AgriEngineering, Volume 3, Issue 4 (December 2021) – 17 articles

Broiler meat is one of the most consumed meats worldwide. The broiler production system poses several challenges for the producer, including maintaining environmental conditions for rearing. The popularization of mobile devices (smartphones) among people, including those with lower incomes, makes it possible for specialist systems to be developed and used for diverse purposes through Apps (mobile application). The present study proposed the development of a mobile application to help farmers follow up on-farm flock management. We retrieved rearing environment and flock data from commercial broiler farms that complied with broiler-producing standards and followed the breeders’ recommendations. Data were organized and normalized to serve as the basis for the software. We specified a performance index based on the average environment and flock-based data. The language used for the application development was Python compatible with the GNU GPL (General Public License), which has a vast library of ready-made functions. For the graphical interface, we selected Kivy and KivyMD framework. The developed mobile application might help farmers evaluate broiler rearing conditions on-farm during the flock’s growth and grade the flock using a performance index. Full article

Crop planting area and spatial distribution information have important practical significance for food security, global change, and sustainable agricultural development. How to efficiently and accurately identify crops in a timely manner by remote sensing in order to determine the crop planting area and its temporal–spatial dynamic change information is a core issue of monitoring crop growth and estimating regional crop yields. Based on hundreds of relevant documents from the past 25 years, in this paper, we summarize research progress in relation to farmland vegetation identification and classification by remote sensing. The classification and identification of farmland vegetation includes classification based on vegetation index, spectral bands, multi-source data fusion, artificial intelligence learning, and drone remote sensing. Representative studies of remote sensing methods are collated, the main content of each technology is summarized, and the advantages and disadvantages of each method are analyzed. Current problems related to crop remote sensing identification are then identified and future development directions are proposed. Full article

This review presents the state-of-the-art research on IoT systems for optimized greenhouse environments. The data were analyzed using descriptive and statistical methods to infer relationships between the Internet of Things (IoT), emerging technologies, precision agriculture, agriculture 4.0, and improvements in commercial farming. The discussion is situated in the broader context of IoT in mitigating the adverse effects of climate change and global warming in agriculture through the optimization of critical parameters such as temperature and humidity, intelligent data acquisition, rule-based control, and resolving the barriers to the commercial adoption of IoT systems in agriculture. The recent unexpected and severe weather events have contributed to low agricultural yields and losses; this is a challenge that can be resolved through technology-mediated precision agriculture. Advances in technology have over time contributed to the development of sensors for frost prevention, remote crop monitoring, fire hazard prevention, precise control of nutrients in soilless greenhouse cultivation, power autonomy through the use of solar energy, and intelligent feeding, shading, and lighting control to improve yields and reduce operational costs. However, particular challenges abound, including the limited uptake of smart technologies in commercial agriculture, price, and accuracy of the sensors. The barriers and challenges should help guide future Research & Development projects and commercial applications. Full article

Restrictions on soil water supply can dramatically reduce crop yields by affecting the growth and development of plants. For this reason, screening tools that can detect crop water stress early have been long investigated, with canopy temperature (CT) being widely used for this purpose. In this study, we investigated the relationship between canopy temperature retrieved from unmanned aerial vehicles (UAV) based thermal imagery with soil and plant attributes, using a rainfed maize field as the area of study. The flight mission was conducted during the late vegetative stage and at solar noon, when a considerable soil water deficit was detected according to the soil water balance model used. While the images were being taken, soil sampling was conducted to determine the soil water content across the field. The sampling results demonstrated the spatial variability of soil water status, with soil volumetric water content (SVWC) presenting 10.4% of variation and values close to the permanent wilting point (PWP), reflecting CT readings that ranged from 32.8 to 40.6 °C among the sampling locations. Although CT correlated well with many of the physical attributes of soil that are related to water dynamics, the simple linear regression between CT and soil water content variables yielded coefficients of determination (R²) = 0.42, indicating that CT alone might not be sufficient to predict soil water status. Nonetheless, when CT was combined with some soil physical attributes in a multiple linear regression, the prediction capacity was significantly increased, achieving an R² value = 0.88. This result indicates the potential use of CT along with certain soil physical variables to predict crop water status, making it a useful tool for studies exploring the spatial variability of in-season drought stress. Full article

Crown rot disease is caused by Fusarium pseudograminearum and is one of the major stubble-soil fungal diseases threatening the cereal industry globally. It causes failure of grain establishment, which brings significant yield loss. Screening crops affected by crown rot is one of the key tools to manage crown rot, because it is necessary to understand disease infection conditions, identify the severity of infection, and discover potential resistant varieties. However, screening crown rot is challenging as there are no clear visible symptoms on leaves at early growth stages. Hyperspectral imaging (HSI) technologies have been successfully used to better understand plant health and disease incidence, including light absorption rate, water and nutrient distribution, and disease classification. This suggests HSI imaging technologies may be used to detect crown rot at early growing stages, however, related studies are limited. This paper briefly describes the symptoms of crown rot disease and traditional screening methods with their limitations. It, then, reviews state-of-art imaging technologies for disease detection, from color imaging to hyperspectral imaging. In particular, this paper highlights the suitability of hyperspectral-based screening methods for crown rot disease. A hypothesis is presented that HSI can detect crown-rot-infected plants before clearly visible symptoms on leaves by sensing the changes of photosynthesis, water, and nutrients contents of plants. In addition, it describes our initial experiment to support the hypothesis and further research directions are described. Full article

Plastic contamination in US lint bales has increased with the adoption of new cotton harvesters that form cylindrical or round modules on the machine. It is of significant interest to the US cotton industry to reduce this contamination to preserve grower profitability and the reputation of the US as a reliable source of clean cotton fiber. The objective of this work is to describe the design and operation of a system for use on cotton gin module feeders that provides monitoring of plastic accumulation on the dispersing cylinders and video data to help document the module wrap condition and unloading/unwrapping procedures that may have caused the potential contamination event on the dispersing cylinders. In 2020, an integrated plastic contamination monitoring system was installed on module feeders at two commercial cotton gins in Texas. The system is comprised of sub-systems that provide images of plastic accumulation on the dispersing cylinders, a log of the processing sequence for round modules, video data of the unloading/unwrapping process for each module and a software program that integrates the data from the two sub-systems. The system was developed to operate on one computer, store the data in a common location, and simplify the process of extracting module specific data for a given event when plastic accumulates on the module feeder dispersing cylinders. The data provided by the system can be useful to manufacturers in comparing performance among module wrap products as well as to gin managers in training gin employees on module handling procedures to mitigate plastic contamination and improve worker safety. Full article

The Manila Clam is an important economic shellfish in China’s seafood industry. In order to improve the design of juvenile Manila Clam seeding equipment, a juvenile clam discrete element method (DEM) particle shape was established, which is based on 3D scanning and EDEM software. The DEM contact parameters of clam-stainless steel, and clam-acrylic were calibrated by combining direct measurements and test simulations (slope sliding and dropping). Then, clam DEM simulation and realistic seeding tests were carried out on a seeding wheel at different rotational speeds. The accuracy of the calibrated clam DEM model was evaluated in a clam seeding verification test by comparing the average error of the variation coefficient between the realistic and simulated seeding tests. The results showed that: (a) the static friction coefficients of clam-acrylic and clam-stainless steel were 0.31 and 0.23, respectively; (b) the restitution coefficients of clam-clam, clam-acrylic, and clam-stainless steel were 0.32, 0.48, and 0.32, respectively. Furthermore, the results of the static repose angle from response surface tests showed that when the contact wall was acrylic, the coefficient rolling friction and static friction of clam-clam were 0.17 and 1.12, respectively, and the coefficient rolling friction of clam-acrylic was 0.20. When the contact wall was formed of stainless steel, the coefficient rolling friction and static friction of clam-clam were 0.33 and 1.25, respectively, and the coefficient rolling friction of clam-stainless steel was 0.20. The results of the verification test showed that the average error between the realistic and simulated value was <5.00%. Following up from these results, the clam DEM model was applied in a clam seeding simulation. Full article

In this work, the production of a novel and sustainable silage was realized and optimized. Three agro-industrial wastes produced in bulk: olive mill wastewater (OMWW), grape pomace (GP) and de-proteinized feta cheese whey (DFCW) were mixed with coarsely ground maize grains, and the mixture was inoculated with commercial lactic bacteria starter culture and fermented for 30 days under anaerobic conditions to obtain silage. Sixty-seven recipes with varying compositions of the three agro-wastes were ensilaged, and four silage quality indices: pH value, % acidity as lactic acid, total lactobacillus count (cfu/g) and total yeast and mold count (cfu/g) were monitored throughout the ensilage process, and the obtained data were used to perform multicriteria optimization of the silage composition. The optimization target was to simultaneously maximize the pH drop, % total acidity as lactic acid and lactobacillus count while minimizing the count of undesirable yeasts and molds. Following this optimization strategy, it was found that the best composition of the mixture of all three tested agro-industrial wastes to obtain a high-quality silage was the one containing: 20% w/w GP, 60% w/w OMWW and 20% w/w feta cheese whey. Finally, the produced silage was tested in broilers’ nutrition and by 10% w/w inclusion in the feed, which led to the production of high added-value bioactive meat rich in ω-3 fatty acids and with high antioxidant capacity. Full article

The Internet of Things asserts that several applications, such as smart cities or intelligent agriculture, can be based on various embedded systems programmed to do different tasks, by transferring data over a network from sensors to a server, where the information is stored and treated, supporting the decision-making process. In this context, LoRaWAN is an accurate network topology based on a wireless technology called LoRa that is capable of transmitting small data rates at a long range, using low-powered devices, making it ideal for the acquisition of climate variables, such as temperature and relative humidity. Applying this architecture to agriculture buildings can be very useful to guarantee indoor thermal comfort conditions. In this study, this technology is applied to a passive solar system composed by a high thermal inertia wall, defined as Trombe wall, with air vents provided in the massive wall to improve heat transfer by air convection, and an external shading device to avoid overheating during summer and heat losses during winter. It is intended to analyze the possibility to control the interiortemperature of a poultry brooding house given that, in the early stages of life, chickens need accurate climate conditions in order to enhance their growth and reduce their mortality rate. In brief, temperature values acquired by different sensors placed on the Trombe wall travel through a LoRaWAN wireless network and are received by an application that controls the actuators, in this case, the opening and closing of the Trombe wall air vents, while the external shading device is controlled locally. Full article

One of the challenges in the future of food production, amidst increasing population and decreasing resources, is developing a sustainable food production system. It is anticipated that robotics will play a significant role in maintaining the food production system, specifically in labor-intensive operations. Therefore, the main goal of this project is to develop a robotic fruit harvesting system, initially focused on the harvesting of apples. The robotic harvesting system is composed of a six-degrees-of-freedom (DOF) robotic manipulator, a two-fingered gripper, a color camera, a depth sensor, and a personal computer. This paper details the development and performance of a visual servo system that can be used for fruit harvesting. Initial test evaluations were conducted in an indoor laboratory using plastic fruit and artificial trees. Subsequently, the system was tested outdoors in a commercial fruit orchard. Evaluation parameters included fruit detection performance, response time of the visual servo, and physical time to harvest a fruit. Results of the evaluation showed that the developed visual servo system has the potential to guide the robot for fruit harvesting. Full article

The loss of fresh fruits after harvesting is not new since it has constantly been a challenge for humankind. The growing population in developing countries, where food shortages exist, require serious food security measures to address hunger and malnutrition. Present research focused on the development, fabrication and testing of mango pulp extractor to assist small-scale fruit farmers in the countryside with a view to minimizing fruit spoilage. The unit, whose major material was food grade stainless steel (SS-304), consists of major components such as teflon brushes mounted shaft, motor, main frame, hopper, extraction compartment, pulp outlet, fruit residue outlet, perforated sieve and bearings. After construction, the machine was tested at three feed rate (2.0, 2.5, 3.0 kg/min) and extraction speed levels (500, 900 and 1400 rpm). Each of these factors was replicated three times, which resulted into 3 × 3 × 3 factorial experimental design. The optimum operating parameters for maximum pulp yield, maximum extraction efficiency and minimum extraction losses were determined. The physicochemical analysis of the extracted pulp was also carried out. Results revealed a maximum pulp yield of 77.9%, highest extraction efficiency of 96.03% and highest extraction loss of 9.3%. The mango pulp extraction machine was found to be affordable, easy to operate and maintain. The breakeven point of the machine was found to be 40 h if the machine is operated at its peak capacity. Therefore, it is recommended for small-scale farmers and for cottage industry. Full article

Coffee is a crop of great relevance in socioeconomic terms for Brazilian agribusiness, which is the world’s largest producer in cultivated areas. The implementation of precision agriculture in the coffee culture has provided countless benefits to its development, which over the years has been cultivated in the same area. However, there is a lack of studies that address the impact of the application of variable-rates inputs in soil on the energy efficiency and sustainability of these systems. This study aimed to analyze how variable-rate fertilization influences energy efficiency in coffee growing. A production area subjected to variable and fixed rates of fertilizer in alternating rows was evaluated. Geo-referenced yield data was collected to assess yield response for fixed and variable rate applications. The energy assessment was combined with the Geographic Information System (GIS) to determine site-specific energy indicators. To determine the energy flow, only NPK fertilizer applications were considered as inputs and the yield as output. The results obtained indicated that the variable rate fertilizer application has a small difference, indicating greater energy efficiency concerning the applied fertilizer and coffee production per crop season. It was observed in the 06/07 crop, the incorporated energy was 10.7 MJ kg⁻¹ for VR and 10.2 MJ kg⁻¹ for UR and for the 07/08 crop it was 30.7 MJ kg⁻¹ for VR and 34.9 MJ kg⁻¹ for UR. The energy balance was more efficient at variable rates, as it provided fertilizer savings without compromising yield. However, the difference between the embodied energy per mass of coffee produced was very small compared to the fixed rate. Full article

Aimed at issues associated with the poor air supply and poor automatic targeting accuracy of existing orchard sprayers, this paper designs a jet-type orchard remote control sprayer with automatic targeting which is suitable for standardized orchards in hilly and mountainous areas. By optimizing the structure of the diversion box, the uniformity of deposition and penetration ability of the pesticide droplets to the fruit tree canopy are improved, and a uniform wild field distribution is realized simultaneously. An accurate positioning of the fruit tree canopy space orientation is achieved through automatic targeting and azimuthal adjustment systems. When the target is detected, the solenoid valve is controlled to open, and vice versa, and the distance from the nozzle to the fruit tree canopy is adjusted in real time to improve the utilization rate of pesticides. The test results show that the effective range of the jet-type orchard remote control sprayer is no more than 3.5 m, and the maximum flow rate range is 6~6.5 L/min. Within the effective spraying range, the farther the distance is, the higher the automatic targeting accuracy. The pesticide droplets sprayed by the spraying machine have a certain penetration ability, and the uniformity of the droplets is good, which solves solidification problems caused by the penetration of pesticide into the soil. This research provides a reference for jet spraying operation and automatic targeting spraying structure design. Full article

Collecting real-time data on physical and chemical parameters of the soil is a prerequisite for resource-efficient and environmentally sustainable agriculture. For continuous in situ measurement of soil nutrients such as nitrate or phosphate, a lab-on-chip approach combined with wireless remote readout is promising. For this purpose, the soil solution, i.e., the water in the soil with nutrients, needs to be extracted into a microfluidic chip. Here, we present a soil-solution extraction unit based on combining a porous ceramic filter with a microfluidic channel with a 12 µL volume. The microfluidic chip was fabricated from polydimethylsiloxane, had a size of 1.7 cm × 1.7 cm × 0.6 cm, and was bonded to a glass substrate. A hydrophilic aluminum oxide ceramic with approximately 37 Vol.-% porosity and an average pore size of 1 µm was integrated at the inlet. Soil water was extracted successfully from three types of soil—silt, garden soil, and sand—by creating suction with a pump at the other end of the microfluidic channel. For garden soil, the extraction rate at approximately 15 Vol.-% soil moisture was 1.4 µL/min. The amount of extracted water was investigated for 30 min pump intervals for the three soil types at different moisture levels. For garden soil and sand, water extraction started at around 10 Vol.-% soil moisture. Silt showed the highest water-holding capacity, with water extraction starting at approximately 13 Vol.-%. Full article

High piglet pre-weaning mortality rates can be attributed to poor creep area microclimate resulting in negative productivity, welfare, and economic consequences. A piglet mechanistic steady-state thermal balance model was developed using previous models and expanded to assess (a) thermal interactions of multiple pigs and (b) conduction heat transfer. The piglet Effective Environment Temperature (EET) equation was also modified to incorporate piglet age (day 0 to 30) and a conduction heat transfer term. Model parameters were validated with empirical data consisting of the thermal component (dry-bulb temperature, T_db; mean radiant temperature, T_MR; airspeed, U; mat underside temperature, T_m) of the microclimate and dimension data of the piglets (i.e., body weight, length, height, width, and calculated surface area). Model results demonstrate that the common microclimate supplemental heat sources (heat mats and heat lamps; HL) can meet the needs of the piglets. The new EET was more consistent for a novel semi-enclosed heated microclimate (SEHM) in comparison to the HL. This demonstrates the benefit of precision technologies over manually adjusted supplemental heat sources. The experimental data and model results suggest further development of an ideal thermal index for piglet microclimates needs to account for variations of piglet health and body condition to be more applicable in industry. Full article

Conventional farming necessitates a large number of resources and infrastructure such as land, irrigation, manpower to manage farms, etc. Modern initiatives are required to automate conventional farms. Smart indoor farms offer the potential to remedy the shortfalls of conventional farms by providing a controlled, intelligent, and smart environment. This paper presents a three-dimensional perspective consisting of soilless farming, energy harvesting, and smart technologies, which could be considered as the three important characteristics of smart indoor farms. A six-layer smart indoor farms architecture has also been proposed, which explains how data are collected using various sensors and devices and then transmitted onto the cloud infrastructure for further analysis and control through various layers. Artificial lighting, smart nutrition management, and artificial climate control, to name a few, are some of the important requirements for smart indoor farms while considering control and service management factors. The major bottleneck in installing such systems is both the economical and the technical constraints. However, with the evolution of technology (and when they become widely available in the near future), a more favourable farming scenario may emerge. Furthermore, smart indoor farms could be viewed as a potential answer for meeting the demands of a sustainable agricultural revolution as we move closer to Agriculture 4.0. Finally, in order to adapt smart indoor farms and their study scope, our work has presented various research areas to potential researchers. Full article

Recent advances in light emitting diode (LED) technology have provided exciting opportunities for plant lighting applications, and it is expected that LED lighting will soon overtake the still common use of high-intensity discharge (HID) lighting technology. Because LED lighting offers novel capabilities, extensive research is needed to identify optimal lighting practices for the large number of crops grown by commercial greenhouse growers. Plant scientists and growers facing decisions about plant lighting systems do not always have sufficient information about lamp performance characteristics. In this paper, we reported on various technical performance characteristics for 18 lamp types commonly used for plant production, and compared these characteristics with the characteristics of sunlight. The results showed a substantial range of performance characteristics, highlighting the importance of a careful assessment before selecting a light source for horticultural applications. The data presented in this paper can be used to assess the suitability of a specific light source for a particular horticultural application. Full article