Automatic Section Research Articles

Life cycle assessment of four different precision agriculture technologies and comparison with a conventional scheme

Precision farming technologies have the potential to enhance agricultural sustainability, but their exact environmental impact remains uncertain. This study aimed to (1) compare the life cycle assessment (LCA) of a conventional five-year crop rotation system with and without precision agriculture technologies (PATs) in Lower Austria; (2) to assess the emission hotspots and (3) to perform a sensitivity analysis on fertilization using the DeNitrification-DeComposition (DNDC) soil model to quantifying soil emission. Evaluated PATs included automatic steering systems, automatic section control (ASC), proximal sensors, and prescription maps from remote sensors. The crop rotation system included spring barley, soy, winter wheat, rapeseed, and winter barley. Assessed agricultural processes encompassed tillage, seeding, plant protection, fertilization, and harvesting. The impacts evaluated were climate change, fine particulate matter formation, freshwater eutrophication, freshwater ecotoxicity, terrestrial acidification, terrestrial ecotoxicity, and human carcinogenic toxicity. The sensor scheme scenario showed the highest reductions in climate change, followed by the prescription map, ASC, and autosteer scheme with reductions of −17.0, −8.9, −6.4, and −2.4%, respectively. This study emphasizes the potential of PATs to minimize environmental impacts in crop production while recognizing the influence of site and technology-specific factors. Future research should consider local variables for a comprehensive environmental assessment.

High precision vibration sectioning for 3D imaging of the whole central nervous system

BackgroundImaging and reconstruction of the morphology of neurons within the entire central nervous system (CNS) is important for deciphering the neural circuitry and related brain functions. With combination of tissue clearing and light sheet microscopy, previous studies have imaged the mouse CNS at cellular resolution, while remaining single axons unresolvable due to the tradeoff between sample size and imaging resolution. This could be improved by sectioning the sample into thick slices and imaged with high resolution light sheet microscopy as described in our previous study. However, the achievable quality for 3D imaging of serial thick slices is often hindered by surface undulation and other artifacts introduced by sectioning and handling limitations. New methodsIn order to improve the imaging quality for mouse CNS, we develop a high-performance vibratome system for sample sectioning and handling automation. The sectioning mechanism of the system was modeled theoretically and verified experimentally. The effects of process parameters and sample properties on sectioning accuracy were studied to optimize the sectioning outcome. The resultant imaging outcome was demonstrated on mouse samples. ResultsOur theoretical model of vibratome effectively depicts the relationship between the sample surface undulation errors and the sectioning parameters. With the guidance of the theoretical model, the vibratome is able to achieve a local surface undulation error of ±0.5 µm and a surface arithmetic mean deviation (Sa) of 220 nm for 300-μm-thick tissue slices. Imaging results of mouse CNS show the continuous sectioning capability of the vibratome. Comparison with existing methodOur automatic sectioning and handling system is able to process serial thick slices for 3D imaging of the whole CNS at a single-axon resolution, superior to the commercially available vibratome devices. ConclusionOur automatic sectioning and handling system can be optimized to prepare thick sample slices with minimal surface undulation and manual manipulation in support of 3D brain mapping with high-throughput and high-accuracy.

Understanding farmer views of precision agriculture profitability in the U.S. Midwest

Precision Agriculture (PA) technologies are well known to be useful in addressing field heterogeneities and enabling informed site-specific management decisions. While profitability is the foremost factor considered by farmers when making PA adoption decisions, information in this regard is lacking from the farmers' perspective. This paper analyzed 1119 farmer responses from a 2021 survey conducted in four states along the western margins of the U.S. Midwest. Our findings show that while most (around 60%) non-adopters indicate that they are unaware of PA profit change, adopters are likely to rate a major profit increase. About two thirds of adopters rated at least a 5% increase in profitability towards variable rate (VR) fertilizer application (72%), VR seed application (68%), and automatic section control (66%). We modeled farmers' profit change subsequent to PA adoptions. Our regression results demonstrate that the profits from PA usage increase over time and that use of conservation practices likely influences PA profitability in a positive way. As soil quality and weather factors also affect profit ratings, it would be beneficial to compare and demonstrate profitability potential of various PA technologies on a regional basis and tailor the promotion efforts to farmers most likely to benefit from them.

An open source corpus and automatic tool for section identification in Spanish health records

Background:Electronic Clinical Narratives (ECNs) store valuable individual’s health information. However, there are few available open-source data. Besides, ECNs can be structurally heterogeneous, ranging from documents with explicit section headings or titles to unstructured notes. This lack of structure complicates building automatic systems and their evaluation. Objective:The aim of the present work is to provide the scientific community with a Spanish open-source dataset to build and evaluate automatic section identification systems. Together with this dataset, the purpose is to design and implement a suitable evaluation measure and a fine-tuned language model adapted to the task. Materials and Methods:A corpus of unstructured clinical records, in this case progress notes written in Spanish, was annotated with seven major section types. Existing metrics for the presented task were thoroughly assessed and, based on the most suitable one, we defined a new B2 metric better tailored given the task. Results:The annotated corpus, as well as the designed new evaluation script and a baseline model are freely available for the community. This model reaches an average B2 score of 71.3 on our open source dataset and an average B2 of 67.0 in data scarcity scenarios where the target corpus and its structure differs from the dataset used for training the LM. Conclusion:Although section identification in unstructured clinical narratives is challenging, this work shows that it is possible to build competitive automatic systems when both data and the right evaluation metrics are available. The annotated data, the implemented evaluation scripts, and the section identification Language Model are open-sourced hoping that this contribution will foster the building of more and better systems.

Hybrid method to automatically extract medical document tree structure

A huge and rapidly growing quantity of medical documents is available in an electronic versions. These informing documents mostly have textual content in natural language. These facts can make the documents difficult to read, ambiguous, or even contain mistakes. Consequently, when a doctor decides on treatment, many medical critical errors can happen. The information extraction in unstructured documents can handle this problem. In our paper, we introduce an automatic section detection method in the medical field SDM (Section Detection in Medical field) to improve information extraction tasks by providing more context. Accordingly, we have constructed some rules to prepare automatically the training set. Then, we benefit from numerous features such as formatting style, syntactic, and semantic features to train a machine learning model to find titles. Then, a section tree is generated that can be useful for other tasks. As anticipated, our experiments show that merging these features using a Convolutional Neural Network (CNN) can lead to a better result in real medical documents according to the F1-score measure. Thus, we benefit from the layout information and our method can provide the document sections in a tree form. It is worth noting that our method can be easily applied in other fields since it is not strongly dependent on the document type or language.

Development and performance evaluation of an automatic section control system for corn precision planters

Overlap- planted area (OPA) tends to appear when large precision planters with more row units were employed in planting corn for the operator would typically need to drive the planter into the already planted area and decide when to stop planting to ensure complete coverage. This will lead to an increase in the cost of seeds and potential yield losses. In this paper, an automatic section control (ASC) system for corn precision planters was proposed to address above problems, the working principle of the system is to build a database of planted areas (DAPA) by collecting coordinates of the planted area during planting, and constantly query whether the coordinates of the seed tube egress point (STC) of each row unit is in DAPA, finally control the start-stop state of the corresponding brushless DC motors (BLDCM) according to the query results. A mathematical model calculating STC of each row unit in real-time according to coordinates acquired by GPS receivers is established. In addition, the system adopts controller area network (CAN) bus distributed control mode, which makes independent control of the row unit possible and offers good extensibility. Algorithms including Geohash algorithm, algorithm of discarding the same prefix, and dynamic trie data structure for improving the efficiency and performance of the ASC systems were proposed. Laboratory experiments were conducted at five Geohash string quantities (7410, 37040, 74070, 111110, and 148,150 Geohash strings), the results demonstrate that the proposed algorithms have high efficiency and are basically not affected by the increase of DAPA scale: time consumed (t) of retrieving and inserting a Geohash string from the dynamic trie is less than 36.51 ms and 62.99 ms, respectively, and there is no significant difference in t under various Geohash string quantities (P greater than 0.05). Field experiments were conducted at three positioning frequencies (fGPS) (2, 5, and 10 Hz) and three field shape complexity (pa) (0.08, 0.10, and 0.12). The results showed that the dp value could be decreased immensely when the ASC function was turned on: under the ASC function turned off, the corresponding dp values under the pa values of 0.08, 0.1, and 0.12 are 9.17 %, 7.71 %, and 10.74 %, respectively, while once the ASC function is enabled, the dp values under all experiments conditions do not exceed 1.63 %, and the change of pa has no significant effect on the dp. As the fGPS increases from 2 Hz to 5 Hz, dp value of field 1–3 decreased significantly by 0.56, 0.39, and 0.52 percentage points, respectively. Due to the influence of processor performance, the fluctuation of dp value is not obvious when fGPS increases from 5 Hz to 10 Hz. In conclusion, the proposed ASC system has a good performance in reducing OPA and can be employed on corn precision planters to save seeds and improve yield.

The adoption and usage of precision agriculture technologies in North Dakota

Precision agriculture technologies (PATs) hold promise for improving resource usage and agricultural profitability. This paper examines the adoption of automatic section control, Global Positioning Systems and autosteer, satellite imagery, variable rate nitrogen application, and variable rate seeding by farm operators in North Dakota. Survey data are analyzed using a double-hurdle model. The double-hurdle model allows operators' adoption and usage decisions to be examined separately. Results indicate that larger operations are more likely to adopt PATs, suggesting that economies of scale exist among PAT adopters. Several PATs have complementary effects on the adoption of other technologies. These effects are most noticeable for variable rate technologies. Cropping patterns are related to the adoption of PATs, as corn production is positively associated with the adoption of multiple PATs while wheat production is negatively associated with adoption of variable rate technologies. These results have implications for farm managers, precision agriculture dealers and service providers, and policy makers.

Reference section identification of construction specifications by a deep structured semantic model

PurposeContractors must check the provisions that may cause disputes in the specifications to manage project risks when bidding for a construction project. However, since the specification is mainly written regarding many national standards, determining which standard each section of the specification is derived from and whether the content is appropriate for the local site is a labor-intensive task. To develop an automatic reference section identification model that helps complete the specification review process in short bidding steps, the authors proposed a framework that integrates rules and machine learning algorithms.Design/methodology/approachThe study begins by collecting 7,795 sections from construction specifications and the national standards from different countries. Then, the collected sections were retrieved for similar section pairs with syntactic rules generated by the construction domain knowledge. Finally, to improve the reliability and expandability of the section paring, the authors built a deep structured semantic model that increases the cosine similarity between documents dealing with the same topic by learning human-labeled similarity information.FindingsThe integrated model developed in this study showed 0.812, 0.898, and 0.923 levels of performance in NDCG@1, NDCG@5, and NDCG@10, respectively, confirming that the model can adequately select document candidates that require comparative analysis of clauses for practitioners.Originality/valueThe results contribute to more efficient and objective identification of potential disputes within the specifications by automatically providing practitioners with the reference section most relevant to the analysis target section.

Development of a Hydraulic System for the Automatic Expansion of Powered Roof Support

A mechanical support in a longwall complex requires proper supervision and control of operating parameters because it is responsible for the safety of machines and workers. Its main functions are to protect the excavation against the adverse effects of rock mass and to move it along with the operational progress of the shearer and the scraper conveyor. In the era of Industry 4.0 as well as green economy and sustainable development, the development of machines and devices included in the longwall complex is an important area of invention. When it comes to the mechanical support included in the longwall complex, the authors propose changes to the hydraulic control system. The main purpose of the work was to develop a system that can automatically expand the legs of the powered support. Tests were carried out under real conditions while equipping the support section with a prototypical hydraulic system and with a system monitoring the correct operation of the prototype. This article presents the development of a prototypical installation under real conditions for testing on a longwall. The innovative solution proposed by the authors consisted of introducing a prototypical double valve block into the hydraulic system of the housing, which enables the function of automatic section expansion. The authors proposed a solution aimed at shortening the work time of the powered-support-section operator. The research results made it possible to evaluate the usefulness of the proposed solution. This type of solution can be considered technical support in the process of coal mining in an underground mine. Analysis presented in this paper, along with results from research conducted and its conclusions, can be of practical help to enclosure users to improve reliability and achieve optimal performance.

Precision Agriculture: Where do We Stand? A Review of the Adoption of Precision Agriculture Technologies on Field Crops Farms in Developed Countries

Precision agriculture is a management concept, which relies on intensive data collection and data processing for guiding targeted actions that improve the efficiency, productivity, and sustainability of agricultural operations. Several studies have assessed the adoption rate of precision agriculture technologies at regional or national scale, but the literature lacks global evaluations of the development of precision agriculture. For this paper, a review of 17 papers was conducted to provide an evaluation of the adoption rate of precision agriculture technologies on field crops farms in developed countries. This review shows a fast development of Global Navigation Satellite System-based technologies (such as guidance system and automatic section control), and yield monitor on combine harvesters, with a rate of adoption ranging from 60 to 80% in 2016. The adoption rate of these technologies is higher for North American farms than for European farms, with an average rate of adoption 17% higher in North America than in Europe. The three technologies closely correlated with variable rate application (soil mapping, variate rate fertilizing, and variable rate seeding) have seen a slower pace of growth, with only a third of the field crops farms of developed countries using automated methods of managing the spatial crop variability and spatial soil variability within a field. Three hypotheses to explain this difference are discussed: successive adoption of technologies, reject of complex technologies and preference for technologies improving working conditions.

Sectioning of branches of distribution networks with connected wind power plants

The paper presents a developed algorithm for coordinating the response times of the devices for automatic sectioning of bilaterally power supplied lines, of the digital relay protection and the reclosers in medium-voltage distribution networks with connected wind power plants.

Підхід щодо розміщення реклоузерів в розподільних мережах

Today, the electricity supplier is not able to declare the possible level of reliability of electricity supply, and the consumer simply does not have the opportunity to buy such “reliable” electricity. In such conditions, a differentiated approach to tariff formation is inevitable, which has been implemented in practice today, albeit in its infancy. Further improvement of the tariff-forming mechanism is impossible without creating a "flexible" dependence of the tariff on the indicators of the consumer's power supply reliability. Reliability indicators, in turn, are based, on the one hand, on the methods and approaches for their determination, and on the other, on statistically reliable data on the reliability of the elements that make up the equipment in the "generation-consumer" chain. Localization by automatic sectioning points at the design stage in the context of RAB tariff setting (incentive tariff setting) ensures the target nature of reducing SAIDI (index of average duration of outages in the system) and, as a result, assessing the possibility of achieving the target ENS (estimated volume of non-supplied electrical energy) significantly reduces the cost of network design and reconfiguration. In this regard, it is necessary to revise the state and topology of problem networks, including the operated partitioning hardware; to define support services in the energy company; be trained in software (for example, TELARM) as a design tool; to create the standards of the company (group of companies), taking into account the experience of colleagues from Moldova, the Security Council, the Baltic States, far abroad. As part of a scientific search, an approach was proposed, which is the basis for calculations to determine the optimal installation locations for automatic sectioning points for an average air line, as well as a parallel-serial air line with "targeted" automatic reserve input, corresponding to the optimal SAIDI value. The results obtained are presented in the framework of a joint technical meeting of leading specialists of operating enterprises, the customer and the staff of the Department of Power Supply named after A. V.M. Sinkova NULES of Ukraine.

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.

PRODUCTIVITY OF CORN HYBRIDS IN RELATION TO SOWING OVERLAP

ABSTRACT The automatic control of section shut-off in seed drills minimizes seeding overlap and can reduce productivity losses, especially in responsive crops such as corn. In that context, this study evaluated the effect of sowing overlap on the grain yield and productivity of three corn hybrids. A DB-50 precision seed drill, with 33 rows equipped with a 16-row automatic section control, was used in this experiment. A randomized block design was applied to test three corn hybrids under two sowing conditions (without sowing overlap - WOSO; and with sowing overlap - WSO), with four replications. The analyzed variables were the number of plants per hectare, the number of cobs per hectare, cob length, the number of grains per cob, the thousand grain weight, and productivity. WOSO areas presented cobs that were larger and had more grains, as well as a higher thousand grain weight, resulting in a productivity 13% higher than that of WSO areas. Therefore, the use of automatic section control is a technically feasible alternative to reduce seed costs and avoid productivity losses in corn crops.

Restoring normal network operation mode by automatically disabling network ATS

Automatic sectionalizing and redundancy of power transmission lines is one of the conditions for network intellectualization and can significantly reduce the power supply interruption time for rural consumers. However, both sectionalizing and redundancy of power transmission lines in 0.4 kV electric networks are used extremely limitedly since there are no sufficiently effective methods and technical means for their implementation. This article presents a method to automatically deactivate the automatic load transfer switch when restoring the normal network operation mode. The paper considers the implementation of the method on the example of damage occurring in the network where power is supplied to consumers from two power sources using an automatic load transfer switch and two sectionalizing units. A device is developed which allows implementing the developed method of automatic load transfer switch deactivation. The device consists of sectionalizing unit, automatic load transfer switch, voltage presence sensor, power direction sensor, memory element, repeater element, element AND and 3 elements NOT. The work of the device is described. The proposed method for automatically disconnecting the automatic load transfer switch in order to return the consumers’ power supply circuit to its initial state solves the problem of eliminating unreasonable power supply interruptions for consumers.

Effectiveness of Automatic Section Speed Control System Operating on National Roads in Poland

Driving speed remains within the most important factors in road safety, and speed not only affects the severity of a crash but is also related to the risk of being involved in a crash. Inappropriate speed is responsible for more than a third of all fatal accidents occurring on roads. In Poland the problem of speeding drivers is widely present. Hence, effective speed management and enforcement of speed limits on existing roads plays an important role. Possible solutions for rural roads are very limited and are focused mainly on administrative speed limitations and speed cameras enforcement. However, due to their limited effectiveness new solutions are still being sought. High expectations are associated with the automatic section speed control system that has recently been introduced in Poland. The aim of this paper is to examine the efficiency of the automatic section speed control system on the basis of speed surveys collected on chosen national roads where the system for sectional speed control was first implemented. Conducted comparisons and statistical analyses included driver’s average speed, speed percentiles, the number of speeding drivers as well as speed heterogeneity. To evaluate the efficacy of the sectional speed system, speed measurements were also conducted on fourteen, similar in geometry and functional characteristics, reference national roads located in Podlaskie voivodship in Poland without any specific speed enforcement.

OTOMATİK KORİDOR HIZ KONTROLÜ’NÜN BİR EĞİTİM YERLEŞKESİNDEKİ TEKRARLI SÜRÜCÜLERDEN OLUŞAN BİR ÖRNEKLEM ÜZERİNDEKİ GÖRÜŞLER VE HIZ ETKİLERİ ÜZERİNE ANALİZİ

Trafikte kazalara sebep olan yüksek hız problemini çözmek için uygulanan hız denetim sistemlerinden biri olan Otomatik Koridor Hız Kontrolü, dünya çapında son derece yüksek seviyede motorize olmuş ülkelerde popülerliği artan yeni ve gelişmiş bir akıllı ulaştırma sistemi uygulamasıdır. Bu makalede bir üniversite kampüsü içindeki düşük hız limitli güzergâhlara 2013 yılında mobil olarak kurulan bu sistemin, tekrarlı (her gün kampüse gidip gelen) sürücülerin önce/sonra dönemlerindeki hızlarına ve görüşlerine etkisini araştıran bir çalışma sunulmaktadır. Sürücülere yapılan anketlerden ise 729 adedi geçerli sayılmıştır. Titizlikle yapılan tespitlere göre; anket katılımcılarından sadece 32 adedinin önce/sonra dönemlerinin her birinde en az 8 kere sistem tarafından ortalama hızları tespit edilenler olduğu tespit edilmiştir. Önce dönemine ait hızların ortalaması 38.73 km/s iken, sonra döneminde hızlar 35.13 km/s’e düşmüştür. Sürücülerin kampüste uygulanan hız limitleri hakkındaki düşünceleri sorulduğunda ise, %3.3’ü hız limitlerinin yüksek olduğunu, %56.7’si düşük olduğunu, %36.7’si ise yeterli olduğunu belirtmiştir. Ankete katılan ve ortalama hızları tespit edilen sürücülerin “cinsiyet, yaş, görev, kaza sayısı, hız sınırı hakkında düşünceler” değişkenlerine göre önce/sonra dönemlerine ait ortalama hız farklılıklarını bulmak için Bağımsız iki örnek T testi kullanılmış “eğitim düzeyi, araç kullanma yılı, diğer aracı geçme eğilimi” değişkenlerinin önce/sonra dönemlerine ait ortalama hız farklılıklarını bulmak için ise Tek değişkenli varyans analizi yapılmıştır. Analize göre farklar anlamlı değildir. Cezai yaptırım olmaksızın ortalama hızlar anlamlı düşüş göstermiştir; fakat hız sınırlarına daha yüksek bir uyum, bir uygulama yaptırımı ile sağlanabilir. Sürücülerin kaza geçmişleri ile ortalama hızlarındaki düşüşler arasında anlamlı fark görülmemiştir.

Automatic Section Control Technologies and GPS Auto-guidance Systems Adoption in Cotton Production

Using data from a survey of cotton producers in 14 US states, and a bivariate probit regression, this study examined the effects of the following measured parameters on the adoption of Automatic Section Control (ASC) technologies and GPS Auto-Guidance (AG) systems: age, education, farm size, field geometry, information sources, as well as the use of specific production practices and other Precision Agriculture (PA) technologies. Results suggest that younger, more educated producers, consulting farm dealers for information about PA technologies, using other PA technologies, and managing larger farming operations located in counties with more irregularly shaped fields are more likely to adopt ASC technologies and AG systems. Predicted adoption probabilities estimated using regression results suggest the use of other PA technologies and farm dealers as a source of precision farming information have the largest impact on the probability of adopting ASC by cotton farmers. Additionally, these results suggest farmers with operations in eastern Arkansas, western Tennessee, and a couple of counties in middle Tennessee are more likely to adopt ASC technologies. Producers in these regions had the highest percentages of users of other PA technologies and farm dealers to obtain PA information.

Planter Technology to Reduce Double‐Planted Area and Improve Corn and Soybean Yields

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.

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.