Abstract in English:ABSTRACT With the increasing scale of farms and the correspondingly higher number of laying hens, it is increasingly difficult for farmers to monitor their animals in a traditional way. Early warning of abnormal animal activities is helpful for farmers’ fast response to the negative impact on animal health, animal welfare and daily management. This study introduces an automatic and non-invasive method for detecting abnormal poultry activities using a 3D depth camera. A typical region including eighteen Hy-line brown laying hens was continuously monitored by a top-view Kinect during 49 continuous days. A mean prediction model (MPM), based on the frame difference algorithm, was built to monitor animal activities and occupation zones. As a result, this method reported abnormal activities with an average accuracy of 84.2% and a rate of misclassifying abnormal events of 15.8% (PFPR). Additionally, it was found that the flock showed a diurnal change pattern in the activity and occupation quantified index. They also presented a similar changing pattern each week.
Abstract in English:ABSTRACT Plant ambiance studies the environmental condition favorable to plant growth at the initial stage of seedlings or the complete production cycle. This study aimed to evaluate the cultivation of the ornamental pepper ‘Pyramid’ under protected environments and growing benches with and without reflective material. The protected environments consisted of a greenhouse covered with low-density polyethylene film and 42/50% shading thermo-reflective screen under the film, structure with 35% shading thermo-reflective aluminized screen, and structure with 30% shading black screen. The growing benches were tested in environments without and with reflective material made of aluminized screen. The environment of the agricultural greenhouse covered with low-density polyethylene film and 42/50% thermo-reflective screen under the film favored the growth of ornamental pepper plants regarding height and diameter and provided early flowering and high fruit production. The use of the reflective material showed no significant results for plant height, stem diameter, and the number of leaves. The use of reflective material increased the number of fruits in plants under the environments with 35% shading aluminized screen and 30% shading black screen.
Abstract in English:ABSTRACT An increasing amount of sunlight is available to sunken greenhouses located in northern China, but it remains unclear how the indoor temperature changes at different heights and at the north and south ends of the structure. To study how the temperature in a single indoor section, at multiple points, varies in a sunken solar greenhouse, 10 measurement lines were arranged in a section 30 m from the west wall. Each line was equipped with a corresponding WT-59 wireless sensor. Temperature and humidity data were collected from 8 March 2019 to 26 December 2019. The following results were obtained. (1) The indoor temperature variation in a day could be divided into four stages: from 0:00 to 7:30 h, the temperature at all measurement points decreased linearly; from 7:30 to 14:30 h, the temperature at all measurement points increased curvilinearly; from 14:30 to 18:00, the temperature at all measurement points decreased curvilinearly; and from 18:30 to 24:00, the temperature at all measurements points decreased linearly. (2) The maximum temperature on sunny days in the greenhouse was higher than that on cloudy days and snowy days, but the maximum temperature on cloudy days and snowy days in the greenhouse occurred 3 h earlier than on sunny days. (3) The lowest average temperature of a sunken solar greenhouse over 3–6 months was 7.5ଌ, without heating. The research results provide theoretical and reference data on how the temperature changes in the interior of a solar greenhouse and inform about the three-dimensional planting height and ventilation times.
Abstract in English:ABSTRACT To efficiently eliminate the noise generated by the triaxial accelerometer when collecting pigs’ behavioural data, this paper adopted SNR and MSE as the indexes to evaluate the de-noising effect of pigs’ acceleration signal under various combinations of wavelet basis, decomposition layer, threshold rule and threshold function. Based on the optimal wavelet parameter combinations, the de-noised data were divided into a training dataset and test dataset to conduct a 3-fold cross validation. The results showed that Db4 wavelet can achieve a satisfactory de-noising effect when used as a wavelet basis for 8 layers wavelet decomposition based on Rigrsure threshold rules and the new improved threshold function. As a result, compared with traditional wavelet hard threshold de-noising, soft threshold de-noising and EMD de-noising method, the improved threshold function improved the stability of signal filtering, which was shown to be more practical, effective and feasible. As such, wavelet de-noising was found to significantly improve the classification accuracy of all four behaviour classes (lying, standing, walking and exploring) considered for this study, and the overall major mean accuracy was improved from 0.680 to 0.826.
Abstract in English:ABSTRACT This paper presents a new approach to properly estimate energy consumption inside a greenhouse. In this study, we have adopted improved classical modelling to evaluate the energy balance of a greenhouse with a higher precision. While the traditional classical model focuses mainly on the cooling and heating (and denies the deep influence of lighting factors), we demonstrate the importance of considering these three necessary components as being interdependent through this academic study; they should all be integrated in order to reach optimal crop production and efficient energy consumption. Our contribution will be to improve the traditional classical model and to demonstrate that daylight, as well as artificial lighting, has fundamental consequences on the estimating of the required energy consumption and the choice of the optimal shape and coverage material of the greenhouse.
Abstract in English:ABSTRACT The productivity of a crop is related to the water demand inserted in its development. The measurement of water and its optimization directly influences the final costs of crop production for agricultural producers. In this sense, the objective of this study is evaluating the fuzzy modeling in estimating the productivity of the radish crop (fresh phytomass of the tuberous root) affected by different irrigation depths (25%, 50%, 75%, 100%, and 125%), based on evapotranspiration of the crop (ETc). To measure the results, two fuzzy systems (with triangular and Gaussian membership functions respectively) and a polynomial regression model were developed to perform model validation comparisons. The fuzzy modeling showed a better fit of the data compared to the polynomial regression model, with reduced errors (RMSE with values 6.3 and 6.9 in the fuzzy models versus 8.8 in the regression model) and higher correlation coefficient (0.54 and 0.5 fuzzy versus 0.1 regression). The triangular fuzzy model estimated the best crop yield (31.9 g of fresh phytomass) when using a 100% ETc depth. Also, the curve generated by the fuzzy model accurately represents all the productivity averages in each depth, in addition to this model presenting the smallest errors (compared to the triangular model and the regression model) and the highest R2. However, the Gaussian fuzzy model proved to be more efficient in representing the agronomic reality, as it does not have peaks and valleys, and it is a smooth model in both growth and degrowth.
Abstract in English:ABSTRACT In order to estimate the response of biometric variables in different irrigation depths in radish crop, as well as their relations in the development of the crop, a fuzzy mathematical analysis was carried out from irrigation with depths of different percentages of the crop evapotranspiration (ETc), using Gaussian pertinence functions for the input variable and triangular for the biometric output variables. Validations were performed using neural network models, smoothing splines and polynomial regression. The relation among the biometric variables was measured applying the Pearson correlation coefficient. The results showed that the fuzzy modeling presented superiority in the crop development estimate over the quadratic polynomial regression model, neural network and smoothing splines, because it achieved an average reduction of errors among the biometric variables, of 7.8% 94.6% and 9.2% for the RMSE in the respective models, as well as a better adjustment of the data with average R2 of the variables. The modeling with neural network showed inadequate agronomic behavior in data representation. Regarding biometric variables, the length and diameter of the tuberous root are inversely correlated, and the fresh phytomass of the tuberous root is correlated only with the fresh phytomass of the root.
Abstract in English:ABSTRACT Water availability is one of the most important factors for the growth of tree seedlings in forestry-related regions. We hypothesized that under different water regimes, a water-retaining polymer (hydrogel) can positively contribute to chlorophyll- a fluorescence and growth in Campomanesia xanthocarpa (Mart.) O. Berg. Four water retention capacities (WRC) were evaluated: 25%, 50%, 75%, and 100%, depending on the presence or absence of hydrogel at the substrate. The lowest WRCs, particularly those under 25% without hydrogel, reduced chlorophyll index and negatively affected the photochemical activities of photosystem II. However, under low water availability the hydrogel mitigated the damage inflicted on the reaction centers and chlorophyll synthesis. The greatest growth effects occurred at 100% WRC in the presence of the hydrogel. Physiological indices were higher under 100% WRC without hydrogel and 50% with hydrogel. The increase in biomass and Dickson quality were more pronounced in the seedlings produced under 50% WRC and hydrogel, and the addition of these parameters to the substrate contributed to more viable morphophysiological indicators for the production of C. xanthocarpa seedlings.
Abstract in English:ABSTRACT The development of the Internet and the technologies associated with it has allowed disseminating and cheapening of communication equipment, prototyping services, electronic sensors, and all types of devices. Agriculture has benefited from these technological advances to boost its productivity and profitability. This study presents the development of a data acquisition and device control platform to obtain, in real-time and remotely, information from the field for decision-making and process automation. All electronic components are low-cost and “open hardware”, and the software is “open-source”. The developed platform was validated during a development cycle of two lettuce varieties (Japanese and crisp), in which the soil water matric potential was monitored at two depths (10 and 25 cm), while solar irradiation, air temperature, and soil temperature were evaluated only to monitor the cycle. The platform automatically and satisfactorily controlled the applied irrigation depths using only the data of matric potential by activating a solenoid valve and made the information from the sensors available on the ThingSpeak Internet of Things (IoT) platform.
Abstract in English:ABSTRACT A pneumatic olive harvester was developed and evaluated in this study. The components of the developed machine were the limb clamp, vibrating unit, control elements, main tube, air-pressured hoses, control valve, and power source. The measurements that related to the development of the harvester were fruit and limb damage, and some physical and mechanical properties of the olives fruit-stem system. The results demonstrated that the effectiveness of the developed machine to harvest olive fruits. The appropriateness of the developed machine was evaluated by some criteria: machine productivity, fruit removal, fruit damage, limb damage depth at the contact point with the clamp of the machine, breakage of shaken limb, and consumed energy. The suitable values of these criteria were achieved at 27 Hz frequency and 60 mm stroke.
Abstract in English:ABSTRACT One of the main costs in agriculture is related to mechanized operations, which, in turn, are associated with the capital invested in machinery and equipment, the scale of production, and the operating efficiency. Thus, the choice of technology to carry out these operations must take these factors into account to minimize the production cost. In this context, this study aimed to evaluate the most economical investment option for the set of sprayings on a farm located in the municipality of Mineiros, Goiás, Brazil, by comparing two technologies (ground and aerial spraying) and identifying the scale of production that makes each of the technologies more feasible. This study covers the period of one year with the soybean crop in the summer season, followed by the cultivation of corn in the off-season. Economic feasibility indicators were calculated, and the total average costs of both technologies were compared. The results allowed concluding that the investment in aerial spraying with the aircraft acquisition is assertive, as it reduced losses due to crushing. Contracting the service via third parties is feasible and can be used not only in cases of emergency, as it allows for increased profitability.
Abstract in English:ABSTRACT The uniformity and quality of spraying depend on the stability of the spray boom, defined as the suspension system between the boom and the machine chassis. This paper presents a procedure for improving the performance of passive spray bar suspensions through parameter adjustment. Two multibody dynamics models of a tractor sprayer set were developed to evaluate their suspension systems: a rigid body dynamics model (RBDM) and a finite element model (FEM) using deformable bodies. To calibrate the models in the experiment, an accelerating force was applied to the suspension, and the displacements of the shock absorber and the rubber springs were monitored. The FEM is more suitable for the evaluation of the horizontal oscillations of the bar, based on root mean square (RMS) values and a standard curve used to evaluate the stability of the bar. The horizontal stiffness of the bar significantly influences the oscillatory displacement and must be included in the simulation models. Resizing the structure can reduce the horizontal oscillations of the bar.
Abstract in English:ABSTRACT In drying processes and in the storage of agricultural products, the study of thermodynamic properties is indispensable in the search for solutions to issues of stability and optimization of the conditions of agro-industrial processes. The aim of this work was to determine hygroscopic equilibrium isotherms and study the thermodynamic properties of white bean grains submitted to different equilibrium temperatures and relative humidity levels. Phaseolus vulgaris L. grains were used, with an initial water content of 0.142 (dry basis), temperature variations ranging between 18 and 50 °C, and relative humidity between 19% and 78%. Fifteen mathematical models were tested to determine the hygroscopic equilibrium isotherms, and the Sigma model was the one that best suited the experimental data. The thermodynamic properties of the beans were determined from Sigma-Copace model. The integral isosteric heat of desorption and the differential entropy increased with the reduction of the water content, and the phenomenon of water desorption of white bean grains was a non-spontaneous process controlled by enthalpy.
Abstract in English:ABSTRACT Cranberries and blueberries are small fruits known for their antioxidant properties. However, due to their high water content and short shelf life, they are generally marketed as dehydrated berries. The present work aimed to model the rehydration of dehydrated berries. Rehydration tests were conducted at 7 and 29°C using milk as a solvent and at 7, 29, and 45°C when the solvent was water. The mass gain was assessed at different intervals, and the experimental data were fitted to the Fick model considering the berries as spheres. Six empirical/semi-empirical models describing the diffusion of water during drying were used to predict the rehydration process. Fick’s law satisfactorily represented the data, and the highest diffusion coefficients were found when the berries were rehydrated in water at 45°C. Rehydration of berries in milk resulted in nutrient gain as different diffusive flows occurred during the process. The use of empirical models to predict the operating time of the rehydration processes allows flexibility as such models are mathematically simpler than the Fick model. Diffusivity is essential for the design/construction of equipment, and/or process optimization and implementation.
Abstract in English:ABSTRACT Soil apparent electrical conductivity (ECa) sensors have been used to detect spatial variability because they correlate with soil attributes. Studies with soil attributes have shown that the number of subsamples and sampling points influences mapping. However, there are no studies that investigated the influence of sampling or subsampling density on ECa maps. Therefore, this study verified the influence of ECa readings per sample point on the semivariance and kriging analysis. The data were collected from an area (2.5 ha) of coffee plants. One hundred sampling points were measured considering 20 readings each. 1, 5, 10, 15, and 20 sample point readings were tested. The influence of the number of readings per sampling point on the ECa mapping was determined using linear regression analysis at a significance level of 5%. The results obtained showed that ECa readings per sampling point significantly influence ECa maps. In addition, they demonstrated that reducing the number of readings per sampling point increases prediction errors by kriging. Thus, ECa maps determined with the highest readings per sampling point were mostly accurate.