The main objective of this study was to analyze variable rate seeding (VRS) methods and critically evaluate their suitability and effectiveness for the challenges under field conditions. A search was performed using scientific databases and portals by identifying for analysis and evaluation 92 VRS methodologies, their impact and economic benefits depending on the main parameters of the soil and environment. The results of the review identified that VRS could adapt the appropriate seeding rate for each field zone, which was based on site-specific data layers of soil texture, ECa, pH and yield maps. Then, remotely detected images or other data which identify yield-limiting factors were identified. The site-specific sowing method (with a variable sowing rate for each field area) allows the optimization of crop density to obtain the best agronomic and economic results. Various proximal and remote sensor systems, contact and contactless equipment, mapping and VRS modeling technologies are currently used to determine soil and crop variability. VRS depends on the field characteristics’ sowing equipment capabilities, the planned harvest, soil productivity and machine technology interactions with the environment. When forecasting the effective payback of a VRS over the desired period, the farm size should on average be at least 150 ha. In future studies, to achieve the best solutions and optimal methods, it is important to test, evaluate and put into practice the latest methodologies on farms, to perform complex assessments of changes in sensor, soil, plant and environmental parameters.

Reducing the overuse of mineral fertilizers in crop production is a key factor related to healthier soil, healthier food, and more economical, efficient, and cleaner agricultural production. The aim of this study was to investigate and to compare the effects of fixed and variable rate fertilization with fertilizer consumption, energy consumption, and environmental impact. A 4-year experimental field study using crop rotation of four plants (spring barley, winter oilseed rape, winter wheat, and faba bean) was performed. Fertilization with phosphorus and potassium at a variable rate were performed and applied based on the soil properties analyzed before the start of the research and completion of the fertilization maps. Nitrogen fertilization was performed by additional fertilization using a proximal N-sensor, which gives the accurate nitrogen uptake in plants in real-time. This was followed by a comparative evaluation analysis of variables and conventional fixed-rate fertilization methods to assess fertilizer consumption, energy consumption, environmental impact, and economic efficiency. The results of the study showed that an application of a variable fertilization rate can reduce the total amount of nitrogen, phosphorus, and potassium fertilizers by 24.9%, energy consumption by 3463.1 kg ha⁻¹, and emissions of greenhouse gases (GHG) by 341.5 kg CO_2eq ha⁻¹ compared to fixed fertilization rate. The method of fertilization with a variable application rate reduced the costs of fertilization, and at the same time, the costs of the total plant production by €168.0 ha⁻¹, on average.

Weed control is one of the most important technological operations to ensure crop yield and quality in ecological sugar beet production. However, conventional mechanical weed control is labor- and time-intensive and has adverse effects on the soil and the environment. The aim of this study was to experimentally investigate the influence of conventional mechanical and robotic weed control systems on soil properties and to assess the effectiveness of these different weed control methods in ecological sugar beet production. This study examines two different weed control systems: robotic weed control (RWC) and conventional weed control (CWC). Field experimental studies were carried out with a solar-powered field robot and conventional inter-row cultivation (CWC1—first cultivation, CWC2—second cultivation) to determine the effectiveness of mechanical weed control in ecological sugar beet crops. The influence of different weed control systems on the physical properties of the soil in the contact zone between the soil and the tires of weed control machines was investigated. The results showed that the average weed control effectiveness inter-row was higher in the RWC (81%) compared to that in the CWC2 (46%). The overall weed control effectiveness of the robotic weed control in the sugar beet inter-row and intra-row was around 49%. The measurements showed that the weed control process reduced the soil moisture and temperature in all treatments tested. Experimental studies have confirmed that the weed control operation, although carried out with relatively lightweight robots, also has an impact on soil bulk density. RWC weed control resulted in an average increase of 0.16 g cm^–3 in soil bulk density in the topsoil layer (0–10 cm) after weeding. Both CWC1 and RWC increased soil penetration resistance (PR). For CWC1, the average increase in topsoil PR after weed control was 20%, while for RWC, the increase was marginal, only around 1%. Automated precision weed control by self-propelled solar-powered field robots is an important solution to reduce the need for tedious and time-consuming manual weeding.

Sowing or seedbed depth is an important agro-technological parameter that varies with specific on-field soil and microclimatic conditions and depends on crop biology. There is a lack of detailed information regarding how seedbed depth relates to other seedbed parameters and affects the development of agricultural crops. Several seeder constructions and methods for seeding condition detection and depth adjustment have been investigated in high-precision, digitally backgrounded, in-site sowing systems; however, there is still a gap in knowledge due to the limited use of these technologies in conditions of high soil and micro-climatic variability. Therefore, the aim of this study was to highlight the impact of sowing depth on crop seedbed parameters, mainly established by the Kritz method, to ascertain the correlation between sowing depth, germination, crop development and productivity, and to overview the methods and equipment used for detection, adjustment and control of sowing depth in precision site-specific sowing systems. Our results showed that, in most cases, when sowing depth extended beyond the optimum, the moisture content in the seedbed decreased significantly. Sowing depth also correlated with the roughness of the seedbed (surface and bottom) and seedbed aggregate size distribution, but the direction of the relation depended on crop type and maximum sowing depths. Sowing depth correlated with crop germination, development and productivity parameters; however, the direction of exposure and intensity also varied with respect to crops, weather conditions, tillage and sowing equipment. Sowing depth uniformity is greatly influenced by the regulation of clamping force, the spatial variability of soil in fields and sowing operation speed.

Rapidly warming climate, tightening environmental requirements, an aging society, rising wages, and demand for organic products are forcing farming to be more efficient and sustainable. The main aim of this study was to perform an analytical analysis and to determine the energy use and GHG emissions of organic sugar beet production using different weed control methods. Seven different methods of non-chemical weed control were compared. Mechanical inter-row loosening, inter-row cutting and mulching with weeds, weed smothering with catch crops, and thermal inter-row steaming were performed in field experiments at the Experimental Station of Vytautas Magnus University (Lithuania, 2015–2017). The other three, namely, automated mechanical inter-row loosening with cameras for row-tracking, inter-row loosening with a diesel-powered robot, and inter-row loosening with an electric robot were calculated analytically. The results showed that the average total energy use of organic sugar beet production was 27,844 MJ ha⁻¹, of which manure costs accounted for 48–53% and diesel fuel for 29–35%. An average energy efficiency ratio was 7.18, while energy productivity was 1.83 kg MJ ha⁻¹. Analysis of GHG emissions showed that the total average GHG emissions to the environment from organic sugar beet production amounted to 4552 kg CO_2eq ha⁻¹, and the average GHG emissions ratio was 4.47. The most sustainable organic sugar beet production was achieved by using mechanical inter-row loosening with a diesel-powered robot for weed control.

Wheat is among the world’s most important agricultural crops, with winter wheat accounting for approximately 25.5% of the total agricultural crop in Lithuania. The unchangeable goal of crop production is to achieve good and economically beneficial crop yield, but such efforts are often based on conventional agrotechnological solutions, and excessive fertilization, which is uneconomical and negatively affects the soil, the environment, and human health. In order to produce a rich and high-quality cereal crop, scientists and farmers are increasingly focusing on managing the sowing and fertilization processes. Precision technologies based on spectrometric methods of soil and plant characterization can be used to influence the optimization of sowing and fertilizer application rates without compromising crop yield and quality. The aim of this study was to investigate the effect of site-specific seeding and variable-rate precision fertilization technologies on the growth, yield, and quality indicators of winter wheat. Experimental studies were carried out on a 22.4 ha field in two treatments: first (control)—SSS (site-specific seeding) + URF (uniform-rate fertilization); second—SSS + VRF (variable-rate precision fertilization) and 4 repetitions. Before the start of this study, the variability of the soil apparent electrical conductivity (ECa) was determined and the field was divided into five soil fertility zones (FZ-1, FZ-2, FZ-3, FZ-4, and FZ-5). Digital maps of potassium and phosphorus precision fertilization were created based on the soil samples. Optical nitrogen sensors were used for variable-rate supplementary nitrogen fertilization. The variable-rate precision fertilization method in individual soil fertility zones showed a higher (up to 6.74%) tillering coefficient, (up to 14.55%) grain yield, number of ears per square meter (up to 27.6%), grain number in the ear (up to 6.2%), and grain protein content (up to 12.56%), and a lower (up to 8.61%) 1000-grain weight on average than the conventional flat-rate fertilization. In addition, the use of the SSS + VRF method saved approximately 14 kg N ha⁻¹ of fertilizer compared to the conventional SSS + URF method.