Agricultural Engineering

Biostimulating Extracts from Arctium lappa L. As Ecological Additives in Soybean Seed Coating Applications

2024-12-13T12:19:54+01:00

This paper proposes a new biostimulant coating for soybean seeds. The aim of the study was to create a coating for Glycine max (L.) Merr. soybean seeds, using root infusion from Arctium lappa L. as a biostimulant component. The effectiveness of the produced coating was evaluated in a three-year field study. The analysis of the effectiveness of the developed coating was based on the evaluation of plant biometric traits and yield. The study showed that the designed and manufactured soybean seed coating based on the root infusion of Arctium lappa L. can be considered as a new agronomic strategy to improve the productivity of soybean Glicyne max (L.) Merr. under actual field conditions. The application of the biostimulant coating resulted in soybean plants with significantly increased biometric traits (plant height, height of the first pod set, number of pods per plant, number of seeds per pod) and productivity (yield improvement of more than 10%). Only a reduced weight of 1,000 seeds compared to control samples was noted.

Numerical Simulation of Soil Water Dynamics in Automated Drip Irrigated Okra Field Under Plastic Mulch

2024-12-13T12:19:54+01:00

In India, drip irrigation with plastic mulch is a common practise for irrigation that conserves water. For the design and administration of irrigation regimes, a thorough understanding of the distribution and flow of soil water in the root zone is required. It has been demonstrated that simulation models are effective tools for this purpose. In this work, an automated drip-irrigated Okra field with seven treatments namely T1- Soil moisture-based drip irrigation to 100% FC, T2- Soil moisture-based drip irrigation to 80% FC, T3- Soil moisture-based drip irrigation to 60% FC, T4- Timer based drip irrigation to 100% CWR, T5- Timer based drip irrigation to 80% CWR, T6- Timer based drip irrigation to 60% CWR and T7- Conventional drip irrigation at 100% CWR were utilised to mimic the temporal fluctuations in soil water content using the numerical model HYDRUS2D. With the help of the observed data, the inverse solution was used to optimise the soil hydraulic parameters. The model was used to forecast soil water content for seven field treatments at optimal conditions. Root mean square error (RMSE) and coefficient of determination (R²) were used to assess the congruences between the predictions and data. With RMSE ranging from 0.036 to 0.067 cm³, MAE ranging from 0.020 to 0.059, and R² ranging from 0.848 to 0.959, the findings showed that the model fairly represented the differences in soil water content at all sites in seven treatments.

Moisture Dependent: Physical Properties of Baobab Seeds (Adansonia digitata L.)

2024-12-13T12:19:55+01:00

The research investigated physical properties of baobab seeds to determine suitable equipment for the processing of its seeds. Pods of baobab used in the study were collected at a local farm in Ilorin, North Central Nigeria. Physical properties of the samples, such as moisture contents, mass, axial dimensions, shape indices, true and bulk densities, porosity, angle of repose and surface area were determined. The results showed that physical properties of baobab seeds were stable for moisture content, ranging between 12 to 18% dry mass (dm). The 100 seed mass (g) and geometric mean diameter increased from 0.60 g to 0.62 g and 10.12 to 10.27 mm respectively, in the moisture range of 12 to 18% dm. Other studied ranges of physical properties ranges included: average length (12.22 to 12.63 mm), width (10.10 to 10.28 mm), thickness (8.23 to 8.42 mm,), sphericity, (81.23 to 82.56 mm), surface area (319.42 to 332.53 mm² ), 50 seed mass (0.60 and 0.62 g), and 1000 seed mass (12 and 12.4 g) within the moisture content range of 12 to 18% dm. The angle of repose of baobab seeds decreased with an increase in moisture content. The maximum value of 29.18^o was obtained at 14% moisture content while a minimum value of 24.42^o was obtained at 18% moisture. Moisture content had a significant effect on coefficient of friction of baobab seeds on glass, stainless steel, plywood and rubber. In the same moisture range (12-18%), the static coefficient of friction for baobab seeds ranged from 0-739 to 0-905 on stainless steel, 0-960 to 1-190 on galvanized steel, 0-812 to 1-055 on plywood and 0-496 to 0-950 on glass. The least coefficient of friction values were recorded on stainless steel and glass which implies that baobab seeds will move with lower resistance on these surfaces in post-harvest handling. On the other hand, the resistance will be higher on plywood and glass. The data obtained will serve as guide for agricultural and food engineers, food processors and technicians involved in design and construction of post-harvest equipment used for separating, cleaning, milling and other production processes, to which baobab seeds are subjected.

Comparison of NDVI, NDRE, MSAVI and NDSI Indices for Early Diagnosis of Crop Problems

2024-12-13T12:19:55+01:00

In precision agriculture, it is possible to use satellite monitoring of fields. Satellite monitoring systems allow you to get free images with a resolution of up to 10 m per pixel, which is sufficient to determine the state of vegetation of plants on such indicators as the normalized vegetation index NDVI. However, the NDVI indicator already indicates the existing problems of correction which will not help to restore the lost yield of crops, but only helps to prevent further losses. Using the NDSI soil salinity index, it is possible to determine the difference in its properties from spectral images. Also, you can study the vegetation of plants in the early stages of their development, in fact immediately after germination. Soil-adjusted vegetation index, such as MSAVI, is used for this purpose. Studies indicate the possibility of using NDSI and MSAVI indicators for early diagnosis of confirmed crops NDVI and NDRE (indicating chlorophyll activity in plants) at later stages of their development. Studies conducted on soybean, spring barley and maize crops sown in the spring of 2021 indicate a correspondence between raster field maps show-ing the above indices made from March to July. Statistical analysis of raster images of field maps using specialized software showed a correlation between NDSI and MSAVI in March and May, respectively, with NDVI and NDRE indexes in June and July. Therefore, it is possible to judge the expediency of using NDSI and MSAVI indicators for early diagnosis of possible problems with plant vegetation, as well as for the creation of maps of differential fertilization.

Smartphone-Operated Smart Farm Watering System Using Long-Range Communication Technology

2024-12-13T12:27:22+01:00

Keeping proper soil moisture is essential in growing good quality and efficient fruit yield. To that effect, soil moisture level must be controlled, to maintain proper watering. A smartphone application was developed to operate a smart farm watering system. It monitors the soil’s moisture and launches sprayers to water dried areas. The system’s architecture was built in a distributed client-server computing system, in a small computing grid. The grid was built across long range (LoRa) communication networks with the same ID, but different addresses. In terms of integration, the system was built using autonomous microprocessors, which consist of a server and five client microprocessors. A smartphone was used as the server of a central controller, and four moisture detection modules and a water spraying system module were used as autonomous clients. The server was inter-connected with the clients via a star-type topology network in the polling processes. Each client module autonomously analyzes the measured digital voltage of the moisture sensor plugged into the soil. When the server sends queries regarding the status of the moisture level, the client sends the request signal to the server using the LoRa communication technology. The communication between the server and the clients is based on the LoRa communication technology. The LoRa-to-Bluetooth converter is used to connect the Bluetooth and the LoRa signal. The field test was performed in a watermelon field, with an area of approximately 6600 m². The water spraying system constructed with LoRa communication technology could successfully manage and control the moisture level in the field test.