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AgriEngineering, Volume 3, Issue 1 (March 2021) – 9 articles

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Article
Numerical Study of the Drying of Cassava Roots Chips Using an Indirect Solar Dryer in Natural Convection
AgriEngineering 2021, 3(1), 138-157; https://0-doi-org.brum.beds.ac.uk/10.3390/agriengineering3010009 - 17 Mar 2021
Cited by 2 | Viewed by 1042
Abstract
In this work, an indirect solar dryer for drying cassava root chips was modelled and experimentally validated using the environmental conditions of Yaoundé in Cameroon and Yamoussoukro in Ivory Coast. The dryers were operational in natural convection mode. Resolution of the equations was [...] Read more.
In this work, an indirect solar dryer for drying cassava root chips was modelled and experimentally validated using the environmental conditions of Yaoundé in Cameroon and Yamoussoukro in Ivory Coast. The dryers were operational in natural convection mode. Resolution of the equations was achieved by finite differences and the 4th order of Runge–Kutta methods. A model was proposed for performing heat and mass transfer using thermophysical properties of cassava roots, and the obtained results were satisfactory for all conditions, with moisture content difference of less than 0.2 kg/kg between the experimental and theoretical results. The model showed that the core of the product takes more time to dry, which always prolongs the drying duration. The heat and mass transfer coefficients vary during the entire process of solar drying. The drying kinetics vary during the drying with values lower than 1.2 × 10−4 kg/(kg.s). The great gradients of humidity were observed in the thickness of the sample with a regular distribution of the temperature each drying time in the thickness of the sample. Full article
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Article
Sen2Grass: A Cloud-Based Solution to Generate Field-Specific Grassland Information Derived from Sentinel-2 Imagery
AgriEngineering 2021, 3(1), 118-137; https://0-doi-org.brum.beds.ac.uk/10.3390/agriengineering3010008 - 16 Mar 2021
Cited by 2 | Viewed by 976
Abstract
Grasslands are important for their ecological values and for agricultural activities such as livestock production worldwide. Efficient grassland management is vital to these values and activities, and remote sensing technologies are increasingly being used to characterize the spatiotemporal variation of grasslands to support [...] Read more.
Grasslands are important for their ecological values and for agricultural activities such as livestock production worldwide. Efficient grassland management is vital to these values and activities, and remote sensing technologies are increasingly being used to characterize the spatiotemporal variation of grasslands to support those management practices. For this study, Sentinel-2 satellite imagery was used as an input to develop an open-source and automated monitoring system (Sen2Grass) to gain field-specific grassland information on the national and regional level for any given time range as of January 2016. This system was implemented in a cloud-computing platform (StellaSpark Nexus) designed to process large geospatial data streams from a variety of sources and was tested for a number of parcels from the Haus Riswick experimental farm in Germany. Despite outliers due to fluctuating weather conditions, vegetation index time series suggested four distinct growing cycles per growing season. Established relationships between vegetation indices and grassland yield showed poor to moderate positive trends, implying that vegetation indices could be a potential predictor for grassland biomass and chlorophyll content. However, the inclusion of larger and additional datasets such as Sentinel-1 imagery could be beneficial to developing more robust prediction models and for automatic detection of mowing events for grasslands. Full article
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Article
Effect of Ploughing Techniques on Water Use and Yield of Rice in Maugo Small-Holder Irrigation Scheme, Kenya
AgriEngineering 2021, 3(1), 110-117; https://0-doi-org.brum.beds.ac.uk/10.3390/agriengineering3010007 - 03 Mar 2021
Cited by 13 | Viewed by 1185
Abstract
The objective of this study was to determine the effect of paddy rice ploughing techniques on water use and the yield of rice crop, as well as water use efficiency for rice growing in small-holder irrigation schemes. The study was conducted at a [...] Read more.
The objective of this study was to determine the effect of paddy rice ploughing techniques on water use and the yield of rice crop, as well as water use efficiency for rice growing in small-holder irrigation schemes. The study was conducted at a farmer’s field in Powo B sub-block of Maugo Irrigation Scheme. The period of study was from July 2019 to January 2020, which is the rice season. The experimental site was located in the vicinity of Olare Shopping Centre, Kamenya Sub-location, Kochia East Location, Kochia Ward, Rangwe Sub-County, Homa Bay County, Nyanza Region, Kenya in Maugo rice scheme in Kenya. In the study, four irrigation tillage practices were applied: ox-plough, conventional ox-plough, hand hoe and tractor ploughing. The results showed that conventional ox-ploughing consumed the highest amount of water at 1240 mm. The highest water use efficiency of 0.49 kg/m3 and highest yield of 5.7 tons/ha were observed for hand hoe ploughing. Use of the hand hoe ploughing technique increased yields by 20 percent, as compared to the conventional ox-ploughing. Therefore, the use of water for ploughing is not necessary in the study area. Future research will be needed to see how farmers are adopting the technology before scaling up to full mechanization, as partial mechanization was not profitable. Full article
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Article
Growth of Basil (Ocimum basilicum) in DRF, Raft, and Grow Pipes with Effluents of African Catfish (Clarias gariepinus) in Decoupled Aquaponics
AgriEngineering 2021, 3(1), 92-109; https://0-doi-org.brum.beds.ac.uk/10.3390/agriengineering3010006 - 26 Feb 2021
Cited by 1 | Viewed by 892
Abstract
Basil (Ocimum basilicum) was cultivated in Rostock, Northern Germany, in a decoupled aquaponic system with African catfish (Clarias gariepinus) under intensive rearing conditions by using three hydroponic components, the dynamic root floating technique (DRF), the raft technique, and grow [...] Read more.
Basil (Ocimum basilicum) was cultivated in Rostock, Northern Germany, in a decoupled aquaponic system with African catfish (Clarias gariepinus) under intensive rearing conditions by using three hydroponic components, the dynamic root floating technique (DRF), the raft technique, and grow pipes. A 25% of the recommended feed input still allowed African catfish growth and provided adequate nitrogen and calcium levels in the process water. After 36 days, the plants were examined with respect to 16 different growth parameters. DRF performed significantly better than raft and/or grow pipes in 11 parameters. Total weight of basil was significantly higher in DRF (107.70 ± 34.03 g) compared with raft (82.02 ± 22.74 g) and grow pipes (77.86 ± 23.93 g). The economically important leaf biomass was significantly higher in wet and dry weight under DRF cultivation (45.36 ± 13.53 g; 4.96 ± 1.57 g) compared with raft (34.94 ± 9.44 g; 3.74 ± 1.04 g) and grow pipes (32.74 ± 9.84 g; 3.75 ± 1.22 g). Two main factors limited plant growth: an unbalanced nutrient concentration ratio and high water temperatures with an average of 28 °C (max 34.4 °C), which resulted in reduced root activity in raft and grow pipes. DRF was able to maintain root activity through the 5 cm air space between the shoots and the nutrient solution and thus produced significantly more biomass. This suggests DRF to be used for basil aquaponics under glass house conditions with high-temperature scenarios. Future studies are needed to optimize nutrient loads and examine systems with the plant roots exposed to air (Aeroponics). Full article
(This article belongs to the Special Issue Aquaponics: Advancing Food Production Systems for the World)
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Article
Near-Infrared Spectroscopy (NIRS) and Optical Sensors for Estimating Protein and Fiber in Dryland Mediterranean Pastures
AgriEngineering 2021, 3(1), 73-91; https://0-doi-org.brum.beds.ac.uk/10.3390/agriengineering3010005 - 17 Feb 2021
Cited by 1 | Viewed by 1392
Abstract
Dryland pastures provide the basis for animal sustenance in extensive production systems in Iberian Peninsula. These systems have temporal and spatial variability of pasture quality resulting from the diversity of soil fertility and pasture floristic composition, the interaction with trees, animal grazing, and [...] Read more.
Dryland pastures provide the basis for animal sustenance in extensive production systems in Iberian Peninsula. These systems have temporal and spatial variability of pasture quality resulting from the diversity of soil fertility and pasture floristic composition, the interaction with trees, animal grazing, and a Mediterranean climate characterized by accentuated seasonality and interannual irregularity. Grazing management decisions are dependent on assessing pasture availability and quality. Conventional analytical determination of crude protein (CP) and fiber (neutral detergent fiber, NDF) by reference laboratory methods require laborious and expensive procedures and, thus, do not meet the needs of the current animal production systems. The aim of this study was to evaluate two alternative approaches to estimate pasture CP and NDF, namely one based on near-infrared spectroscopy (NIRS) combined with multivariate data analysis and the other based on the Normalized Difference Vegetation Index (NDVI) measured in the field by a proximal active optical sensor (AOS). A total of 232 pasture samples were collected from January to June 2020 in eight fields. Of these, 96 samples were processed in fresh form using NIRS. All 232 samples were dried and subjected to reference laboratory and NIRS analysis. For NIRS, fresh and dry samples were split in two sets: a calibration set with half of the samples and an external validation set with the remaining half of the samples. The results of this study showed significant correlation between NIRS calibration models and reference methods for quantifying pasture quality parameters, with greater accuracy in dry samples (R2 = 0.936 and RPD = 4.01 for CP and R2 = 0.914 and RPD = 3.48 for NDF) than fresh samples (R2 = 0.702 and RPD = 1.88 for CP and R2 = 0.720 and RPD = 2.38 for NDF). The NDVI measured by the AOS shows a similar coefficient of determination to the NIRS approach with pasture fresh samples (R2 = 0.707 for CP and R2 = 0.648 for NDF). The results demonstrate the potential of these technologies for estimating CP and NDF in pastures, which can facilitate the farm manager’s decision making in terms of the dynamic management of animal grazing and supplementation needs. Full article
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Article
Design and Experimental Study of a Wine Grape Covering Soil-Cleaning Machine with Wind Blowing
AgriEngineering 2021, 3(1), 50-72; https://0-doi-org.brum.beds.ac.uk/10.3390/agriengineering3010004 - 04 Feb 2021
Viewed by 1079
Abstract
Due to the cold and dry climate during the winter season of Central Asia, in order to prevent frostbite and vines drying out for wine grapes, the common methods are burying the vines in winter under a thick layer of soil and then [...] Read more.
Due to the cold and dry climate during the winter season of Central Asia, in order to prevent frostbite and vines drying out for wine grapes, the common methods are burying the vines in winter under a thick layer of soil and then cleaning them out in the next spring. The design of existing vine digging machinery is not precise enough and can only remove the outer layer of the soil on both sides and the top. It cannot clean the soil from the central area of the buried vine. Sometimes, the branches and buds get damaged due to uneven driving condition. To solve the problem, an innovative non-contact blower was designed and tested to clean the vine. In this paper, the design specifications and operation parameters of the blower were determined according to the agronomic properties of the grapevines. Fluent-EDEM coupling, that is, with the help of Engineering discrete element method (EDEM) and CFD fluid simulation software Fluent, was the most common method for dynamic simulation of gas-solid two-phase flow. The Fluent-EDEM coupling simulation was used to simulate the dynamics of soil particles under the action of different wind speeds and blowing patterns, with the goal of a high soil cleaning rate. A prototype of the soil cleaning blower was manufactured and tested at the vineyards of Ningxia Yuquanying Farm in China. The results showed that the blower had an operation efficiency of 4669 mh−1, with an average soil removal rate of 80%. The efficiency of covering soil cleaning and rattan raising was greatly improved, and the damage rate of the vines, branches and the buds was greatly reduced. Full article
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Article
Mapping Wheat Dry Matter and Nitrogen Content Dynamics and Estimation of Wheat Yield Using UAV Multispectral Imagery Machine Learning and a Variety-Based Approach: Case Study of Morocco
AgriEngineering 2021, 3(1), 29-49; https://0-doi-org.brum.beds.ac.uk/10.3390/agriengineering3010003 - 28 Jan 2021
Cited by 2 | Viewed by 1554
Abstract
Our work aims to monitor wheat crop using a variety-based approach by taking into consideration four different phenological stages of wheat crop development. In addition to highlighting the contribution of Red-Edge vegetation indices in mapping wheat dry matter and nitrogen content dynamics, as [...] Read more.
Our work aims to monitor wheat crop using a variety-based approach by taking into consideration four different phenological stages of wheat crop development. In addition to highlighting the contribution of Red-Edge vegetation indices in mapping wheat dry matter and nitrogen content dynamics, as well as using Random Forest regressor in the estimation of wheat yield, dry matter and nitrogen uptake relying on UAV (Unmanned Aerial Vehicle) multispectral imagery. The study was conducted on an experimental platform with 12 wheat varieties located in Sidi Slimane (Morocco). Several flight missions were conducted using eBee UAV with MultiSpec4C camera according to phenological growth stages of wheat. The proposed methodology is subdivided into two approaches, the first aims to find the most suitable vegetation index for wheat’s biophysical parameters estimation and the second to establish a global model regardless of the varieties to estimate the biophysical parameters of wheat: Dry matter and nitrogen uptake. The two approaches were conducted according to six main steps: (1) UAV flight missions and in-situ data acquisition during four phenological stages of wheat development, (2) Processing of UAV multispectral images which enabled us to elaborate the vegetation indices maps (RTVI, MTVI2, NDVI, NDRE, GNDVI, GNDRE, SR-RE et SR-NIR), (3) Automatic extraction of plots by Object-based image analysis approach and creating a spatial database combining the spectral information and wheat’s biophysical parameters, (4) Monitoring wheat growth by generating dry biomass and wheat’s nitrogen uptake model using exponential, polynomial and linear regression for each variety this step resumes the varietal approach, (5) Engendering a global model employing both linear regression and Random Forest technique, (6) Wheat yield estimation. The proposed method has allowed to predict from 1 up to 21% difference between actual and estimated yield when using both RTVI index and Random Forest technique as well as mapping wheat’s dry biomass and nitrogen uptake along with the nitrogen nutrition index (NNI) and therefore facilitate a careful monitoring of the health and the growth of wheat crop. Nevertheless, some wheat varieties have shown a significant difference in yield between 2.6 and 3.3 t/ha. Full article
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Article
Simulation and Evaluation of Heat Transfer Inside a Diseased Citrus Tree during Heat Treatment
AgriEngineering 2021, 3(1), 19-28; https://0-doi-org.brum.beds.ac.uk/10.3390/agriengineering3010002 - 13 Jan 2021
Viewed by 1462
Abstract
Heat treatment has been applied in previous studies to treat diseased plants and trees affected by heat-sensitive pathogens. Huanglongbing (HLB) is a heat-sensitive pathogen and the optimal temperature–time for treating HLB-affected citrus trees was estimated to be 54 °C for 60 to 120 [...] Read more.
Heat treatment has been applied in previous studies to treat diseased plants and trees affected by heat-sensitive pathogens. Huanglongbing (HLB) is a heat-sensitive pathogen and the optimal temperature–time for treating HLB-affected citrus trees was estimated to be 54 °C for 60 to 120 s from indoor experimental studies. However, utilizing this method in orchards is difficult due to technical difficulties to effectively apply heat. Recently, a mobile thermotherapy system (MTS) was developed to in-field treat HLB-affected trees. This mobile device includes a canopy cover that covers the diseased tree and a system to supply steam under the cover to treat the tree. It was proven that the temperature inside the canopy cover can reach the desired one (i.e., 54 °C) to kill bacteria. However, for HLB, the heat should penetrate the tree’s phloem where the bacteria live. Therefore, measuring the heat penetration inside the tree is very critical to evaluate the performance of the MTS. In this study, a heat transfer model was developed to simulate the heat penetration inside the tree and predict the temperature in the phloem of the diseased tree during the in-field heat treatment. The simulation results were compared with in-field experimental measurements. The heat transfer model was developed by a comparative analysis of the experimental data using the ANSYS software. Results showed that the temperature in the phloem was 10–40% lower than the temperature near the surface of the bark. Simulation results were consistent with experimental results, with an average relative error of less than 5%. Full article
(This article belongs to the Special Issue Evaluation of New Technological Solutions in Agriculture)
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Article
Definition and Application of a Computational Parameter for the Quantitative Production of Hydroponic Tomatoes Based on Artificial Neural Networks and Digital Image Processing
AgriEngineering 2021, 3(1), 1-18; https://0-doi-org.brum.beds.ac.uk/10.3390/agriengineering3010001 - 04 Jan 2021
Cited by 1 | Viewed by 1362
Abstract
This work presents an alternative method, referred to as Productivity Index or PI, to quantify the production of hydroponic tomatoes using computer vision and neural networks, in contrast to other well-known metrics, such as weight and count. This new method also allows the [...] Read more.
This work presents an alternative method, referred to as Productivity Index or PI, to quantify the production of hydroponic tomatoes using computer vision and neural networks, in contrast to other well-known metrics, such as weight and count. This new method also allows the automation of processes, such as tracking of tomato growth and quality control. To compute the PI, a series of computational processes are conducted to calculate the total pixel area of the displayed tomatoes and obtain a quantitative indicator of hydroponic crop production. Using the PI, it was possible to identify objects belonging to hydroponic tomatoes with an error rate of 1.07%. After the neural networks were trained, the PI was applied to a full crop season of hydroponic tomatoes to show the potential of the PI to monitor the growth and maturation of tomatoes using different dosages of nutrients. With the help of the PI, it was observed that a nutrient dosage diluted with 50% water shows no difference in yield when compared with the use of the same nutrient with no dilution. Full article
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