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Sociotechnological Sustainability in Pasture Management: Labor Input and Optimization Potential of Smart Tools to Measure Herbage Mass and Quality. SUSTAINABILITY 2022. [DOI: 10.3390/su14127490] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Investing labor time in herbage measurements is important for precision pasture management. In this study, the labor input of three smart herbage measurement tools—multispectral imagery linked to an unmanned aerial vehicle (UAV), a semi-automated rising plate meter (RPM), and near-infrared reflectance spectroscopy (NIRS) of cut herbage samples—and of direct observation was modeled based on the REFA work element method. Three to five users were observed during work execution to identify best-practice workflows. Time measurements were conducted using video footage. The resulting standard times of work elements were used to model labor input for herbage measurements in different farm sizes (i.e., milking platforms of 6–100 ha) and subdivisions of a farm’s milking platform (i.e., 4–45 paddocks). Labor time requirement differed between the smart farming tools (0.7–5.9 h) depending on the farm size and milking platform scenario. The labor time requirement increased for all tools with an increase in farm size and was lowest for the RPM. For the UAV tool, it did not increase noticeably when the division of the milking platform changed. Nevertheless, the potential to save time was identified for the UAV and the NIRS. Therefore, the automation of certain steps in the workflows would contribute to sociotechnological sustainable pasture management.
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Migliaccio G, Pavone P. Primary sector in Italy: profitability dynamics and relationship with the international economic crisis. INTERNATIONAL JOURNAL OF PRODUCTIVITY AND PERFORMANCE MANAGEMENT 2021. [DOI: 10.1108/ijppm-05-2020-0229] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Purpose
This paper investigates the income dynamics of Italian primary sector, during and after the international economic crisis. It focuses on three research questions: what has been the evolution of the main profitability ratios of agricultural enterprises in recent years? After the crisis, have the surviving farms increased their profitability? Has the profitability been different also in relation to the geographic location?
Design/methodology/approach
Income dynamics of a sample of companies have been analyzed, obtaining the 10-year evolution of the average value of three income indices (return on equity [ROE], return on assets [ROA] and return on sales [ROS]). Statistical elaborations and the analysis of variance (ANOVA) method have been used.
Findings
The years of the international economic crisis are often characterized by higher incomes than the following ones. The descending trend involves all three national macroareas of Italy, although characterized by considerable socioeconomic differences.
Research limitations/implications
The study considers only the society that survived the crisis, so, presumably, the strongest. Moreover, other ratios should be considered in order to have a more complete view.
Practical implications
Public policymakers could use this study for a better intervention in support of agricultural and agro-industrial activities.
Social implications
The careful economic and financial analysis of the sector favors the relaunching strategies of the Italian primary sector in which many employees work.
Originality/value
The research contributes to the literature by providing a quantitative analysis of the dynamics of the sector, through the comparative information that may be derived from financial statements.
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Abstract
Climate-smart agriculture is an approach for developing agricultural strategies to modernize agricultural systems using digital techniques, aiming for sustainable agriculture and ensuring food security under climate change. This article provides a systematic literature review of smart agriculture technologies towards climate-smart agriculture in Cyprus, including robotics, Internet of Things, and remote sensing. The paper starts with a review of climate-smart agriculture, presenting its importance in terms of optimizing agricultural production processes in order to address the interlinked challenges of food security and climate change. An extensive literature review of works published in the areas of robotics, Internet of Things, and remote sensing is undertaken, with particular attention paid to works carried out in relation to agriculture in Cyprus. The paper analyzes aspects of the climate-smart agriculture research situation in Cypriot agriculture, identifies gaps, and concludes with new directions.
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Bechar A, Vitner G. Effective productivity management of mixed flower farms. INTERNATIONAL JOURNAL OF PRODUCTIVITY AND PERFORMANCE MANAGEMENT 2019. [DOI: 10.1108/ijppm-03-2018-0125] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Purpose
The purpose of this paper is to investigate the issue of low yields in the packinghouses of green ornamentals and cut flowers due to the high rate of crops waste. Waste may be caused by pests, diseases and extreme weather or environmental conditions that are not under the farmer’s control. Other causes may relate to work processes as follows: irrigation, spraying, harvesting, handling, transportation, sorting, bundling and packaging.
Design/methodology/approach
The farm under study is a private owned business managed by the owner’s family members with growing area of 22 ha and eight daily workers. The farm produces about 2.5m units (flower stems) per year. The farm represents a typical flower farm in Israel. A costing model and decision rules were developed to identify the critical waste rate that will consider being economic to ship to the market. The model takes into account the production process, the production yield, the operational costs and sales price and calculates the breakeven point. A simulation model was developed to verify the relationships between waste rate to the total process time per stem and flow time.
Findings
Results show that the critical waste rate for Ruscus, Antirrhinum, Aralia and Aspidistra crops is 16, 74, 22 and 39 percent, respectively. The total process time per harvested stem decreases as the waste rate increases.
Originality/value
A working model was developed to determine the waste threshold rate and support the farmer in day-to-day economic decisions regarding shipment to the market and effective management of his workers.
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