AgriEngineering, Volume 1, Issue 3 (September 2019) – 10 articles

This concept paper outlines a conceptual framework for the design and development of user-integrated semi-autonomous lawn mowing systems. This is approached from a systems engineering perspective, considering both hardware and software elements and integration with the user. This is an important and emerging field of study within the several engineering communities, including robotics, agricultural engineering, smart city development, and general systems engineering. In several sections of this paper, a review of current progress on this problem is presented (both in general and related to specific aspects of the system), followed by a discussion of the problem from a systems engineering perspective, a general system architecture developed by the authors, a preliminary set of design requirements, and a discussion of some practical implementation strategies. This work is meant to provide a baseline and motivation for the further development and refinement of these systems within the agricultural engineering and robotics communities and is relevant to both academic and commercial research. Full article

Strawberry is an important fruit crop in Canada but powdery mildew (PM) results in about 30–70% yield loss. Detection of PM through an image texture-based system is beneficial, as it identifies the symptoms at an earlier stage and reduces labour intensive manual monitoring of crop fields. This paper presents an image texture-based disease detection algorithm using supervised classifiers. Three sites were selected to collect the leaf image data in Great Village, Nova Scotia, Canada. Images were taken under an artificial cloud condition with a Digital Single Lens Reflex (DSLR) camera as red-green-blue (RGB) raw data throughout 2017–2018 summer. Three supervised classifiers, including artificial neural networks (ANN), support vector machine (SVM), and k-nearest neighbors (kNN) were evaluated for disease detection. A total of 40 textural features were extracted using a colour co-occurrence matrix (CCM). The collected feature data were normalized, then used for training and internal, external and cross-validations of developed classifiers. Results of this study revealed that the highest overall classification accuracy was 93.81% using the ANN classifier and lowest overall accuracy was 78.80% using the kNN classifier. Results identified the ANN classifier disease detection having a lower Root Mean Square Error (RMSE) = 0.004 and Mean Absolute Error (MAE) = 0.003 values with 99.99% of accuracy during internal validation and 87.41%, 88.95% and 95.04% of accuracies during external validations with three different fields. Overall results demonstrated that an image texture-based ANN classifier was able to classify PM disease more accurately at early stages of disease development. Full article

The global agriculture sector faces many challenges in its mission to meet the increasing demand for food and fiber. Climate change, increasing population growth, emergence of crop diseases, damage to crops from rodents and critters, and shrinking farming land in some regions are among these challenges. Application of agrochemicals has proven to be an efficient answer to some of these challenges. However, the impacts of these products on human health and the environment combined with the increased requirement for sustainable farming requires the development of optimal spraying practices that would balance out all interests and concerns. In this paper, a mathematical model is developed to jointly minimize spraying time and drift losses. The obtained bi-objective mixed integer nonlinear programming model is solved for a case study example published in the crop protection literature. Optimal solutions are obtained using the weighted sum method and the epsilon-constraint approach. The results showed that valid and reasonable solutions can be obtained by selecting the appropriate combination of boom height, nozzle spacing, nozzle type, and tractor travel speed. Useful insights are obtained through various computational experiments. Full article

The investigation presented herein had as its scope the development of an integrated process for the efficient extraction of polyphenols from hop. For this purpose, a novel, natural deep eutectic solvent (DES) was synthesised, composed of glycerol and L-alanine, and the process was optimised by deploying a response surface methodology based on a Box–Behnken design. The variables considered were the DES/water proportion, the liquid-to-solid ratio and the stirring speed. Under the optimised conditions, the yield in total polyphenols achieved was 118.97 ± 8.27 mg gallic acid equivalents per g of dry mass. Ultrasonication, incorporated into the process as a pretreatment step, was shown to significantly change the kinetic pattern of polyphenol extraction and contributed to attaining higher yields only at 80 °C, whereas at lower temperatures a supressing effect was observed. Furthermore, increasing temperature was negatively correlated with the second-order extraction rates, evidencing a slow-down of the extraction rate at elevated temperatures. Full article

Boosting innovation and research in the agricultural sector is crucial if farmers are asked to produce more with less. Precision agriculture offers different solutions to assist farmers in improving efficiency and reducing labor costs while respecting the legal requirements. Precision spraying enables the treatment of only the plants that require it, with the right amount of products. Our research group has developed a solution based on a reconfigurable vehicle with a high degree of automation for the distribution of plant protection products in vineyards and greenhouses. The synergy between the vehicle and the spraying management system we developed is an innovative solution with high technological content, and attempts to account for the current European and global directives in the field of agricultural techniques. The objectives of our system are the development of an autonomous vehicle and a spraying management system that allows safe and accurate autonomous spraying operations. Full article

Drip-irrigation can improve uniformity in water distribution, water use efficiency, and crop productivity in the saline and nonsaline regions of South Asia and in Bangladesh where the availability and quality of water resources are scare for sustainable crop production. However, the currently available drip-irrigation systems (DIS) have limitations especially in the design and field performance of emitters. A new type of emitter with low pressure (gravity) was developed, installed and evaluated using the locally produced materials in two locations (nonsaline and saline zones) of Bangladesh. The emitter discharge rate was measured for the variable operating heads of 1.5, 2, and 2.5 meter (m) with 0%, 1%, and 1.5% slopes with eggplant (Solanum melongena L.), a commonly grown vegetable in the region. The tested parameters of the emitter were manufacturer coefficient of variation (CV_m), emission uniformity (EU), coefficient of uniformity (CU), and the statistical uniformity (Us) of water application. Our results reveal that the discharge rates of the emitter varied from 3 to 5 L h⁻¹ under the operating head of 1.5 to 2.5 m with the slope of 0–1.5%, with better performance of the DIS at 2 m operating pressure head and for slopes of 0% and 1%. The CU of all the test parameters was more than 80%, implying that the DIS was designed and installed with appropriate dimensions for the efficient application and distribution of water to the individual plants, with the emitter performance classified as fair to excellent considering water application and distribution, as well as crop yield. The new emitter used for DIS in field conditions showed that the eggplant yield, water use, and water productivity were greater by 4.6%, 38%, and 70%, respectively, compared to farmers’ irrigation practice. We conclude that the DIS has a great prospect to save water, and could be a convenient irrigation water application method for sustainable crop production in saline and nonsaline regions of Bangladesh and similar soil and climatic conditions in South Asia. Full article

This research work dealt with the development of an operational methodology with appropriate technical components for monitoring and forecasting of rice crop (Boro) production in Bangladesh. Designed system explores integrated application of remote sensing (RS) sciences and Geographic Information System (GIS) technology. Terra MODIS 16-day Normalized Difference Vegetation Index (NDVI) maximum value composite (MVC) image product MOD13A1 of 500 m spatial resolution covering Bangladesh have been utilized for a period 2011–2017. Hence the district-wise sum of NDVI on pixel-by-pixel has been calculated from Jan–April during 2011–2017. Regression analysis between district-based pixel-wise summation of MODIS-NDVI and district-wise BBS (Bangladesh Bureau of Statistics) estimated Boro production revealed strong correlation (R² = 0.57–0.85) where in March most of the regression coefficient shows significant correlation due to maximize photosynthetic activities. Therefore, the highest regression coefficient value from derived set of coefficient value (BCP-Boro Crop Production Model 2) has been utilized to obtain year-wise rice productions for all the years (2011–2017). Global Positioning System (GPS)-based field verification, accuracy assessment and validation operation have been carried out at randomly selected geographical positions over the country using various statistical tools. The results demonstrate good agreement between estimated and predicted yearly Boro rice production during 2011–2017 time period with Mean Bias Error (MBE) = −29,881 to 19,431 M.Ton; Root Mean Square Error (RMSE) = 5238 to 11,852 M.Ton; Model Efficiency (ME) = (0.86–0.94); Correlation Coefficients = 0.65 to 0.87. Therefore MODIS-NDVI based regression model seems to be effective for Boro production forecasting. The system generally appears to be relatively fast, simple, reasonably accurate and suitable for nation-wide crop statistics generation and food security issues. Full article

Efficient transplanting has been identified as one of the essential steps towards achieving an increased yield in the farm. However, many factors are affecting these processes such as soil moisture content and the speed of pickup. This study was carried out to investigate the effect of different soil moisture content and pickup speeds on pickup force, balance, resistance, and lump damage during transplanting of seedlings. The results showed that penetration resistance was inversely proportional to the speed and soil moisture content. The highest penetration resistance (38 N) values were recorded under the lowest speed (0.5 mm/s) at the low moisture content; whereas, the lowest penetration resistance was obtained at highest speed (10 mm/s) under high moisture content. The highest pick-up force resistance values were recorded under the lowest speed (0.5 mm/s) at low moisture content than the lowest pick-up force resistance of 1.4 N at (10 mm/s) under the high moisture content. On the other hand, an increase of pick-up force led to a decrease in the pick-up force resistance. The pick-up damage and the pick-up speed are directly proportional—nevertheless, the former increased with a decreasing soil moisture content. The highest pick-up damage values (82%) were observed under the top-most speed (10 mm/s) at high moisture content. It can be concluded that for successful auto-transplanting of seedling the soil condition, the force applied and speed should be taken into consideration. This work will implement an effective seedling-picking performance and basis for the optimal design of end-effectors. Full article

Feedstock degradation is a major source of financial risk for cellulosic biorefineries. To assess the impact of the feedstock loss and quality during storage, this study explored interactions of moisture content and temperature on the degradation of biomass. Specifically, this study evaluated the dry matter loss and compositional change of corn stover during storage conditions common at industrial biomass storage facilities. This lab-scale study allowed for increased measurement precision associated with quantifying how biomass degradation changes the quality of stored biomass. Results of this work define stable biomass storage moisture content of less than 20% in which there is low risk for degradation over time. At moisture levels above 20%, biomass degradation will be prevalent with hemicellulose being the most degraded fraction of the feedstock. Additionally, results demonstrate that temperature has a minimal impact on biomass degradation in non-frozen storage conditions. Full article

In this paper, a novel control-loop concept is presented to investigate the viscoelastic properties of different pome fruits. Repeated mechanical effects are one of the most important risk factors during the postharvest procedures, so our work aimed to expand knowledge in the field. The actual investigations involved Golden Delicious apples and Packham pears. The developed model is based on the Poynting–Thomson body and, during the validating dynamic creep tests, different repeated compressive loads were applied. The examined frequencies were chosen from the most common components of the frequency distribution during the transportation process; the given range is responsible for the highest volume of fruit damage and the most extensive losses. The identified mathematical system determines the viscoelastic model parameters with the best fit to the measured creep data. The model properties of the tested fruit textures are compared in six different frequency setups, with the inspected pome species showing different elastic and viscous responses for the adjusted load conditions. The custom testing device with variable load functions and the proposed solution allow system identification with a wide range of setup possibilities. The resulted viscoelastic parameters can be used for further failure analysis and for the comparison of different pome fruit materials. Full article