate and realistic tractor /implement combinations with different sizes of fully mounted plough depending on the draught, and the speed of each selected gear of the tractor. For each acceptable combina- tion of tractor and fully mounted plough determined, the costing routine is used to calculate the annual costs.The branch and bound algorithm is suitable for mixed integer solutions to the farm machinery selection problem. Machinery sets are selected simultaneously with the chosen cropping pattern on a given land area. Machinery sets are matched correctly to the tractor sizes. Four sizes of tractor are available (45 kW, 61 kW, 74 kW and 94 kW,. Field operations take place in discrete time periods during which available work days are predicted from soil type and weather records for the specific site. Cereal and root crops are distinguished by optimum sowing and harvesting date. Discrete time periods are defined in relation to these optimal dates and give rise to overlapping operations for different crops. The calculation of probability levels for available work days when operations are subject to different criteria is discussed. A single arbitrary value of 75% probability for available work days is adopted in the linear programming model for the main part of the study.Two stage processes are used to simulate available work days in each time period. The patterns generated converge on the relative frequency pattern laid down by the generating process. The range of experience is wider than that contained in the short series of 24 years historical data. The simulation model generates results suitable for stochastic dominance ranking.In a simulation experiment on a 250 ha arable farm cropping cereals and potatoes, alternative solutions are obtained by integer linear programming, the solutions being ranked according to gross revenue. Annual costs of operating farm machinery are derived from a separate costing algorithm based on the annual hours of use which are determined by the size of the task and not by the sequence of work days. After deducting the annual costs of machinery operation, the cumulative net revenue curves cross and second order stochastic dominance ranking is used to identify the optimum (maximum profit) solution.The current study demonstrates the viability of the analytical procedures but further work is now required to reduce the computing time involved for the complete machinery selection procedure. Meanwhile, a commercial software package is prepared on the calculation of annual machinery ownership costs

B843: The Ecology, Economics, and Management of Potato Cropping Systems: A Report of the First Four Years of the Maine Potato Ecosystem Project

The bulletin reports on the first four years of the Maine Potato Ecosystem Project, a long-term, multidisciplinary study of alternative crop management strategies. The study site is a 15-acre tract on the northern boundary of the University of Maine\u27s Aroostook Farm in Presque Isle, Maine, divided into 96 main plots that are grouped into four blocks. Each block is an area where soil survey data show similar soil characteristics. Thus, given the same production inputs, the crop output is expected to be the same on each plot within a block. Within each block there are 24 plots to which the different treatments have been randomly assigned. A treatment is a particular combination of the following factors: (1) pest management—conventiorial, reduced input, or biological; (2) potato variety—Atlantic or Superior; and (3) soil management—amended or unamended.https://digitalcommons.library.umaine.edu/aes_bulletin/1025/thumbnail.jp

Simulation of site-specific irrigation control strategies with sparse input data

Crop and irrigation water use efficiencies may be improved by managing irrigation application timing and volumes using physical and agronomic principles. However, the crop water requirement may be spatially variable due to different soil properties and genetic variations in the crop across the field. Adaptive control strategies can be used to locally control water applications in response to in-field temporal and spatial variability with the aim of maximising both crop development and water use efficiency. A simulation framework ‘VARIwise’ has been created to aid the development, evaluation and management of spatially and temporally varied adaptive irrigation control strategies (McCarthy et al., 2010). VARIwise enables alternative control strategies to be simulated with different crop and environmental conditions and at a range of spatial resolutions. An iterative learning controller and model predictive controller have been implemented in VARIwise to improve the irrigation of cotton. The iterative learning control strategy involves using the soil moisture response to the previous irrigation volume to adjust the applied irrigation volume applied at the next irrigation event. For field implementation this controller has low data requirements as only soil moisture data is required after each irrigation event. In contrast, a model predictive controller has high data requirements as measured soil and plant data are required at a high spatial resolution in a field implementation. Model predictive control involves using a calibrated model to determine the irrigation application and/or timing which results in the highest predicted yield or water use efficiency. The implementation of these strategies is described and a case study is presented to demonstrate the operation of the strategies with various levels of data availability. It is concluded that in situations of sparse data, the iterative learning controller performs significantly better than a model predictive controller

Air pollution and livestock production

The air in a livestock farming environment contains high concentrations of dust particles and gaseous pollutants. The total inhalable dust can enter the nose and mouth during normal breathing and the thoracic dust can reach into the lungs. However, it is the respirable dust particles that can penetrate further into the gas-exchange region, making it the most hazardous dust component. Prolonged exposure to high concentrations of dust particles can lead to respiratory health issues for both livestock and farming staff. Ammonia, an example of a gaseous pollutant, is derived from the decomposition of nitrous compounds. Increased exposure to ammonia may also have an effect on the health of humans and livestock. There are a number of technologies available to ensure exposure to these pollutants is minimised. Through proactive means, (the optimal design and management of livestock buildings) air quality can be improved to reduce the likelihood of risks associated with sub-optimal air quality. Once air problems have taken hold, other reduction methods need to be applied utilising a more reactive approach. A key requirement for the control of concentration and exposure of airborne pollutants to an acceptable level is to be able to conduct real-time measurements of these pollutants. This paper provides a review of airborne pollution including methods to both measure and control the concentration of pollutants in livestock buildings

Labour‐saving technologies in smallholder agriculture: An economy‐wide model with field operations

Labour-saving technologies are relevant for agricultural development. Yet, as this study shows, they are poorly integrated into agricultural production functions of economy-wide models. We report a computable general equilibrium (CGE) model, which explicitly incorporating field operations (e.g. land preparation, weeding or harvesting) in the context of smallholder agriculture. The field operations approach allows to model technological trade-offs in organic and conventional production systems at various stages of the agricultural production process. Simulating a structural change scenario, we compare the performance of the field operations approach with published benchmark production structures by assessing how they replicate empirically observed changes in land and agrochemical use. This benchmark analysis shows that incorporating field operations replicates the observed empirical changes most accurately and allows for more realistic modelling of labour-saving technologies. We use the field operations model to investigate three policy options to mitigate labour shortages in the agricultural sector of Bhutan. Permitting the employment of Indian workers in agriculture has the highest short-term potential in this respect. We find that subsidising agricultural machinery hiring services and removing import tariffs on agrochemical inputs are found to be less effective. Further options for model developments, such as combining field operations and labour market seasonality, are highlighted.Stiftung fiat panis, Ulm, Germany http://dx.doi.org/10.13039/501100011087Humboldt‐Universität zu Berlin http://dx.doi.org/10.13039/501100006211Peer Reviewe

An investigation of the application of programming techniques to farm management problems, with special reference to beef cattle feeding in the Lothians of Scotland and in Alberta

The Lothians of Scotland are generally farmed intensive- ly, with arable farming predominating in the more easterly regions. Potatoes form an integral part of the cropping pat- tern with sugar beets and turnips somewhat less widely grown. Wheat and barley are the principal cereal crops. Grass is in- cluded in the rotation on practically every farm. The returns from cropping are usually complemented by returns from the production of beef cattle. Farmers of the area usually have one or more beef cattle enterprises, frequently with emphasis on fattening cattle for slaughter.The farming pattern, with emphasis on potato production, requires a substantial labour force, measured on an "acres per man" basis, as compared to less intensively farmed areas such as the unirrigated portions of Alberta. The availability of this labour force during non -critical seasons might be expect- ed to result in a level of mechanization differing from that developed for less intensively farmed areas. For field work, a larger number of smaller capacity machines might be expected, and for cattle feeding a lower level of mechanization might be expected. Despite these expectations there is a keen interest in highly mechanized processes. This is particularly evident in processes associated with cattle production.This intensive, well integrated pattern of agriculture offers a challenging application for linear programming as a management aid. In addition, the interaction between cropping practise, manpower availability, and level of mechanization, particularly with respect to beef cattle feeding, offers an excellent medium for the extension of linear programming into the fixed -cost sector of farm business.Tabulated, the objectives of the research leading to the preparation of this thesis were to:1) Investigate the application of linear programming as an aid to farm planning in the Lothians.2) Complementary to this objective, to assess the availability and suitability of Scottish agri- culture research data for the preparation of linear programmes.3) The development of extensions to linear programming to permit the analysis of any mechanized activity in full economic association with other farm activities.4) An investigation of the use of linear programming, with extensions, as a method for determining the optimum levels of mechanization for beef cattle feeding

Yield trends and yield gap analysis of major crops in the world

This study aims to quantify the gap between current and potential yields of major crops in the world, and the production constraints that contribute to this yield gap. Using an expert-based evaluation of yield gaps and the literature, global and regional yields and yield trends of major crops are quantified, yield gaps evaluated by crop experts, current yield progress by breeding estimated, and different yield projections compared. Results show decreasing yield growth for wheat and rice, but still high growth rates for maize. The yield gap analysis provides quantitative estimates of the production constraints for a number of crops and regions and reveals the difficulty to measure and compare yield potentials and actual yields consistently under a range of environmental conditions, and it shows the difficulty to disentangle interacting production constraints. FAO yield growth projections are generally lower than what possibly could be gained by closing current yield gaps

Agricultural Structures and Mechanization

In our globalized world, the need to produce quality and safe food has increased exponentially in recent decades to meet the growing demands of the world population. This expectation is being met by acting at multiple levels, but mainly through the introduction of new technologies in the agricultural and agri-food sectors. In this context, agricultural, livestock, agro-industrial buildings, and agrarian infrastructure are being built on the basis of a sophisticated design that integrates environmental, landscape, and occupational safety, new construction materials, new facilities, and mechanization with state-of-the-art automatic systems, using calculation models and computer programs. It is necessary to promote research and dissemination of results in the field of mechanization and agricultural structures, specifically with regard to farm building and rural landscape, land and water use and environment, power and machinery, information systems and precision farming, processing and post-harvest technology and logistics, energy and non-food production technology, systems engineering and management, and fruit and vegetable cultivation systems. This Special Issue focuses on the role that mechanization and agricultural structures play in the production of high-quality food and continuously over time. For this reason, it publishes highly interdisciplinary quality studies from disparate research fields including agriculture, engineering design, calculation and modeling, landscaping, environmentalism, and even ergonomics and occupational risk prevention