Adoption Of Precision Agriculture Technologies Research Articles

Precision Agriculture for Resource Use Efficiency in Smallholder Farming Systems in Sub-Saharan Africa: A Systematic Review

Opportunities exist for adoption of precision agriculture technologies in all parts of the world. The form of precision agriculture may vary from region to region depending on technologies available, knowledge levels and mindsets. The current review examined research articles in the English language on precision agriculture practices for increased productivity among smallholder farmers in Sub-Saharan Africa. A total of 7715 articles were retrieved and after screening 128 were reviewed. The results indicate that a number of precision agriculture technologies have been tested under SSA conditions and show promising results. The most promising precision agriculture technologies identified were the use of soil and plant sensors for nutrient and water management, as well as use of satellite imagery, GIS and crop-soil simulation models for site-specific management. These technologies have been shown to be crucial in attainment of appropriate management strategies in terms of efficiency and effectiveness of resource use in SSA. These technologies are important in supporting sustainable agricultural development. Most of these technologies are, however, at the experimental stage, with only South Africa having applied them mainly in large-scale commercial farms. It is concluded that increased precision in input and management practices among SSA smallholder farmers can significantly improve productivity even without extra use of inputs.

Event dependence and heterogeneity in the adoption of precision farming technologies: A case of US cotton production

This study aims to examine event dependence and heterogeneity in the adoption of precision farming (PF) technologies. The study uses farm-level data and a conditional frailty model to estimate the empirical model. A novelty of this study is the introduction of a group level heterogeneity in the traditional conditional frailty model. The simulation model shows that the conditional frailty model addresses both event dependence and heterogeneity related issues in technology adoption. Results indicate that farmers with large farms, a higher share of total cultivated farmland, a higher percentage of income from farming, and farmers using computers for farm management are more likely to adopt PF technologies early on after a technology becomes available. Further, cotton producers who think that PF technology would be valuable in the future and those receiving farming information from university publications are more likely to adopt PF technologies soon after thetechnologiesbecome available.

A Precision Agriculture Technology Course for Regions with Lower Technology Adoption Levels

HighlightsPrior and post-knowledge surveys showed that students had varied knowledge levels in the course topics. Knowledge gains were higher for the course topics with lower prior knowledge scores. Knowledge surveys can be used to adapt to the needs of the students in real-time, improve instructional material, identify effective teaching methods, and modify the course. Abstract. Precision agriculture technologies offer several benefits, and most important among them are higher farm profits and improved environmental health. The quality of precision agriculture education is one of the main barriers to the adoption of these technologies. There are studies documenting the development of precision agriculture technology courses for the world regions with higher levels of adoption. However, there are limited studies for the world regions typically characterized by lower adoption of these technologies. This study attempts to develop and teach a precision agriculture technology course for such a world region Puerto Rico, a U.S. territory. This study also consisted of collecting and analyzing the pre- and post-knowledge levels of the students attending the developed course. Using the procedure for calculation of overall grade point average, the knowledge score for each course topic was calculated from all the pre- or post-survey responses for the course topic. Additionally, the knowledge gain for each course topic was calculated by subtracting the prior knowledge score from the post knowledge score of the course topic. The results indicated that knowledge gains were higher for the course topics with the lower prior knowledge scores and were lower for the course topics with the higher prior knowledge scores. The study indicates that a prior knowledge survey can be used to adapt to the needs of the students in real-time. Likewise, a post-knowledge survey can be used to improve instructional material, identify suitable teaching methods, and modify the course. World regions with limited adoption of precision agriculture technology may begin with a precision agriculture technology course without laboratory exercises, and later add laboratory exercises as equipment becomes available and adoption level increases. Keywords: Agricultural and environmental systems, Course development, Curriculum, Precision agriculture technologies, Student assessment

Factors Affecting Precision Agriculture Adoption: A Systematic Litterature Review

Abstract The aim of this paper is to present the main advances in the adoption of precision agriculture technologies. While we are witnessing the emergence of a literature dedicated to the adoption of new technologies, this theme still suffers from a lack of consensus on its conceptualization. Based on the prisma statement method (Preferred Reporting Items for Systematic Reviews and Meta-Analyzes), the objective is to carry out a review of the systemic literature in order to identify the main factors of adoption of the technologies of precision agriculture over the past ten years. The results show that individual factors are the most empirically identified as determining factors in the adoption of precision agriculture technologies. That said, the farmer is at the center of the adoption decision. Perceived utility is the factor most identified in the literature as the determinant of adoption.

Trends in scientific research on precision farming in agriculture using science mapping method

AbstractThe article highlights the worldwide dissemination of precision agriculture scientific researches published from the period of 1996–2018, data gathered in the Scopus citation database, using the science mapping method. The findings show that there is a constant rise in the number of publications in precision agriculture. The USA is not only leading in the adoption of precision agriculture technologies but also in the publication of papers, accompanied by China placed in second place. The most frequent keywords highlighted the main topics authors concentrated on more, and the national affiliation of most cited papers was the USA. The main prominence and contributions of the results present scientific research trends in precision agriculture in the last two decades, and demonstrate the main countries, authors and organizations who have contributed, and were more productive in this area.

Measuring a farm's profitability after adopting precision agriculture technologies: A case study from Italy

<p class="Abstract">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.</p>

Determinants of adoption and adoption intensity of precision agriculture technologies: evidence from South Dakota

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.

The adoption of precision agriculture technologies by Florida growers: a comparison of 2005 and 2018 survey data

The adoption of precision agriculture technologies by Florida growers: a comparison of 2005 and 2018 survey data

Duration analyses of precision agriculture technology adoption: what's influencing farmers' time-to-adoption decisions?

PurposePrecision technologies have been available at the farm level for decades. Some technologies have been readily adopted, while the adoption of other technologies has been slower. The purpose of this study is to examine the factors influencing farmers' time-to-adoption decisions as duration between year of commercialization of precision agriculture (PA) technologies and year of adoption, at the farm level.Design/methodology/approachTime-to-adoption, which is the difference in years between technologies becoming commercially available and the year of adoption was determined using non-parametric duration analysis, and the impact of specific farm/farmer characteristics on time-to-adoption were estimated using a semi-parametric Cox proportional-hazard (CPH) model, based on a panel dataset of 316 Kansas farms from 2002 to 2018.FindingsThe findings indicate that, time-to-adoption for embodied-knowledge technologies such as automated guidance and section control were statistically shorter than for information-intensive technologies such as yield monitors, precision soil sampling and variable rate fertility. Duration was indirectly (directly) proportional to commercialization date of embodied-knowledge (information-intensive) technology. More so, time-to-adoption statistically differed among technologies within these two broad categories. Time-to-adoption varies across farm location and between both types of technologies. Millennial farmers are more likely to adopt both types of technologies sooner compared to baby boomers. Net farm income, percentage changes in debt-to-asset ratio, corn to total crop acres and machinery investment had no significant impact on the time-to-adoption for both information-intensive and embodied-knowledge technologies. On the other hand, while variations exist, time-to-adoption of PA technologies is mainly driven by location of farm, generation of farmer, number of workers, years of farming experience, total acres cropped and the cost of crop insurance.Originality/valueThis study investigates how the financial position of farms, amongst other important factors might influence time-to-adoption of PA technologies. Results are useful to extension personnel and retailers for planning marketing or farm outreach programs taking into consideration that, time-to-adoption differs across regions and by specific characteristics, key amongst them: generation of farmer, number of workers, years of farming experience, total acres cropped and the cost of crop insurance.

A hybrid modelling approach to understanding adoption of precision agriculture technologies in Chinese cropping systems

Precision agriculture has the potential to deliver improved and more sustainable food production. Despite the various Chinese policy initiatives to strengthen national food security, there is evidence that the adoption of precision agriculture technologies in China has been much lower when compared to other developed agricultural economies. This study therefore aims to explore factors that determine Chinese farmers’ adoption of precision agriculture technologies in cropping systems and to provide recommendations on technology promotion in the future. The current status of precision agriculture adoption by smallholder farmers within crop farming systems in the North China Plain was explored. An integrated model of “Adapted Unified Theory of Acceptance and Usage of Technology (AUT2)” was developed to explain individual farmers’ intention to adopt precision agriculture. 456 surveys were conducted via face to face interviews in the North China Plain and structural equation modelling analysis was used to estimate the proposed AUT2 model. The results showed that perceived need for technology characteristics (PNTC), perceived benefits, perception of the efficacy of facilitating conditions and perceived risks of adoption have significant impacts on farmers’ intention to adopt precision agriculture. The facilitating conditions (e.g. knowledge, resources and access to consultant services) were the best predictor improving Chinese farmers’ willingness to adopt these technologies. Policy makers and service providers need to consider these factors in the promotion of technologies.

Environmental Benefits of Precision Agriculture Adoption

The purpose of this study is to analyse the environmental benefits of precision agriculture technology adoption obtained from the mitigation of negative environmental impacts of agricultural inputs in modern farming. Our literature review of the environmental benefits related to the adoption of precision agriculture solutions is aimed at raising farmers' and other stakeholders' awareness of the actual environmental impacts from this set of new technologies. Existing studies were categorised according to the environmental impacts of different agricultural activities: nitrogen application, lime application, pesticide application, manure application and herbicide application. Our findings highlighted the effects of the reduction of input application rates and the consequent impacts on climate, soil, water and biodiversity. Policy makers can benefit from the outcomes of this study developing an understanding of the environmental impact of precision agriculture in order to promote and support initiatives aimed at fostering sustainable agriculture.

ROLNICTWO PRECYZYJNE – KONCEPCJE I PERSPEKTYWY

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 of and needs for 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.

Profitability and downside risk implications of site-specific nitrogen management with respect to wheat grain quality

Profitability analyses of site-specific nitrogen (N) management strategies have often failed to provide satisfying reasons for adoption of precision farming technologies. However, effects of precision farming on product quality and price premiums, as well as on downside risk mitigation, are generally not taken into account. This study aimed to evaluate the comparative advantages of site-specific N management over uniform N management considering N supply on grain quality, and accordingly price premiums for wheat from a downside risk point of view. A virtual field was modelled with two subfields representing two distinctive yield zones to investigate how consideration of grain quality affects the economic potential of site-specific N management under temporally varying N mineralization and changing price patterns of wheat. Moreover, the extent was investigated to which site-specific N management can have a risk-reducing effect on economic shortfalls compared to uniform N management. Two site-specific N management options were assessed: variable N rate application using yield mapping and N sensor for real-time proximal sensing. Results indicated that even though crop yields were only slightly higher, higher expected protein contents of grains could be achieved with site-specific N management options compared to uniform N management. Baking wheat quality was secured to a greater extent with site-specific N management options. Higher average grain quality improved the economic benefits due to price premiums. A risk-reducing effect was observed with the site-specific N management by maintaining the baking wheat quality with a higher probability. Higher economic returns mostly compensated the additional costs for the precision farming technologies in the lower tail of the probability distribution and, thus, site-specific N management did not show any substantial disadvantage on downside risk as compared to uniform N management.

Exploring the impact of innovation adoption in agriculture: how and where Precision Agriculture Technologies can be suitable for the Italian farm system?

Starting from the twenty-first century, the digital paradigm has brought with it a new way of thinking about innovation within the firms through the introduction of the Internet of Things (IoT) and the Information and Communications Technology (ICT), keys factors of digital transformation technologies. In addition, the use of Precision Agriculture (PA) has created a new approach to farming practices, allowing farmers to reduce the inputs, while protecting natural resources. Today, also in Italy PA is starting to be an effective technological innovation potentially capable to improve farms efficiency and sustainability. Given these considerations, the present paper aims, firstly, to review the factors more affect the adoption of precision agriculture technologies (PATs); secondly, to investigate where the PATs could be convenient to apply in Italy. A multi-Criteria Decision Analysis method is performed to achieve this goal. The analysis shows that the geographical area more likely to use PATs in Italy is the North East territory. However, in Italy, the adoption of these technologies in agriculture meets various obstacles: the cultural barrier to innovation and a limited awareness of benefits; the reduced average size of farms, with the difficulty of investing in and appreciating the benefits of PATs.

A systematic literature review of the factors affecting the precision agriculture adoption process

For agricultural industries to capture many environmental and economic benefits that have been demonstrated for precision agriculture (PA) technologies, an understanding of the factors affecting adoption of these technologies is required to adequately inform the development of PA approaches and the programs used to promote their use. A systematic review of the literature was undertaken to explore the processes of adoption of PA technologies, using an innovation diffusion framework to analyse the complex interactions between different factors in the adoption process. A total of 34 relevant publications were extracted from Scopus database following a systematic search and analysis process. PA technologies adoption research has predominantly been undertaken in the United States and Germany, with industrial crops receiving the most research attention. Relative advantage and motivation were the most frequently mentioned factors affecting PA technologies adoption. However, very few studies have examined multiple components of the complex adoption process, and most were narrowly focussed on assessing the impact of a single aspect. The conclusions drawn from the review are that many of the determinants of innovation diffusion that have been examined in other industry contexts were absent in the PA technologies adoption literature, and that the complexity and multidimensional nature of the adoption process was very poorly represented.

Economic, Agronomic, and Environmental Benefits From the Adoption of Precision Agriculture Technologies

Precision agriculture (PA) as an integrated information- and production-based farming system is designed to delivery high-end technology solutions to increase farm production efficiency and profitability while minimizing environmental impacts on the ecosystems and the environment. PA technologies are technology innovations that incorporate recent advances in modern agriculture providing evidence for lower production costs, increased farming efficiency and reduced impacts. However, the adoption of the precision agriculture technologies has encountered difficulties such as additional application or management costs and investment on new equipment and trained employees. Some of these PA technologies were proven efficient, providing tangible benefits with lower costs and as a result they quickly gained scientific interest. To investigate further the economic, agronomic, and environmental benefits from the adoption of PA technologies a systematic review was conducted, based on the systematic search and evaluation of related eligible articles.

Satellite detection of rising maize yield heterogeneity in the U.S. Midwest

The future trajectory of crop yields in the United States will influence food supply and land use worldwide. We examine maize and soybean yields for 2000–2015 in the Midwestern U.S. using a new satellite-based dataset on crop yields at 30m resolution. We quantify heterogeneity both within and between fields, and find that the difference between average and top yielding fields is typically below 30% for both maize and soybean, as expected in advanced agricultural regions. In most counties, within-field heterogeneity is at least half as large as overall heterogeneity, illustrating the importance of non-management factors such as soil and landscape position. Surprisingly, we find that yield heterogeneity is rising in maize, both between and within fields, with average yield differences between the best and worst soils more than doubling since 2000. Heterogeneity trends were insignificant for soybean. The findings are consistent both with recent adoption of precision agriculture technologies and with recent trends toward denser sowing in maize, which disproportionately raise yields on better soils. The results imply that yield gains in the region are increasingly derived from the more productive land, and that sub-field precision management of nutrients and other inputs is increasingly warranted.

Farm’s Sequence of Adoption of Information-intensive Precision Agricultural Technology

Abstract. Precision agriculture (PA) has been commercially available for decades, however only specific technologies have been readily adopted. The overall goal of this study was to provide information of the historical changes (from 2000 to 2016), current status of PA utilization, and sales expectations in the next time period. Within this overarching objective, specific goals included 1) determining the specific technologies that farmers adopt and 2) estimating the probability of transitioning from one bundle of PA technologies to another. The three information-intensive technologies included: 1) yield monitor (YM) with or without GNSS 2) variable rate (VR) application of inputs, and 3) precision soil sampling (PSS). Combinations of these three technologies in addition to a possible “no technology adopted” response resulted in eight categories of PA technology bundles. Each year, farms were classified as having one of these eight possible bundles of PA technology. Adoption of PA technologies has increased over time, with the use of only YMs and the bundle of all three PA technologies (YM, PSS, and VR) as the two primary bundles being adopted. When only VR was adopted, there was a 47% probability that the farm would add a YM by next year. When a farm used YM, VR, and PSS, there was a 99% probability that a farm would continue using the bundle in the following year. The results are useful for farmers, extension professionals, and policymakers to understand prior adoption paths for bundles of PA technology. Future steps can connect this database on adoption of PA technology with farm meta-descriptors such as acreage, type of crop, rotation, other relevant management practices, and financial variables so to better understand how farmers are integrating technologies into their farming operations. Keywords: Adoption, Information-intensive, Markov chain, Precision agriculture, Sequential, Site specific, Soil sampling, Transition probability, Variable rate, Yield monitor.

Precision Farming Adoption Trends in the Southern U.S.

Studies investigating temporal and geographic adoption of precision farming technologies (PFT) are valuable for researchers, consultants, and farmers to make more informed production decisions. Focusing on southern U.S. cotton producers, the objective of this study was to assess the timing trends and geographic patterns of PFT adoption. Data were obtained from a mail survey of cotton producers in 14 southern states in 2013. The overall PFT adoption level was 73.5%. Specifically, the adoption level was 40.9% for information gathering (IG), 67% for global positioning system-guidance (GPSG), 25.3% for variable rate application (VRA), and 29.3% for automatic section control technologies (ASC). The cumulative adoption level across years generally fit the logistic function curve for the various PFT evaluated in this study. The peak annual adoption growth was 4.0% in 2008 for IG, 6.8% in 2010 for GPSG, 4.4% in 2010 for VRA, and 7.2% in 2010 for ASC. Geographically, cotton farmers in the Corn Belt region had the highest PF adoption level (91.7%), followed by the Mississippi Delta region (80.7%) and the Northern and Southern Plains region (75.4%). The lowest PF adoption level was in the Southeast region (65.2%). Of the four PFT categories, GPSG was the most widely adopted. The geographic technology adoption patterns are valuable for farm input dealers to target potential buyers of PFT. This study provides researchers with valuable PFT adoption trends among southern cotton farmers and helps producers make more informed adoption decisions.

Adoption of precision agriculture technologies by German crop farmers

In recent years, precision farming has been receiving more attention from researchers. Precision farming, which provides a holistic system approach, helps farmers to manage the spatial and temporal crop and soil variability within a field in order to increase profitability, optimize yield and quality, and reduce costs. There has been considerable research in farmers’ adoption of precision agriculture technologies. However, most recent studies have considered only a few aspects, whereas in this study a wide range of farm characteristics and farmer demographics are tested to gain insight into the relevant aspects of adoption of precision farming in German crop farming. The results of a logistic regression analysis show that predictors with positive influence on the adoption of precision farming are agricultural contractor services such as an additional farming business, having under 5 years’ experience in crop farming, having between 16 and 20 years’ experience in crop farming, and having more than 500 ha of arable land. However, having a farm of less than 100 ha and producing barley are factors that exert a negative influence on the adoption of precision farming. The results of this study provide manifold starting points for the further proliferation of precision agriculture technologies and future research directions.