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Whole farm analysis of automatic section control for agricultural machinery
Abstract
Automatic section control was analyzed in a whole farm decision-making framework when implemented on an agricultural sprayer and/or planter. In addition, various field types and navigational scenarios were examined to determine their impact on profitability. It was determined that automatic section control increased net returns under all scenarios; up to $36/ha. This investigation highlighted the importance of considering field size in addition to field shape as well as initial navigational scenarios when determining the profitability of automatic section control.
... The largest benefit associated with automatic section control is the reduction in overlapped areas, especially prevalent on irregularly shaped fields. As a result, this technology can potentially increase profits due to reduced input costs [31]. Farms with larger acreage rather than small-acre farms have more readily adopted precision agriculture technologies. ...
... Some precision agriculture practices have also been reported in some parts of Kentucky. In Central Kentucky, automatic section control technology was used for deep tillage, spraying, and planting [31]. Shockley et al. [31] find that irregularly shaped fields are common in Kentucky; therefore, automatic section control could be more profitable for Kentucky producers than for those with square fields like those found in the Midwest. ...
... In Central Kentucky, automatic section control technology was used for deep tillage, spraying, and planting [31]. Shockley et al. [31] find that irregularly shaped fields are common in Kentucky; therefore, automatic section control could be more profitable for Kentucky producers than for those with square fields like those found in the Midwest. Automatic section control increased net returns under all scenarios, up to $36/ha. ...
... These technologies are believed to have numerous benefits in production agriculture, with a potentially large economic impact. They are believed to be able to improve the efficiency of farm operations by lowering input costs and have been shown in prior studies to have the potential to increase net returns (Schimmelpfenning, 2016;Smith et al., 2013;Shockley et al., 2012;Shockley et al., 2011;Mooney et al. 2009;Dillon et al., 2007;Batte and Ehsani, 2006;Griffin et al. 2005). In addition to lowering input costs through improved accuracy of application, it is also believed that precision agriculture technologies will allow farmers to increase production due to the vast amount of information available to them; allowing them to produce more output with less input (Sustainable America, 2012). ...
... When approaching an already-covered area from a different angle, such as in a point-row, the ASC system begins shutting off the respective planter rows/sprayer nozzles as they reach the previously-covered portion of the field, resulting in more complete coverage with reduced overlap. ASC is most effective when used on fields with irregular shape or infield obstructions, as there is more opportunity for double-planting or skips when using traditional planting methods, as will be discussed further in Chapter 3 (Smith et al., 2013;Shockley et al., 2012). ASC on planters and sprayers is a technology that is meant to improve the efficiency of operations and thus lowers input cost and reduces the amount of time spent in the field. ...
... Many of these studies use hypothetical farms and/or simulations in order to determine the potential returns from precision agriculture. Such studies have shown potential for consistent increases in net returns under varying circumstances from multiple specific technologies, including GPS guidance, automated section control, and variable rate application of nutrients (Smith et al., 2013;Shockley et al., 2012;Shockley et al., 2011;Mooney et al., 2009;Dillon et al., 2007;Batte and Ehsani, 2006;Griffin et al., 2005). Plus, a recent study by the USDA's Economic Research Service found positive impacts on profitability measures associated with the use of soil and yield mapping, GPS guidance systems, and variable-rate application of inputs (Schimmelpfenning, 2016). ...
An ever-increasing global demand for food, coupled with increasingly volatile commodity prices have charged producers with the task of becoming more efficient. As such, technologies aimed at producing more with less are continually being developed and marketed to producers. However, whether or not these expensive new technologies have resulted in improved profitability is still unknown, as the vast majority of studies showing their impact on profitability have been performed using hypothetical farms and simulations. These studies have shown the potential for increases in profitability from use, but their impact in the real world is still uncertain. This project uses various fixed-effect panel data models to examine the realized economic impact of using precision agriculture technologies amongst a sample of producers across Nebraska using financial data from 1995-2014. Results of the study show the existence of a strong, positive relationship between number of technologies used and net farm income, indicating that precision agriculture use is associated with higher profitability. However, whether use is driving profitability or profitability is driving use remains somewhat unclear. Pre-and-post analysis among users of the technologies suggest profitability has in fact increased from use, but the result is not statistically significant. This may be a consequence of mixed results among users, with many factors influencing the level of benefit achievable from use. Nonetheless, an obvious learning effect exists for users, with profitability increasing more as experience with the technologies increases. This would be expected due to the need to produce data regarding within-field variability on which to capitalize, along with the investment in learning the ideal use of these relatively complicated technologies. Overall, it is obvious that further research regarding the impact of these technologies is of great relevance. Advisor: Bradley D. Lubben
... Field size and shape received substantial attention in the field of geography (Davis, 1926;Miller, 1953;Boyce and Clark, 1964;White and Renner, 1957) and more importantly in the last decades in agricultural sciences (Batte and Ehsani, 2006;Griffel et al., 2018;Janulevičius et al., 2019;Larson et al., 2016;Zandonadi et al., 2013). Research in agricultural sciences, considered field size and/or shape to examine machinery performances (Amiama, Bueno and Álvarez, 2008;Oksanen, 2013;, input application overlap Jernigan, 2012;Zandonadi et al., 2013), and agricultural production economics literature to investigate profitability of precision agriculture technology, especially on Global Navigation Satellite Systems (GNSS) guidance and related technologies such as boom control (Batte and Ehsani, 2006;Larson et al., 2016;Shockley et al., 2012). ...
... They analyzed a set of hypothetical farm fields each of which was 40.47 ha sized with and without the inclusion of grass waterways through the fields at 45 0 and 60 0 angles. In Kentucky, US, Shockley et al. (2012) investigated impacts of field size and shape on automatic section control profitability. The study was conducted for planting and spraying operations in four fields and within the fields there were a spectrum of shape, size, and obstacles. ...
Research suggests autonomous machines in open field arable farming can enhance biodiversity conservation and ecosystem services restoration. It is hypothesized that autonomous equipment could be a profitable alternative to conventional machines with human operators irrespective of field size and shape or cropping systems. However, lack of agronomic, economic and technical data has constrained economic assessment. Noting this, this study evaluated the economics of field size and shape, and mixed cropping with autonomous machines using the Hands Free Hectare and Hands Free Farm (HFH&HFF) demonstration experience of Harper Adams University, UK. Using the Hands Free Hectare Linear Programming (HFH-LP) optimization model results indicated that autonomous machines in British farming decreased wheat production cost by €15/ton to €29/ton for small rectangular fields and €24/ton to €46/ton for small non-rectangular fields. Sensitivity scenarios of increasing wage rates and labour scarcity shows that autonomous farms adapted easily and profitably to changing scenarios, whilst conventional mechanized farms struggled. The ex-ante economic analysis of corn-soybean strip cropping in the North American Corn Belt of Indiana found that per annum return to operator labour, management and risk-taking (ROLMRT) was 162.58/ha higher for autonomous strip cropping as compared to whole field sole cropping and conventional strip cropping. Conventional strip cropping was only feasible with a substantial amount of labour availability. The ex-ante economic analyses of wheat - barley - flower mix - spring bean regenerative strip cropping practices show that for Great Britain autonomous regenerative strip cropping ROLMRT was £57,760 and £25,596 higher compared to whole field sole cropping and conventional regenerative strip cropping practices. The profitability of autonomous machines in small fields irrespective of field size and shape, strip cropping systems and regenerative practices imply that autonomous machines could offer a win-win farming solution that help achieve the production and environmental goals of arable farming.
... ASC, like automatic steering systems, uses GNSS, and RTK to record precise geolocation datagenerally with a demand on precision of 2 cm (Yves and Noack Patrick, 2012). The objective of this technology is to automatically deactivate the boom sprayer/row of the agricultural implementseeder or sprayerwhen it passes over the same location, thereby preventing overapplication of fertilizers, pesticides, and seeds (Shockley et al., 2012). The overlap reduction by ASC during the plant protection, fertilization, and planting was used to calculate the reduction in seeds, fertilizer, and pesticide inputs. ...
... Literature used to calculate the reduction in inputs for crop productiondiesel, fertilizer, herbicide, seeds, etc. -revealed the most influential variables affecting their results. For example, several studies show that the overlap reductionwhich determines the amount of input savingsby the ASC F. Medel-Jiménez et al. scheme is influenced by the size, shape, and the presence of obstacles in the field as concluded by Corassa et al. (2018); Larson et al. (2015); Shockley et al. (2012); and Velandia et al. (2013). In the case of the proximal sensor and the prescription maps created by vegetation data from remote sensors schemes, the site-specific temporal and spatial characteristics such as weather, soil, and crop necessities have a relevant influence on the results; moreover, as concluded by Colaço and Bramley (2018) results on VRNA strategies using sensors and adopted by different authors are compromised by the experimental design and the comparable reference approach of the experiment. ...
... Such systems can help boost profitability by increasing the accuracy in placement of the inputs through eliminating overlaps and skips, as well as reducing machinery costs due to enhancement in machinery field capacity (Shockley et al., 2011). Complementary to auto-steering and guidance system, automatic section control (ASC) improves input use efficiency and saves input cost by automatically turning off sections, nozzles, and rows on the agricultural sprayers and planters in areas that inputs have been previously applied or in areas designated as non-suitable for crop production (Shockley et al., 2012;Edge et al., 2018). The input cost savings from ASC adoption were evaluated and a higher profit increase potential associated with ASC was achieved in smaller and more irregularly shaped fields (Shockley et al., 2012;Velandia et al., 2013). ...
... Complementary to auto-steering and guidance system, automatic section control (ASC) improves input use efficiency and saves input cost by automatically turning off sections, nozzles, and rows on the agricultural sprayers and planters in areas that inputs have been previously applied or in areas designated as non-suitable for crop production (Shockley et al., 2012;Edge et al., 2018). The input cost savings from ASC adoption were evaluated and a higher profit increase potential associated with ASC was achieved in smaller and more irregularly shaped fields (Shockley et al., 2012;Velandia et al., 2013). Greatest increase in net returns were found when the ASC is used in combination with the guidance systems (Smith et al., 2013). ...
... In the present study, the T3RRA CUTTA® software was not used in the optimisation of headland turns, as these were executed by the machinists, but it did allow the design of optimal trajectories for the tractor with autopilot; even so, the planning of these critical manoeuvres in automation enabled by the software needs to be explored in the future. Shockley et al. (2012b) measured the percentage overlap of spraying and seeding operations, comparing the use of automatic control on the tractor versus a conventional management scheme on four experimental farms, finding differences of up to 12.83% in seeding time without control versus 0.8% in seeding time with control in an irregular plot and 7.27% versus 0.47% in a regular plot, and up to 16.96% overlap in fertilisation without control versus 1.73% with control in an irregular plot and 12.62% versus 1.3% in a regular plot (Shockley et al., 2012b). Similarly, Velandia et al. (2013) found that the percentage of doubleseeded area could range from 0.1% to 15.5%, depending on the size and shape of the experimental plots, and that the adoption of an automatic control system in seeding tractors resulted in savings of between 4 and 26 $ ha -1 (Velandia et al., 2013). ...
... In the present study, the T3RRA CUTTA® software was not used in the optimisation of headland turns, as these were executed by the machinists, but it did allow the design of optimal trajectories for the tractor with autopilot; even so, the planning of these critical manoeuvres in automation enabled by the software needs to be explored in the future. Shockley et al. (2012b) measured the percentage overlap of spraying and seeding operations, comparing the use of automatic control on the tractor versus a conventional management scheme on four experimental farms, finding differences of up to 12.83% in seeding time without control versus 0.8% in seeding time with control in an irregular plot and 7.27% versus 0.47% in a regular plot, and up to 16.96% overlap in fertilisation without control versus 1.73% with control in an irregular plot and 12.62% versus 1.3% in a regular plot (Shockley et al., 2012b). Similarly, Velandia et al. (2013) found that the percentage of doubleseeded area could range from 0.1% to 15.5%, depending on the size and shape of the experimental plots, and that the adoption of an automatic control system in seeding tractors resulted in savings of between 4 and 26 $ ha -1 (Velandia et al., 2013). ...
Purpose: Agricultural work in Colombia, particularly in small and medium-sized farms, is lagging behind in terms of technology; advances such as precision agriculture (PA) are unknown. This project managed to promote the implementation of PA technologies in the primary tasks of land adaptation, by comparing efficiency indices when conventional practices were used against the use of new technologies. Theoretical framework: The company CasaToro SA, with its John Deere® agricultural line, allowed the implementation of StarFire TM6000®, 4240® Monitors, Auto Track 200®, and JDLink® technologies, and the use of T3RRA CUTTA® software, in tractors of its brand in different farms in Tolima, Colombia. Method/design/approach: Measurements of time and area worked in situ were taken and the data obtained were statistically compared using Analysis of Variance (ANOVA). Results and conclusion: Finding significant differences in tasks such as contour line drawing, which reported a decrease of up to 30% in the time needed in h ha–1, and in primary tillage with discs with increases of up to 13% of the tilled area in ha h–1. Research implications: In conclusion, in Tolima, which has extensive areas of agricultural production, the implementation of PA can improve yields and reduce production costs. Originality/value: To demonstrate the benefits of PA.
... Shapes of agricultural fields and obstacles within fields will determine driving patterns for farm operations such as seeding, fertilization, and harvesting. Overlap of seed, fertilizer, and pesticide applications increase with smaller field size and when fields are irregularly shaped, and the amount of overlap depends on size of the farm implement, obstacles in the field, field shape, and field size (Shockley et al. 2012). Automatic section control (ASC) can reduce excess application of seed, fertilizer, or pesticide by turning off parts of equipment where application to land has already occurred. ...
... Technological options for producers to reduce overlapping areas of fields include both software (e.g., guidance systems) and hardware (e.g., ASC of seeder); however, the return on investment of these technologies is site specific depending on farm characteristics (Shockley et al. 2012). It should be noted that because this study is observational in nature, causal links between greater amounts of nutrients in overlapping areas cannot be attributed exclusively to excess nutrient applications. ...
A total of 344 soil cores were taken in annually cropped fields of Alberta, Saskatchewan, Manitoba, and Ontario from 2011 to 2013 in areas where the field shapes, or obstacles within fields, required the driving pattern of farm operations to overlap. Soil nitrate-N concentrations in overlapping areas were 60% greater, soil Olsen-P concentrations were 23% greater, and pH was 0.5 units greater at 0 to 15 cm depth compared to non-overlapping areas, suggesting smaller nutrient use efficiency and potential for greater nutrient loss.
... The agricultural industry is undergoing the digital transforma- 9 tion. Many effects are already visible, such as a growing use of 10 smart technologies and big data analytics, which promise to lead to 11 higher efficiency, and better quality of production. Digital 12 transformation is also leading to the rise of agreements for value 13 co-creation with companies and supply cha Q6 in partners who 14 rethink their operations, controls, and coordination of activities. ...
... 22 Smart agriculture is often referred to as the Fourth Agricultural 23 Revolution [8], given its extensive benefits and prospective 24 economic impacts. The use of 4.0 technologies reduces the 25 environmental impacts and improves productivity and profits at 26 once [9][10][11][12]. 27 In this work, we take into consideration different types of 28 applications of the 4.0 technologies for smart agriculture [13] and 29 specifically: (i) Smart irrigation and input delivery; (ii) Agriculture 30 drones or Unmanned Aerial Vehicles (UAVs) [14]; (iii) Soil and 31 plants monitoring systems [15]; (iv) Yield Monitoring Systems; (v) 32 Farm Management Software (FMSs) and Predictive Data Analytics 33 [16]; (vi) Precision livestock systems, (vii) Smart greenhouses. ...
Smart Agriculture and 4.0 Technologies have brought several benefits to agricultural small and medium enterprises (SMEs). Nonetheless, the penetration of such digital technologies is still poor and slow. This study addresses the issue and provides some insights on the reasons related to the still limited adoption of 4.0 technologies within agricultural SMEs. Authors do not simply focus on the adoption per se, but rather devote attention to the SMEs owners/managers' subjective perception of the opportunity behind the technology adoption, and of the incentives or constraints given by the external environment as well as the organizational capabilities as embedded in the owners/managers’ skills and organizational routines. Authors analyze data collected by surveying 96 Italian agricultural SMEs owners/managers, and empirically confirm the relevance of managerial capabilities, managerial cognition, and managerial perception of the external environment for the adoption of 4.0 technologies in agricultural SMEs.
The results of this research support the conclusion that organizational capabilities related to the search for evidence-based knowledge by the SME’s decision-maker are crucial for the technology’s adoption. In addition, we show the statistical significance of the managerial perception of technological usefulness and of the availability of a supporting business environment either in the form of professional services or institutional support, on the technology’s adoption. The article ends by discussing the results and highlighting relevant managerial implications.
... Previous studies on guidance systems focused on field-level benefits and were adjusted for operation and investment costs (Dhuyvetter et al., 2016;Griffin et al., 2005;Shockley et al., 2011Shockley et al., , 2012aShockley et al., , 2012bSmith et al., 2013). Whole-farm and intangible costs of this technology have not been published. ...
... Precision agriculture goes beyond the costs, benefits, and profits. Research has shown that precision agriculture can be used as a risk management tool (Shockley et al., 2012a;Lowenberg-DeBoer, 1999). The five main risk factors include: ...
... Usage of these technologies give producers the opportunity to reduce their environmental impacts and improve productivity and profits at the same time (Schieffer and Dillon, 2015). Additionally, many studies have shown these technologies' potential for increasing profitability to producers (Smith et al, 2013;Shockley et al, 2012;Shockley et al, 2011;Mooney et al, 2009;Dillon et al, 2007;Batte and Ehsani, 2006;Griffin et al, 2005). Sonka and Coaldrake (1996) expressed the potential of the linkage between the internet and precision agriculture technologies to alter profoundly agricultural production and marketing systems. ...
... As can be seen in table 1 above, nearly 70% of precision agriculture technology users believe that their profits have increased due to the usage of the technologies. This belief would be consistent with the conclusions of a multitude of studies showing the potential for increases in profitability from the use of various specific precision agriculture technologies (Smith et al, 2013;Shockley et al, 2012;Shockley et al, 2011;Mooney et al, 2009;Dillon et al, 2007;Batte and Ehsani, 2006;Griffin et al, 2005). It is also noteworthy that only slightly over 5% of respondents believe their profits have not increased due to use of the technologies, while the remaining approximately 25% reported they were uncertain as to whether or not the technologies have increased their profits. ...
With its tremendous success by notable companies in varying industries, “big data” has become a hard-to-miss phrase and many believe its usage in agriculture is the future of the industry. However, the potential benefits of using big data come with just as many challenges, ranging from not knowing how to make use of it, to the debate over who owns and has access to it. A survey asking for producers’ opinions on precision agriculture technologies and big farm data was distributed to a sample of agricultural producers across Nebraska. A Poisson regression was used to determine the factors influencing propensity for data sharing and frequency tables were used to examine producer opinions on the topic. Older producers and those not using irrigation in their operation were found to have a lower propensity for sharing their farm-level data. In general, producer understanding of what big data is and how to use it is lacking. Precision agriculture users mostly believe they have seen increases in profits and efficiency due to use, but producers expressed concern over not knowing how to interpret and make use of the data as well as the overall affordability and cost of the technologies producing the data.
... They are believed to be able to improve the efficiency of farm operations by reducing overlap of inputs (seed, fertilizer, pesticides, etc.), thus saving money on input costs. Studies on specific precision agriculture technologies have shown them to consistently increase net returns (Smith et al, 2013;Shockley et al, 2012;Shockley et al, 2011). On top of the economic benefit, soil and water quality benefits can result from reduced or targeted application of inputs and irrigation water benefitting the environment through the lowered use of inputs (USDA-NRCS). ...
... Irrigated cropland in Nebraska tends to have higher input costs and higher yields than does dryland cropland in the state. Due to their higher input costs, irrigated producers may be more interested in these technologies because of their potential for increasing efficiency and lowering costs (Smith et al, 2013;Shockley et al, 2012;Shockley et al, 2011). Additionally, the increased yields from irrigation should lead to higher gross farm incomes, further increasing propensity for adoption. ...
An ever-increasing world population and increasingly-volatile commodity prices have charged producers with the task of becoming more efficient. To combat this, precision agriculture technologies aimed at increasing production efficiency are continually being developed, but their adoption is not yet widespread. A survey regarding the usage of these technologies was distributed to a sample of row crop producers across the state of Nebraska and a Poisson regression was used to determine the factors influencing adoption. Results of the study indicate that larger, more tech-savvy producers and those using irrigation are more likely to adopt a higher number of precision agriculture technologies, while operator age and gross farm income were found to be non-influential factors.
... Some of them are; Constant and Variable Rate Applications (Hamburg, 1999;Giles et al., 1996;Gil et al., 2007;Zhai et al., 2012;Sabancı and Aydın, 2014). Automatic Section Control (Saharda et al., 2011;Shockley et al., 2012) and Pulse Width Modulation (PWM) technique applications (Butts et al., 2019;Salcedo et al., 2020). In recent years, pressure-based sprayers have been replaced by flowbased sprayers. ...
Recently, different methods have been developed in order to increase the application efficiency of agricultural sprayer systems. The dynamic control of flow and / or pressure is performed by the proportional control of pumps or valves. The aim of the current study was to minimize the application rate error of field sprayers using the pump motor variable speed drive (VSD) of a centrifugal pump system. The flow rate and pressure control of the pump system was achieved using a Proportional Integral Derivative (PID) controller. During the tests, in the first stage, the flow rate-speed ratio was kept at a constant value to apply a constant application rate with varying ground speeds. In the second stage, the control of the system pressure was accomplished using the manually applied disturbing effects on the system. In the final stage, the flow rate of a spray nozzle was controlled by Pulse Width Modulation (PWM) depending on the speed at different constant pressure values. In flow control test, absulute percentage error of application rate in only six out of 150 measurements were higher than 10% which is acceptable application rate error at varying ground speeds from 6 to 10 km h-1. In pressure control tests, it was observed that the controller moved the system pressure back to the set value within 2-3 seconds after a disturbance applied. The system was able to control the nozzle flow rates between 50% and 100% by changing the duty cycle of the signal applied to the solenoid valve at the nozzle inlet during the PWM spray tests. Further investigation is required to test the observation in the current experiment on field sprayers to improve the efficiency of constant and variable rate or PWM applications. Keywords: PID; Flow based control; Sprayers; Variable rate application
... The Automated Control System (ASC) combines steering and reaction technologies. The ASC uses both GNSS and RTK to record 2 cm accurate geolocation data [29] . This technology aims to automatically deactivate the seeding machine or spraying machine, so that when it passes over the same site, spraying or seeding is stopped, thus preventing excessive use of fertilizers, pesticides, and seeds [30] . ...
Automation is one of the key systems in modern agriculture, providing potential solutions to the challenges related to the growing world population, demographic shifts, and economic situation. The present article aims to highlight the importance of precision agriculture (PA) and smart agriculture (SA) in increasing agricultural production and the importance of environmental protection in increasing production and reducing traditional production. For this purpose, different types of automation systems in the field of agricultural operations are discussed, as well as smart agriculture technologies including the Internet of Things (IoT), artificial intelligence (AI), machine learning (ML), big data analysis, in addition to agricultural robots, and finally, the economic transformations resulting from automation. SA uses technology and data-driven agriculture to increase resource utilization, reduce waste, and minimize environmental impact. Automation in tractors, harvesters, and various agricultural equipment is revolutionizing traditional agriculture, increasing productivity and efficiency, and reducing reliance on human labor. PA and SA emphasize environmentally friendly practices and reduce the inputs required to create ecosystems to protect the environment and mitigate the effects of climate change. This shows how PA and SA can help in the future of the agricultural sector.
... On farm level, adoption of robots leads to cost savings, especially for small-scale farms (Lowenberg-DeBoer et al., 2019). At field level, cost savings realized by automatic section control are higher the smaller and more irregular a field (Shockley et al., 2012). Wheat production, both on regular and irregularly shaped fields, is less costly if autonomous machinery is used (Al-Amin et al., 2023). ...
... Smart farming is a technology and innovation-based agricultural management by utilizing agricultural machines and equipment (agricultural tools and devices) and digital technology in the agricultural sector to increase productivity, added value, competitiveness and profits sustainably [9]. This agricultural system is an evolution of precision agriculture, which aims to increase the quality and quantity of agricultural products and optimize the use of labor [10]. ...
The growth of the hydroponic vegetable cultivation industry has become the main focus in meeting increasing food needs. However, proper and consistent nutritional management is necessary to achieve optimal results in hydroponic cultivation. This research describes the design of a microcontroller-based portable automatic nutrient mixing system designed to simplify and increase the efficiency of hydroponic vegetable cultivation. This system uses a microcontroller as the system’s brain to regulate nutrient concentrations automatically. The nutrients needed for hydroponic plants, such as liquid fertilizer, humic acid, and macro-micro nutrients, can be measured and mixed according to predetermined parameters. The success of this system is supported by the EC (Conductive Capability) sensors integrated into the system. The advantage of this nutrient mixing system is its portability, which allows users to organize hydroponic vegetable cultivation in various locations without significant limitations. The system can also be monitored and controlled remotely via a mobile app or computer, allowing users to control their plants’ nutrition even when they are away. Experimental results show that this system can produce a consistent nutrient mixture that meets the needs of hydroponic plants. Thus, this microcontroller-based portable automatic nutrient mixing system can effectively support the sustainable and efficient growth of the hydroponic vegetable cultivation industry.
... Intensively managed farms have a small advantage per hectare compared to extensively managed farms as far as savings can be achieved. The influence of unshaped fields was not taken into account in this calculation, but can be of considerable importance, especially for TG 3 "Section Control" [26]. ...
The vocational training course program Agriculture in Responsibility for our common World organised within the frame of the Banat Green Deal Project GreenERDE (Education and Research in the context of the digital and ecological transformation of agriculture in the Banat Region and Baden-Württemberg - towards resource efficiency and resilience) and delivered between June 2021 and May 2022 targets the knowledge and experience transfer to the farmer community in the Banat Region, Romania and other parts of the world. Current and future challenges, such as the ecological conversion and digital transformation of agricultural production, but also social, economic and cultural aspects haven been addressed transcending prevailing patterns. The innovative and relevant knowledge originating from practice, experiments, research or development projects throughout Europe and other continents is presented in a training format for interested participants.
... The profitability and economic impact of PAT adoption are dependent on the size of management zones, differences within management zones, field shapes, soil fertility condition, costs and prices, and the types of PATs utilized (Robertson et al. 2012;Shockley et al. 2012). The three most common hurdles to further adoption were the same in the Prairies and Ontario, and they were also the three most relevant factors in the Midwest, according to agri-retailers (Lowenberg-DeBoer and Erickson 2019). ...
Precision agriculture (PA), sometimes known as “prescription farming” or “variable rate technology,” is a collection of techniques that may be used to a variety of fields in agriculture. PA may be regarded as a novel management technique for agricultural systems’ control based on georeferenced data. It is based on the fine-tuning of georeferenced data through the use of monitoring procedures and the integration of soil, plant, and climatic variables (Stewart and McBratney 2000;Plant2001). Prior to precision agriculture becoming extensively adopted, Stafford (2000) underlines the necessity to create new techniques, notably in the field of remote sensing and mapping of spatial variability.
... One way farmers can increase production efficiency is using precision agriculture. Studies show that precision agriculture technologies consistently increase net returns (Smith, Dhuyvetter, Kastens, Kastens, & Smith, 2013;Shockley, Dillon, Strombaugh, & Shearer, 2012;Shockley, Dillon, & Stombaugh, 2011). However, not all farm operators adopt all precision agriculture technologies. ...
Since its inception at the turn of the 20ᵗʰ century, agricultural education has utilized agricultural mechanics and technology (power, structure and technical systems) to embed problem
solving, practical mathematics, and foundational physical sciences to its curriculum. These STEM concepts have kept the agricultural mechanics laboratory real and relevant in the modern school. However, the lack of general agricultural mechanic’s skills/ knowledge within the populace of recently graduated students of agricultural education programs at most universities and
institutions of higher learning is alarming.
Successful agricultural science and technology teachers agreed that their undergraduate coursework did not adequately prepare them to teach the current curriculum. Unanimously, the respondents expressed a concern for the lack of depth, scope, and technical skills in agricultural mechanics
currently being taught to future agricultural science teachers. (Ford, Shinn, & Lawver, 2008).
Due to these current trends in the population of agricultural educators, the strength of these important STEM skill sets taught in a mechanics setting is being lost to the underserved population
of rural students. The basis behind this innovation is utilizing cellular/ compact camera technology and social media to provide a medium for basic agricultural mechanics skills; in this case, tool identification.
... Small robots in particular also reduce the negative impact of cultivation processes on soil structure and biota due to their comparatively low weight (Shockley et al., 2019). With the increase in profitability of small, irregularly shaped fields due to autonomous machinery (Lowenberg-DeBoer et al., 2019;Shockley et al., 2012), ecosystem benefits from smaller field sizes may also be expected (e.g. Fahrig et al., 2015). ...
Farmers' attitudes toward field crop robots in a European setting have hardly been studied despite an increasing availability of the technology. Given the relevance of robots for small-scale agriculture, however, their acceptability in regions dominated by small-scale agriculture such as Bavaria, Germany, is of particular interest. Based on a sample of 174 farmers, an exploratory investigation of factors influencing the preference for large or small field crop robots in general and in specific settings and for mode of operation was carried out. Data were gathered using questionnaires at two events including lectures and field demonstrations and analyzed using bivariate tests. Farm size, farming system (organic/conventional), and occupational structure (part-time/full-time) were relevant attributes influencing the evaluation of advantages and disadvantages of field crop robots. Generally, respondents from larger farms focus more on financial benefits from robots and prefer large autonomous tractors. Conversely, small-scale or organic farmers consider environmental benefits of field crop robots relatively more important and favor small robots. Organic farming also positively correlates with the intent to purchase field crop robots within the next five years. More farmers can generally imagine owning small robots as opposed to an autonomous tractor in ten years, but at the same time view autonomous tractors as more suitable for most specified agronomic tasks. Non-purchase options such as contractor services and machinery sharing represent the preferred modes of robot deployment.
... Previous studies [39]- [44] tried to evaluate the savings and revenues caused by PA, but only by considering either the average savings from the application of a single technology or a specific growth phase of the crop (Table 1) According to [45], the impact of PATs on agricultural production is expected in two areas: ...
Precision agriculture (PA) offers the opportunity for farmers to improve both efficiency in managing resources and optimisation of process inputs, thus increasing their whole farm’s profitability. Despite these well-known benefits, the adoption of PA technologies (PATs) is still challenging due to socio-economic barriers and unique characteristics of the farms: cropping systems, technical developments, field sizes and farm scale. The economic aspect is undoubtedly one of the most important aspects to consider before adopting PATs. In most of the cases, farmers are reluctant to introduce precision farming systems since the costs and uncertainty about the profitability and advantages need to be addressed. This study aims to explore how PATs could affect the profitability of a representative Italian farm specialising in the production of cereals, making this a case study. In detail, an economic analysis was applied to determine the profitability of the farm, which showed that the adoption of PAT’s increased the yield of durum and soft wheat and significantly reduced the cost of mechanical operations and technical means. Therefore, the potential gains from the adoption of PATs challenges policymakers to design targeted interventions which could encourage their uptake. This paper is an extended version of the original contribution presented to the 2019 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor) in Portici, Italy.
... CTF typically releases 57-115 €/ ha extra profit, including the required investment, cost savings and increased yields. 107 The implementation of GNSS provides economic advantages of up to 28€/ha from input savings (Shockley et al., 2012). If a guidance system is already installed, the economic advantage of the automatic section control is even higher. ...
Achieving the UN Sustainable Development Goal of ‘a world with zero hunger’ by 2030 will require more productive, efficient, sustainable, inclusive, transparent and resilient food systems. This requires an urgent transformation of the agrifood sector. Digital innovations may be part of the solution. The ‘Fourth Industrial Revolution’ is seeing sectors rapidly transformed by ‘disruptive’ technologies such as Internet of Things and Artificial Intelligence and there are multiple potential applications in agrifood systems.
However, there are challenges. In particular, there is the risk of a ‘digital divide’. Developing economies and rural areas with weak technological infrastructure, low levels of e-literacy and digital skills and limited access to services risk being left behind in the digitalization process. Work is needed to ensure everyone benefits in the emerging digital society.
Conditions for a digital transformation
Certain conditions will shape the digital transformation of agriculture in different contexts:
• Basic and hygienic conditions are the minimum conditions required to use technology: availability, connectivity, affordability, e-literacy levels and supporting policies.
• Enabling conditions (‘enablers’) further facilitate the adoption of technologies: internet usage and digital skills among populations and support for agripreneurship and innovation culture.
• The capacity to take advantage of digital technologies will define the extent and nature of the economic, social and environmental impacts.
Examples of the use of digital technologies in agrifood systems
Digital technologies have already been shown to deliver benefits in agrifood systems. For example: mobile applications providing price information to farmers can reduce market distortions and improve earnings; precision agriculture technologies can improve efficiency of production; and, artificial intelligence can support timely decision making.
Challenges and future work
Social, economic and policy systems will need to shift to provide the basic conditions and enablers for digital transformation of agriculture. Disparities in access to technologies and services will need to be addressed.
Work on this will require more systematic data on digital technologies and digitalisation at the regional and population level. Different models will need to be identified for the inclusion of small-scale farmers in the digitalization process. Creation of a Digital Agriculture Readiness Index to evaluate the status of digital agriculture in different countries could help identify critical next steps in the digital agriculture transformation process.
... Profitability and economic significance of the adoption of PATs vary based on the size of management zones, variations within management zones, field shapes, soil fertility status, costs and prices, and types of PATs used (Robertson et al. 2008(Robertson et al. , 2012Shockley et al. 2012Shockley et al. , 2018. The adoption of PATs requires substantial investment of capital (Schimmelpfennig and Ebel 2011;Schimmelpfennig 2016;Tozer 2009). ...
Precision agriculture technologies (PATs) are promoted as part of both economically efficient and environmentally sustainable agriculture practices. Available PATs are generally classified into two groups; namely, embodied-knowledge and information-intensive PATs. Adoption levels of embodied-knowledge PATs are high relative to information-intensive PATs. Previous studies on the adoption of PATs do not differentiate between embodied-knowledge and information-intensive PATs. Additionally, most studies focus on the adoption of one or two of the available PATs rather than on adoption intensity—defined as the total number of individual PATs adopted. This study fills this gap in the literature by focusing on PAT adoption in general, and adoption intensity of embodied-knowledge and information-intensive PATs in particular. The study uses data from 198 farm-operator respondents in eastern South Dakota from a 2017 survey and employs descriptive statistics and probit and Poisson regression models for the analyses. As per the study, GPS guidance, yield monitor, and automatic section control systems are the most popular PATs, each with adoption rates of over 50%. Overall, findings from the study show that the effect of cropland size, producers’ perceptions of profitability, and operator off-farm income are similar for both adoption and adoption intensity of embodied-knowledge and information-intensive PATs. However, there are differences in the effect of land productivity and familiarity with computer use between adoption and adoption intensity and between embodied-knowledge and information-intensive PATs. The effect of producers’ perception of the environmental benefits of PATs is inconclusive and needs to be investigated in future research. The results indicate that analyzing PATs as a group of technologies masks differences in determinants between embodied-knowledge and information-intensive PATs. The study provides insights for developing programs, policies, and outreach efforts that encourage the adoption and adoption intensity of both embodied-knowledge and information-intensive PATs. Findings from the study will also be of interest to precision agriculture researchers, extension personnel, agribusinesses, and policymakers who may consider PATs as tools for improving agricultural sustainability and food security.
... An innovative method is the automatic section control, which uses geo-referencing data from a GNSS device to control section. The implementation of this method provides economic advantages due to input savings (Shockley, Dillon, Stombaugh and Shearer, 2012). If an auto-guidance system is already installed the economic advantage of the automatic section control is even higher. ...
The development of technologies in the 20th century led to evolution of precision agriculture concept.Nowadays, precision farming is usually associated with the use of GPS and satellite navigation, GIS, unmanned airplanes and drones, variable rate of application, as well as complex and sophisticated computer systems and software.
On the other hand, the main question is related to the profitability and efficiency of these technologies and the opportunities for their adoption. The main purpose of the research is to investigate the most popular concepts of precision farming and to analyze the technical and economic efficiency of different technologies based on literature review. The results indicate that the adoption of precision farming technologies is closely related to the farmer`s perception and needs institutional support.The promotion of precision farming under the Common Agricultural Policy is necessary in order to overcome the number of economic and environmental challenges and ensure sustainable development and green growth.
... Similarly, IoF2020 [10], the large-scale IoT pilot project on agrifood and DataBio [11], the big data project on agriculture and environment focus on intelligent systems, smart farming, and supply chain management and build systems that can be further exploited. Surveys that thoroughly review the area of smart farming services are available in [5][12] [13] [14]. The main outcomes of the comparative state of the art review conducted can be summarised as follows: (i) Farmers should have an active role in the design, planning and implementation of agricultural research/ innovations; (ii) Technical solutions must be user friendly and should allow farmers to produce more efficiently and leave more time for managing; (iii) Compatibility issues among existing services should be tackled through the use of open standards. ...
The evolution of smart farming and precision agriculture during the last decades has led to an increase of the available solutions that can be used by farmers. However, these two paradigms have not yet achieved high acceptance by end user farmers due to various reasons. In this respect, this paper elaborates on an innovative Multi-Actor Approach architecture that assists farmers to take better decisions and enables them to harness the full value of their own data and knowledge aiming to promote the adoption of the Internet of Things in the agrifood sector. Index Terms-precision agriculture, smart farming, Internet of Things, Multi-Actor Approach.
... However, Pedersen et al. (2006) reports and estimated average reduction in input cost from autonomous machinery of 20%, and ranging from 12 to 25%. Other Furthermore, current precision agriculture technologies such as automated steering and section control reduce input costs by 10% (Shockley et al. 2011(Shockley et al. , 2012. Therefore, a conservative estimate of a 10% reduction in the total cost for selected inputs (herbicide, insecticide, seed, and nitrogen) is applied to autonomous machinery. ...
A multi-faceted whole farm planning model is developed to compare conventional and autonomous machinery for grain crop production under various benefit, farm size, suitable field day risk aversion, and grain price scenarios. Results suggest that autonomous machinery can be an economically viable alternative to conventional manned machinery if the establishment of intelligent controls is cost effective. An increase in net returns of 24% over operating with conventional machinery is found when including both input savings and a yield increase due to reduced compaction. This study also identifies the break-even investment price for intelligent controls for the safe and reliable commercialization of autonomous machinery. Results indicate that the break-even investment price is highly variable depending on the financial benefits resulting from the deployment of autonomous machinery, farm size, suitable field day risk aversion, and grain prices. The maximum break-even investment price for intelligent, autonomous controls is nearly US$500 000 for the median days suitable for fieldwork when including both input savings and a yield increase due to reduced compaction.
... Previous research largely focused on economic benefits associated with precision agriculture technology adoption (Griffin et al., 2004;Schimmelpfennig, 2016Schimmelpfennig, , 2018Schimmelpfennig and Ebel, 2016;Shockley, Dillon, and Stombaugh, 2011;Shockley et al., 2012;Smith et al., 2013). Although results have been mixed with respect to these technologies' impact on farm profits, recent research indicates precision agriculture use has a small (∼2%), positive impact on net returns and operating profits (Schimmelpfennig, 2016). ...
The objective of this research was to evaluate producers’ perspectives of four key precision agriculture technologies (variable rate fertilizer application, precision soil sampling, guidance and autosteer, and yield monitoring) in terms of the benefits they provide to their farms (increased yield, reduced production costs, and increased convenience) using a best-worst scaling choice experiment. Results indicate that farmers’ perceptions of the benefits derived from various precision agriculture technologies are heterogeneous. To better understand farmers’ adoption decisions, or lack thereof, it is important to first understand their perceptions of the benefits precision agriculture technologies provide.
... Vellidis et al. (2014) used peanut (Arachis hypogaea L.) yield calculations to evaluate the accuracy of planting operations and found a tractor equipped with RTK-GPS TG increased yields and thereby profitability when compared to a conventional tractor. Economic analysis of automatic section control with TG for planting operations and whole-farm operations performed showed improved yields and profitability that, in part, were a function of using cheaper, reduced-size equipment for farming the same area of land (Velandia et al., 2013;Shockley et al., 2012b). Shockley et al. (2011) analyzed the profitability and risk involved with adopting TG technology and performed a break-even analysis of TG technology to determine the minimum land needed to achieve positive net returns. ...
A decision-support system was developed to assist small-scale producers, consultants, and extension agents with analyzing expected yield improvements, input cost savings, and equipment efficiency gains associated with global positioning system guidance on tractors using farm-specific details. Default parameters may be modified to perform partial budgeting and break-even analyses on a whole-farm basis. Findings suggest that this technology is profitable on as few as 49 ha, considered small-scale in the region, and under farm conditions assessed within. Further, tractor guidance is more feasible the more input-intensive the crops (e.g. cotton production vs. pasture maintenance) and the more expensive the equipment (e.g. using newer equipment). Changing input use affects greenhouse gas emissions that are reported as carbon equivalent footprint changes due to tractor guidance. For example, changing to tractors with lower horsepower to save on capital investment needs without changing the size of implement drawn, lowers fuel footprint as long as technically feasible and possible from a perspective of completing field work in a timely manner. Also, using manure instead of synthetic fertilizer, while economically advantageous, will increase the footprint of fertilizer applications given, among other factors, lesser nutrient density and thereby greater handling costs with manures. Quantifying these impacts across a whole farm is cumbersome since tractor guidance affects annual equipment use hours that are difficult to track and yet economically important. Hence, the decision support system was designed to capture farm-specific detail. The ability to perform whole-farm planning and sensitivity analyses in an automated, user-friendly, and flexible fashion is expected to increase technology adoption by small-scale producers.
... Tractor guidance (TG) is a precision agriculture technology that allows for more spatially precise application of seed, fertilizer, and agro-chemicals when compared to field operations conducted without GPS guidance. Using TG therefore simultaneously reduces environmental impacts associated with inefficient agricultural input usage (Brown et al., 2012;Shockley et al., 2011Shockley et al., , 2012aShockley et al., , 2012bVelandia et al., 2013;Vellidis et al., 2014). Further, GPS guidance and autosteering systems are widely used to increase operational efficiency, resulting in more even land coverage per unit of time. ...
Core Ideas
Tractor guidance (TG) technology allows for spatially precise input applications.
A decision‐support tool was developed to quantify environmental and economic impacts of TG.
Greatest C equivalent emission reductions and cost savings occurred with Cotton‐Only scenario.
TG was profitable for operations evaluated and led to C equivalent emissions reductions.
This tool may improve agricultural sustainability and enhance technology adoption.
Tractor guidance technology allows for more spatially precise input applications, which leads to efficiency gains that are difficult to quantify at the systems level. A decision‐support tool, Tractor Guidance Analysis (TGA), was developed to quantify carbon equivalent (CE) emission reductions associated with this technology for three scenarios (500 ha each): (i) cotton ( Gossypium hirsutum L.), (ii) soybean [ Glycine max (L.) Merr.], and (iii) cotton and soybean mixed. Carbon equivalent emission reductions for cotton, soybean, and mixed enterprises were 27.5, 5.6, and 16.5 kg ha ⁻¹ , with attendant increases in farm profitability (68,700, 16,900, and, $42,900, respectively). Tractor guidance led to total farm CE emission reductions of 15.7, 3.5, and 9.6 Mg for cotton, soybean, and mixed operations, respectively. These results highlight that CE reductions are (i) crop specific, (ii) scale dependent, and (iii) equipment and input‐use specific. Consequently, TGA can improve agricultural sustainability by informing users of economic and environmental repercussions of tractor guidance and may thereby enhance technology adoption.
... Precision agriculture is believed to have great potential to improve the efficiency of farm operations and to help increase farmers' net returns (Shockley et al., 2012;Smith et al., 2013;Castle et al., 2016), while also lowering water usage (Evans and Sadler, 2008). ...
Originally from Africa, watermelon is a staple crop in South Carolina and rich source of important phytochemicals that promote human health. As a result of many years of domestication and selection for desired fruit quality, modern watermelon cultivars are susceptible to biotic and abiotic stress. The present review discusses how genetic selection and breeding combined with geospatial technologies (precision agriculture) may help enhance watermelon varieties for resistance to biotic and abiotic stress. Gene loci identified and selected in undomesticated watermelon accessions are responsible for resistance to diseases, pests and abiotic stress. Vegetable breeding programs use traditional breeding methodologies and genomic tools to introduce gene loci conferring biotic or abiotic resistance into the genome background of elite watermelon cultivars. This continuous approach of collecting, evaluating and identifying useful genetic material is valuable for enhancing genetic diversity and tolerance and combined with precision agriculture could increase food security in the Southeast.
... Due to high production costs, farmers are exploring new technologies to fi ne-tune the use of diff erent inputs. Under this scenario, ASC technology can be used with different agricultural implements (Larson et al., 2016) such as sprayers and planters, by controlling sections, nozzles, and rows (Luck et al., 2010;Fulton et al., 2011;Sharda et al., 2011;Jernigan, 2012;Shockley et al., 2012a;Luck, 2013;Velandia et al., 2013;Larson et al., 2016). Several studies reported the benefits of ASC with sprayers (Batte and Ehsani, 2006;Luck et al., 2010;Larson et al., 2016), with estimates demonstrating that double application may exceed 10% of the field area (Batte and Ehsani, 2006). ...
Core Ideas
Corn yield was more proportionally reduced for double‐planted area as yield level decreased.
Soybean yield presented similar behavior for both double‐planted area and automatic section control at varying yield levels.
ROI for the ASC technology is recovered with lower planted area when corn is the main crop.
Overall DPA% was 5.5%, but for irregular fields double‐planted area increased faster as planted area rose.
Double‐planted area (DPA) on end rows commonly occurs in corn ( Zea mays L.) and soybean ( Glycine max L.) fields. Economic and yield losses from DPA can be reduced by using the automatic section control (ASC) technology on planters. However, the effects of DPA on crop yield within different yield levels (yield potentials) as well as different DPA proportion within Brazilian fields are not yet quantified. Using two datasets, the objectives of this study were: dataset I‐ (a) quantify yield losses from DPA in corn and soybean; (b) calculate the planting area necessary to recover the investment from ASC for Brazil and U.S. farmers when considering: (i) yield loss, (ii), DPA proportion, (iii) corn/soybean ratio in the rotation, and (iv) planted area; dataset II‐ (c) estimate DPA proportion at a regional‐scale using data from 128 Brazilian fields. The main results were: dataset I‐ (1) corn yield losses linearly increased due to DPA as yield level decreased; (2) soybean yields were less sensitive to DPA; (3) when only corn was considered, economic returns from using ASC was recovered with a smaller planted area; and dataset II‐ (4) overall DPA proportion was 5.5% of the total field area, increasing proportionally for irregular shaped fields. Use of ASC technology benefited soybeans via seed savings, while for corn, via both seed savings and superior yields. Future research focused on the ASC benefits should consider potential interactions between crop genotypes, field management, and environments.
... Furthermore, contract prices reflect drying and storage costs since those operations are imposed on contracted grain within the model. These costs are derived from Iowa State University Extension and Shockley, Dillon, and Stombaugh (2011) in which a hypothetical farm in Henderson County, KY was modeled with simulated data. A summary of the production practices used in the simulation can be found in Table 1. ...
A whole farm economic analysis was performed to maximize net returns utilizing variable maturity groups of corn and soybeans over different soil types. Demand for drying and storage equipment throughout harvest was generated based on profit-maximizing combinations of grain types, their respective maturity groups, and yield potential over different topsoil depths. Two marketing strategies were considered: cash and futures contract sales. It was found that drying equipment became a limiting factor in the proposed system. This prevented storage facilities from reaching full capacity and additional grain from capturing value in the futures market.
Agricultural production decisions impact how agriculture navigates within the safe and just operating space (SJOS). The ability to model and assess these impacts is crucial for policy analysis. This study systematically explores the literature for links between agricultural production decisions and SJOS. As agricultural production decision categories, we examine on-farm technology usage, farm structural change, and field structural change. We identify the impact mechanisms of various aspects of these categories and discuss the scope of evidence available. Technology usage impacts the SJOS often through farmers’ choice of technology and its effect on yield. Farm structural change impacts the SJOS through economies of scale and scope, while field structural change impacts directly and through management efficiency. There is considerable knowledge of these relationships but also research gaps. The study provides fundamental insights for characterizing the decision properties of agricultural production and is useful for guiding policy modelling for improved SJOS outcomes.
Digitalization transforms many industries, especially manufacturing, with new concepts such as Industry 4.0 and the Industrial Internet of Things. However, information technology also has the potential to integrate and connect the various steps in the supply chain. For the food industry, the situation is ambivalent: It has a high level of automatization, but the potential of digitalization is so far not used today. In this review, we discuss current trends in information technology that have the potential to transform the food industry into an integrated food system. We show how this digital transformation can integrate various activities within the agri-food chain and support the idea of integrated food systems. Based on a future-use case, we derive the potential of digitalization to tackle future challenges in the food industry and present a research agenda.
Expected final online publication date for the Annual Review of Food Science and Technology, Volume 15 is April 2024. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
The dramatically increasing nitrogen fertiliser prices and growing environmental awareness emphasise the need to optimise machine operability to avoid double overlapping of the target dose rate in different field units, including headlands and field bodies, to be more congruent with satellite-based nitrogen prescription maps. However, the map grids frequently do not correspond with farmers’ management practices, specifically machine operability. To this end, this study develops an algorithm that subdivides any given field into operable units by considering pneumatic spreaders based on the actual tramline on the field and placing the operable units along with this. The newly developed algorithm allows ex-ante specification of the required fertiliser amount. It shows how well such techniques can implement an optimised application map supported by the statistical information for each field unit. Uniform fertilizer application can further be compared with variable rate application (VRA) as well as machinery with and without section control, allowing the identification of areas with the greatest deviation and the excess amount of nitrogen applied. A more precise nitrogen application on both homogeneous or heterogeneous field units saves nitrogen and decreases the negative environmental impact.
Innovative Agrartechnologien und die digitale Datenverarbeitung gewinnen in der landwirtschaftlichen Praxis immer mehr an Bedeutung, und es ist davon auszugehen, dass die Automatisierung spezifischer landwirtschaftlicher Produktionsschritte mithilfe digitaler Anwendungen weiter voranschreiten wird. Verbunden damit ist die Vision, landwirtschaftliche Maschinen und Prozesse miteinander zu vernetzen, und zwar nicht nur auf Betriebsebene, sondern weit darüber hinaus – von Futtermittel- und Saatgutherstellung über den Anbau der landwirtschaftlichen Erzeugnisse bis hin zu Lebensmittelverarbeitung und Einzelhandel. Ziel ist letztendlich, nicht nur einzelne Prozessabschnitte, sondern gesamte Wertschöpfungsketten zu optimieren, im Sinne einer möglichst effizienten, aber auch ressourcenschonenden Agrar- und Lebensmittelproduktion. Schon jetzt ist abzusehen, dass sich Strukturen, Abläufe und Verantwortlichkeiten in der Landwirtschaft damit grundlegend ändern werden, wenngleich die möglichen Auswirkungen einer umfassenden Digitalisierung der Landwirtschaft derzeit noch weitgehend unklar sind. Klar ist hingegen, dass es sich um ein Thema mit hohem politischem Gestaltungsbedarf handelt, damit sich die angesprochenen Potenziale – insbesondere die Chance auf eine bessere Vereinbarkeit ökonomischer und ökologischer Ziele – umsetzen lassen. Nachdem im ersten Teil der TA-Analyse Entwicklungstrends digitaler Einzelanwendungen beleuchtet wurden (TAB-Arbeitsbericht Nr. 193), widmet sich der vorliegende Bericht den Voraussetzungen und den potenziellen Wirkungen einer umfassend vernetzten Landwirtschaft.
The use of digital systems in precision agriculture is becoming more and more attractive for farmers at every level. A few years ago, the use of these technologies was limited to large farms, due to the considerable income needed to amortize the large investment required. Although this technology has now become more affordable, there is a lack of scientific data directed to demonstrate how these systems are able to determine quantifiable advantages for farmers. Thus, the transition towards precision agriculture is still very slow. This issue is not just negatively affecting the agriculture economy, but it is also slowing down potential environmental benefits that may result from it. The starting point of precision agriculture can be considered as the introduction of satellite tractor guidance. For instance, with semi-automatic and automatic tractor guidance, farmers can profit from more accuracy and higher machine performance during several farm operations such as plowing, harrowing, sowing, and fertilising. The goal of this study is to compare semi-automatic guidance with manual guidance in wheat sowing, evaluating parameters such as machine performance, seed supply and operational costs of both the configurations.
Nowadays, a precise management of agricultural inputs based on spatial variability has become possible due to the availability of new technologies, including Global Navigation Satellite System (GNSS), unmanned aerial vehicles in agriculture (UAVs), high-resolution remote sensing, sensors to measure soil and plant characteristics, and controllers to guide agricultural machinery and apply precise amount of inputs. The benefits of precision agriculture are as follows:
•The return on the investment from crop production may be increased by improvements in yield and/or a reduction in inputs;
•The risk of environmental pollution from over application of agrochemicals that are associated with traditional agriculture can be reduced;
•Greater product quality assurance achieved from precise targeting and recording of field applications that improve traceability.
In the last decade, the number of fully operational and commercially available GNSS has increased. These systems provide accurate, continuous, geographic position and speed information in three dimensions and under all weather conditions to users 24 h a day. In the last two decades, the ability of Differential Global Positioning System to provide real-time, submeter- or even decimeter-level accuracy has revolutionized the agricultural industry. Applications of GNSS for agricultural purposes have thrived in recent years, and the literature is rich with numerous interesting examples. In this chapter, we limit our attention to five specific applications with which the authors are very closely involved: (1) GNSS in crop protection, (2) in variable rate application (VRA), (3) monitoring soil, plants, and production, (4) agricultural UAVs, and (5) ground platforms and autonomous tractors.
Not all the operations in precision agriculture need the same level of accuracy. Most of them, such as yield monitoring or VRAs, can be accomplished satisfactorily with DGNSS that has submeter accuracy. Only some operations, however, demand high (~10 mm range) geopositioning accuracy and precision, such as a plant-specific operation, precision guidance, and controlled traffic farming. This level of accuracy could be achieved with the use of real-time kinematic Global Positioning System.
The aim of this work is to discuss the ways risk may affect farm investments in ICT-based technology such as precision agriculture (PA) technologies and to establish how to better incorporate risk and uncertainty into cost-benefit analyses, in order to calibrate the estimated expected net present value from farmers' investments. To properly measure the factors underlying risk in agriculture it is essential to collect a proper piece of data and information from technology, market, and institutions. However, it is somehow hard to rely on historical information about PA technologies as they have appeared on the market in a recent time. Thus, in this work an ad hoc methodology useful to aid risk-averse farmers is developed, dealing with the estimation of financial parameters like discount rates, economic life of technology, and residual values at the end of the period for which benefits are considered.
Producers are often faced with information from industry touting a generic return on investment of precision agriculture technologies that are inflated through the use of simple techniques that ignore the time value of money. The economics of precision technologies are as site-specific as the technology. Therefore, educating producers (and agribusiness) on how to determine the return on investment by following the correct investment analysis techniques within a proper decision-making framework helps ensure an accurate site-specific return on investment for precision agriculture technologies.
When evaluating the economics of precision agriculture technologies (hardware or software), the results are as site specific as the technology. Following the appropriate decision‐making framework and analyzing the technology for each unique circumstance and farm characteristics is imperative to making the correct investment decision. Earn 0.5 CEUs in Crop Management by reading this article and taking the quiz at www.certifiedcropadviser.org/certifications/self‐study/806 .
This report looks at farm management practices with green growth potential, from farmer-led innovations (such as those directly linked to soil and water, Integrated Pest Management, organic farming) to science-led technologies (such as biotechnology and precision agriculture). Global food demand can only be met in a sustainable way if new forms of agricultural production and innovative technologies can be unlocked to increase the productivity, stability, and resilience of production systems with goals beyond just raising yields, including saving water and energy, reducing risk, improving product quality, protecting the environment and climate change mitigation.
Regardless of the crop production system used, weeds must be controlled at or below an economic threshold in order to achieve an acceptable level of profitability. The best method of weed control will depend on a number of factors, including labor, fuel and machinery cost, crop prices, and farmer’s willingness to accept production risks. In this chapter, we discuss economic factors that drive innovation in precision weed control technologies for agriculture and influence producer adoption of those technologies. We present a theoretical framework to help explain the economic incentives or disincentives to adoption of these emerging technologies. We also introduce the concept of externalities – costs or benefits realized by groups other than producers – which, if internalized to farm firms through taxes, subsidies, or restrictions, may influence producer adoption of a specific technology. We conclude with highlighting a number of important farm-level economic impacts of precision weed technology adoption.
The economic opportunities for combining heuristics management (herein, rules-of-thumb) with several farming technologies (uniform rate, variable rate seeding, variable rate nitrogen (N) and variable rate of both seeding and N) are modeled and investigated. Results suggest that weather-based heuristics as a strategy of selecting optimal production practices is promising for enhancing profitability. The ability to exploit interactive effects between heuristic strategies and precision agriculture technologies offers the potential to enhance profitability of both. The model shows potential for providing useful insights into improved production management decisions.
A whole farm economic analysis was conducted to provide a detailed assessment into the economic, risk, and production implications due to the adoption of auto-steer navigation. It was determined that auto-steer navigation was profitable for a grain farmer in Kentucky with net returns increasing up to 0.90% ($3.35/acre). Additionally, the technology could be used in reducing production risk. Adoption of the technology also alters production practices for optimal use.
Producers lack information about the profitability of variable rate technology (VRT) for agricultural sprayers. An economic framework was developed to evaluate the returns required to pay for VRT investments. Payback variables included input savings, yield gains, and reduced application costs. We illustrate the framework with two example investment scenarios.
Economic assessment of control of precision application perpendicular to the direction of travel remains lacking. This study uses marginal economic analysis through partial budgeting, break-even production area analysis and payback period in assessing the potential profitability of this investment. The hypothesis that savings from input application reduction alone can justify the equipment is confirmed for the base scenario examined. The base scenario indicates a gain of US7.74 l-1, a break-even area of 318 ha and a payback period of 3.19 years.
One of the newest innovations in Precision Agriculture is automatic section control for application equipment. Automatic section control systems will continuously record the areas of a field that have been covered during a field operation and then automatically turn on and off sub-sections of a machine to prevent double coverage of previously treated areas. Research on a cooperator farm in Kentucky, USA has shown potential savings of as much as 25% in very oddly-shaped fields using automatic section control. On the other hand, potential savings in rectangular fields would be almost zero. Accordingly, larger machine or section widths will cause overlapped areas to increase. To make an informed decision about purchasing and implementing the technology, producers need to know the potential savings for a given field shape. This paper describes a software tool that can be used to evaluate the percentage of a field that would be overlapped for different boom section sizes.
Precision guidance and precision sprayer control have substantial promise to reduce input application overlap, thus saving chemicals, fuel, and time during the application process. In this article we provide preliminary estimates of the magnitude of the private benefits for a precision guidance system combined with auto-boom control for agricultural sprayers (precision spraying). Hypothetical farm fields are analyzed, allowing comparison of the performance of the precision system to a traditional, non-precision system for different field shapes. An analysis of the impact of size of farm on system profitability also is explored. Our analyses suggest that, even when considering only private benefits of input savings, the value derived from a precision spraying system can be substantial. This is especially true when the sprayer patterns become more complex due to non-rectangular fields and due to the presence of waterways, drainage ditches or similar obstructions. Economic benefits of the precision spraying system increase proportionally to the cost of the spray material being applied and with the number of annual applications. Benefits also increase with increases in driver error rates for non-precision systems. Because most of the costs of the precision spraying system relate to the fixed investment, these costs are largely constant regardless of farm size. This translates to net benefits of precision spraying that increase with increased farm size.
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December 27, 2011 from http://www.bae.uky.edu/tstomb/Extension/FieldCAT_request.asp.
Improved profitability via enhanced variable rate application management resolution in grain crop production
- C R Dillon
- S Shearer
- S Pitla
- CR Dillon