An approach to compensation of dust effects on seed flow sensors

Optical seed mass flow sensors are widely used on seed drills and planters. An important challenge in these sensors is their malfunction in a dusty condition. Dust caused by soil and seeds may sit on the light elements and disrupt its function. In this study, an approach was developed to compensate this effect. A non-contact intelligent system with infrared diodes and a microcontroller with ARM architecture was built up to monitor the seed flow in the delivery tube of seed drills. At the hardware phase, a glass with a different radius of curvature was installed in front of the elements. The semi-cylindrical glass placement in front of the optical elements meant that the arrangement was sealed against dust. Besides, the fall of the seeds tangential to the glass during the sowing caused the glass to self-clean. However, the hardware configuration of the seed flow sensor with semi-cylindrical glass alone was not sufficient under adverse dusty conditions. A suitable algorithm was therefore developed and applied to compensate for the dust effect. In this case, instead of the level of output voltage, MS (mean of variances) of sensor outputs was calculated. The mass flow estimation model was obtained using multiple regression between the MS index of the seed flow sensor and digital scale data. Experiments were carried out using different types of seeds in several repetitions. In all tests, the correlation coefficient of the mass flow estimation model was obtained above 0.9. The results revealed that this system works correctly and precisely in dusty field conditions without having to clean the sensing elements

A Novel Approach for Development and Evaluation of LiDAR Navigated Electronic Maize Seeding System Using Check Row Quality Index.

Crop geometry plays a vital role in ensuring proper plant growth and yield. Check row planting allows adequate space for weeding in both direction and allowing sunlight down to the bottom of the crop. Therefore, a light detection and ranging (LiDAR) navigated electronic seed metering system for check row planting of maize seeds was developed. The system is comprised of a LiDAR-based distance measurement unit, electronic seed metering mechanism and a wireless communication system. The electronic seed metering mechanism was evaluated in the laboratory for five different cell sizes (8.80, 9.73, 10.82, 11.90 and 12.83 mm) and linear cell speed (89.15, 99.46, 111.44, 123.41 and 133.72 mm·s-1). The research shows the optimised values for the cell size and linear speed of cell were found to be 11.90 mm and 99.46 mm·s-1 respectively. A light dependent resistor (LDR) and light emitting diode (LED)-based seed flow sensing system was developed to measure the lag time of seed flow from seed metering box to bottom of seed tube. The average lag time of seed fall was observed as 251.2 ± 5.39 ms at an optimised linear speed of cell of 99.46 mm·s-1 and forward speed of 2 km·h-1. This lag time was minimized by advancing the seed drop on the basis of forward speed of tractor, lag time and targeted position. A check row quality index (ICRQ) was developed to evaluate check row planter. While evaluating the developed system at different forward speeds (i.e., 2, 3 and 5 km·h-1), higher standard deviation (14.14%) of check row quality index was observed at forward speed of 5 km·h-1

Simulation of site-specific irrigation control strategies with sparse input data

Crop and irrigation water use efficiencies may be improved by managing irrigation application timing and volumes using physical and agronomic principles. However, the crop water requirement may be spatially variable due to different soil properties and genetic variations in the crop across the field. Adaptive control strategies can be used to locally control water applications in response to in-field temporal and spatial variability with the aim of maximising both crop development and water use efficiency. A simulation framework ‘VARIwise’ has been created to aid the development, evaluation and management of spatially and temporally varied adaptive irrigation control strategies (McCarthy et al., 2010). VARIwise enables alternative control strategies to be simulated with different crop and environmental conditions and at a range of spatial resolutions. An iterative learning controller and model predictive controller have been implemented in VARIwise to improve the irrigation of cotton. The iterative learning control strategy involves using the soil moisture response to the previous irrigation volume to adjust the applied irrigation volume applied at the next irrigation event. For field implementation this controller has low data requirements as only soil moisture data is required after each irrigation event. In contrast, a model predictive controller has high data requirements as measured soil and plant data are required at a high spatial resolution in a field implementation. Model predictive control involves using a calibrated model to determine the irrigation application and/or timing which results in the highest predicted yield or water use efficiency. The implementation of these strategies is described and a case study is presented to demonstrate the operation of the strategies with various levels of data availability. It is concluded that in situations of sparse data, the iterative learning controller performs significantly better than a model predictive controller

Air pollution and livestock production

The air in a livestock farming environment contains high concentrations of dust particles and gaseous pollutants. The total inhalable dust can enter the nose and mouth during normal breathing and the thoracic dust can reach into the lungs. However, it is the respirable dust particles that can penetrate further into the gas-exchange region, making it the most hazardous dust component. Prolonged exposure to high concentrations of dust particles can lead to respiratory health issues for both livestock and farming staff. Ammonia, an example of a gaseous pollutant, is derived from the decomposition of nitrous compounds. Increased exposure to ammonia may also have an effect on the health of humans and livestock. There are a number of technologies available to ensure exposure to these pollutants is minimised. Through proactive means, (the optimal design and management of livestock buildings) air quality can be improved to reduce the likelihood of risks associated with sub-optimal air quality. Once air problems have taken hold, other reduction methods need to be applied utilising a more reactive approach. A key requirement for the control of concentration and exposure of airborne pollutants to an acceptable level is to be able to conduct real-time measurements of these pollutants. This paper provides a review of airborne pollution including methods to both measure and control the concentration of pollutants in livestock buildings

Conservation Agriculture and Scale of Appropriate Agricultural Mechanization in Smallholder Systems

This manual has focused on the need to amplify and accelerate adoption of conservation agriculture (CA) practices that enable productivity increases on a sustainable basis. The development of the training manual on ‘Conservation Agriculture and Scale Appropriate Agricultural Mechanization in Smallholder Systems’ is an outcome of the series of advanced training programs on Conservation Agriculture over past one decade. The objectives of this training manual are; (1) To foster capacity building of researchers, extension workers, farmers and machinery manufacturers to promote CA in Asia and Africa; and (2) To raise the awareness of policy planners and decision makers to develop a strategic plan for the development of CA and agricultural mechanization in the developing world. There are several initiatives in South Asia and Africa to promote CA practices as environment-friendly and alternative to conventional agriculture. However, little has been done to document the CA practices or even lessons learnt from these initiatives. Farmers today still lack access to information on CA practices. This is a comprehensive manual that explains in a step by step easy to follow manner on how to implement CA by smallholders in Asia and Africa. It explains what CA is, and why it is important, how to use CA principles in the field and highlights the issues and challenges that researchers, farmers, machinery manufacturers and service providers may encounter when they adopt and adapt CA practices. This manual aims to be a valuable reference and is intended for use by researchers, agricultural extension officers/workers, farmers, machinery manufacturers and service providers to promote CA in Asia and Africa for increasing productivity and reducing poverty. It is written in clear, easy-to-understand language, and is illustrated with numerous figures and tables. It is not intended to cover the subject of conservation agriculture comprehensively but to provide an overview of the principles and practices. Indeed, as the training draws from many distinct disciplines, it is unlikely that any one person will have the necessary technical skills to cover the complete course content. Manual also focuses on two crucial aspects: the provision of farm mechanization services as a viable business opportunity for entrepreneurs, and the essential criteria of raising productivity in an environmentally sensitive and responsible way. This manual is also designed to serve as source of information for custom hire service providers – whether already in the business or intending to start their own hire service business – with skills and competencies in both the technical and the management aspects of the small-scale mechanization business. CA to reach smallholder farmers needed the publication of simplified technical manual. This manual contains useful technical information on CA practices that offer practical answers to questions normally asked by farmers of what, why, how

Mosaic agriculture: a guide to irrigated crop and forage production in northern WA

The Bulletin is a comprehensive guide for pastoralists, agronomists, agribusiness and the broader community on the growing of irrigated crops and pastures within a rangeland pastoral setting. Dispersed irrigation developments on stations throughout the northern rangelands (sometimes referred to as mosaic agriculture) has created opportunities for the introduction of more productive forage species and pastoralists can now grow high quality forage for 12 months of the year. This can help to overcome the key constraint of traditional pastoral systems, the low quality of the feed over the dry season that typically results in stock losing condition.https://researchlibrary.agric.wa.gov.au/bulletins/1271/thumbnail.jp

Agroforestry Opportunities for Enhancing Resilience to Climate Change in Rainfed Areas,

Not AvailableAgroforestry provides a unique opportunity to achieve the objectives of enhancing the productivity and improving the soil quality. Tree systems can also play an important role towards adapting to the climate variability and important carbon sinks which helps to decrease the pressure on natural forests. Realizing the importance of the agroforestry in meeting the twin objectives of mitigation and adaptation to climate change as well as making rainfed agriculture more climate resilient, the ICAR-CRIDA has taken up the challenge in pursuance of National Agroforestry Policy 2014, in preparing a book on Agroforestry Opportunities for Enhancing Resilience to Climate Change in Rainfed Areas at ICAR-CRIDA to sharpen the skills of all stakeholders at national, state and district level in rainfed areas to increase agricultural productivity in response to climate changeNot Availabl

A rapid and low-cost novel biosensor for the detection of early-stage chronic kidney disease

There is an unmet medical need for the effective detection of early-stage kidney disease as many current techniques lack the accuracy to detect it early on. Therefore, most patients are diagnosed at a later phase when irreversible kidney damage has already been done. Blood tests typically detect serum creatinine however this can be unreliable and require laboratory and trained personnel. Within this thesis a metal oxide gas sensor has been developed to detect the volatile organic compound (VOC) trimethylamine (TMA), known to be elevated in early disease stages, via patients expired breath. Aerosol assisted chemical vapour deposition (AACVD) was chosen for its simplicity and ability to produce thin reproducible films without vacuum. Consequently molybdenum oxide (MoO3) thin films were successfully deposited by AACVD and used for the sensing of TMA. Films were further modified with cerium and gold to increase the sensitivity and performance of the sensors, and a variety of characterisation techniques were used such as scanning electron microscopy with coupled energy dispersive spectroscopy, X-ray diffraction and Fourier transform infrared spectroscopy to explore the crystallinity and properties of the optimised sensor films. The sensor was then evaluated successfully using simulated kidney disease patient breath in order to test its feasibility in practice. Finally, initial studies into the use of silicon carbide-tungsten core fibres were investigated as a potential for a next generation self-heating integrated substrate for molybdenum oxide sensors and the detection of TMA gas

Proceedings of the European Conference on Agricultural Engineering AgEng2021

This proceedings book results from the AgEng2021 Agricultural Engineering Conference under auspices of the European Society of Agricultural Engineers, held in an online format based on the University of Évora, Portugal, from 4 to 8 July 2021. This book contains the full papers of a selection of abstracts that were the base for the oral presentations and posters presented at the conference. Presentations were distributed in eleven thematic areas: Artificial Intelligence, data processing and management; Automation, robotics and sensor technology; Circular Economy; Education and Rural development; Energy and bioenergy; Integrated and sustainable Farming systems; New application technologies and mechanisation; Post-harvest technologies; Smart farming / Precision agriculture; Soil, land and water engineering; Sustainable production in Farm buildings