Abstract In recent years, plant phenotyping technologies have been widely applied to evaluate complex plant traits such as morphology, physiology, ecology, biochemistry, tolerance, growth and yield. Hyperspectral/multispectral cameras, artificial lighting sources, mechanisms and computers together capture images of different species of plants. Due to the non-uniform intensity of lighting sources in

Abstract Grid sampling allows a variable rate of lime to be applied and has been marketed as a cost saver to producers. However, there is little research that shows if this precision application is profitable or not. Previous research on variable-rate lime has considered only a small number of fields. This paper uses soil sampling data from 111 fields provided by producers in Oklahoma and Kansas. The

Abstract 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

Abstract Severe working conditions, the cost reduction need and production growth justify the adoption of technological techniques in agricultural production. Currently, Global Navigation Satellite System (GNSS) based navigation systems are very popular in agriculture. However, relying only on GNSS data and the availability of crop maps that also need to be updated may become a problem. One may face

Abstract Nitrogen (N) from farm fields is a source of pollution to fresh and marine waters. Modifying N fertilizer application rate and timing to consider the spatial and temporal variability in plant N requirements could reduce N losses from farmlands, resulting in improvements to surface water quality. In this study, the field-scale hydrologic and N simulation model DRAINMOD-NII was used to predict

Abstract Potassium (K) is one of three main crop nutrients, and the high rate of potash fertilizer utilization (second only to nitrogen) leads to high prices. Therefore, efficient application, as well as rapid and time monitoring of K in crops is essential. Several turnover box and field experiments were conducted across multiple years and cultivation factors (i.e., potassium levels and plant varieties)

Abstract Smartphone technology is promising for the future development of agriculture, as it can facilitate and improve many operational procedures and can also be combined with precision agriculture technologies. Yet, existing research on smartphone adoption in agriculture is scarce. Therefore, this paper empirically explores the factors influencing smartphone adoption by German farmers. The relationship

Abstract Weed control between plastic covered, raised beds in Florida vegetable crops relies predominantly on herbicides. Broadcast applications of post-emergence herbicides are unnecessary due to the general patchy distribution of weed populations. Development of precision herbicide sprayers to apply herbicides where weeds occur would result in input reductions. The objective of the study was to test

Abstract An accurate and robust strawberry flower representation and detection scheme is a key step to enable the reliable forecasting of fruit yield for use in precision agricultural applications. A state-of-the-art deep-level object detection framework which processes images through several layers using a region-based convolutional neural network (R-CNN) was developed to visually represent the instances

Abstract Laser land levelling has contributed immensely to irrigation water saving to cope with declining ground water tables in South Asia. A topographic survey of a field is a pre-requisite to achieve high accuracy in land levelling. Presently, manual topographic surveys are conducted before using a laser land leveller in South Asia, which is cumbersome, time consuming and requires substantial operator

Abstract Accurate estimation of rice yield with remotely sensed data plays a role in ensuring food security at local or national scales. In this study, an estimation scheme integrating a rice canopy scattering model (RCSM) and a genetic algorithm optimization tool (GAOT) was proposed on a basis of radar remote sensing technology. A C-band Radarsat-2 synthetic aperture radar (SAR) image acquired at

Abstract Delineation of management zones (MZs) are needed to manage fields in order to maximize economic return, minimize environmental impact, and improve soil and crop management. The MZs of uniform production potential may offer an effective solution to nutrient management. In this study, a total of 122 geo-referenced representative surface (0–250 mm depth) soil samples were collected from the study

Abstract This study reviewed research published after 1990 on the economics of agricultural mechatronic automation and robotics, and identified research gaps. A systematic search was conducted from the following databases: ScienceDirect, Business Source Complete, Wiley, Emerald, CAB Abstract, Greenfile, Food Science Source and AgEcon Search. This identified 4817 documents. The screening of abstracts

Abstract Specialty crops, such as apples, are vulnerable to insects and pathogens, and require higher pesticide input than row crops, a significant fraction of which is off-target loss, causing adverse environmental and socio-economic impacts. An advanced laser-guided variable-rate sprayer (VRS) could improve spray deposition uniformity and minimize pesticide waste, while maintaining efficacy against

Abstract The remote sensing (RS) technique is less cost- and labour- intensive than ground-based surveys for diverse applications in agriculture. Machine learning (ML), a branch of artificial intelligence (AI), provides an effective approach to construct a model for regression and classification of a multivariate and non-linear system. Without being explicitly programmed, machine learning models learn

Abstract The objective of this study was to evaluate the crop monitoring performance of a consumer-grade camera with non-modified and modified spectral ranges which are commonly used in low-altitude unmanned aerial vehicle (UAV) platforms. The camera was fixed sequentially with seven types of filters for collecting visible images and near-infrared (NIR) images with different center band locations and

Abstract Yield forecasting is essential for management of the food and agriculture economic growth of a country. Artificial Neural Network (ANN) based models have been used widely to make precise and realistic forecasts, especially for the nonlinear and complicated problems like crop yield prediction, biomass change detection and crop evapo-transpiration examination. In the present study, various parameters

Abstract While precision agriculture (PA) technologies are widely used in cropping systems, these technologies have received less attention in mixed farming systems. Little is known about the nature, extent, and temporal stability of spatial variability of pastures in mixed farming systems and the feasibility of managing this variability. This paper describes a technique to create a Stability Index

Abstract The adoption of precision farming techniques (PFTs) has been widely studied targeting specific PFT or farming systems along with the potential benefits of these PFTs in terms of yield or input use. However, few studies have examined how PFTs are adopted and used at the farm level. In this study a preliminary investigation was made of on-farm PFT uses in the Oise region (northern France). Three

Abstract Automation is a new frontier in specialty agriculture equipment. Specifically, unmanned aerial vehicles (UAV), machine vision and robotics will increasingly appear in sustainable agricultural systems. The use of small UAVs retrofitted with spraying systems allows precision aerial applications on small targets. These precision applications can result in significant cost savings and reductions

Abstract Technological innovations are changing mechanisation in agriculture. The most recent wave of innovations referred to as smart farming technologies (SFT), promise to improve farming by responding to economic, ecological, and social challenges and thereby sustainably develop agriculture throughout Europe. To better understand the relevance of ongoing technological progress for farming systems