Search Results (118)

Winter wheat yield prediction is critical for optimizing field management plans and guiding agricultural production. To address the limitations of conventional manual yield estimation methods, including low efficiency and poor interpretability, this study innovatively proposes an intelligent yield estimation method based on a convolutional neural network (CNN). A comprehensive two-factor (fertilization × irrigation) controlled field experiment was designed to thoroughly validate the applicability and effectiveness of this method. The experimental design comprised two irrigation treatments, sufficient irrigation (C) at 750 m³ ha⁻¹ and deficit irrigation (M) at 450 m³ ha⁻¹, along with five fertilization treatments (at a rate of 180 kg N ha⁻¹): (1) organic fertilizer alone, (2) organic–inorganic fertilizer blend at a 7:3 ratio, (3) organic–inorganic fertilizer blend at a 3:7 ratio, (4) inorganic fertilizer alone, and (5) no fertilizer control. The experimental protocol employed a DJI M300 RTK unmanned aerial vehicle (UAV) equipped with a multispectral sensor to systematically acquire high-resolution growth imagery of winter wheat across critical phenological stages, from heading to maturity. The acquired multispectral imagery was meticulously annotated using the Labelme professional annotation tool to construct a comprehensive experimental dataset comprising over 2000 labeled images. These annotated data were subsequently employed to train an enhanced CNN model based on ResNet50 architecture, which achieved automated generation of panicle density maps and precise panicle counting, thereby realizing yield prediction. Field experimental results demonstrated significant yield variations among fertilization treatments under sufficient irrigation, with the 3:7 organic–inorganic blend achieving the highest actual yield (9363.38 ± 468.17 kg ha⁻¹) significantly outperforming other treatments (p < 0.05), confirming the synergistic effects of optimized nitrogen and water management. The enhanced CNN model exhibited superior performance, with an average accuracy of 89.0–92.1%, representing a 3.0% improvement over YOLOv8. Notably, model accuracy showed significant correlation with yield levels (p < 0.05), suggesting more distinct panicle morphological features in high-yield plots that facilitated model identification. The CNN’s yield predictions demonstrated strong agreement with the measured values, maintaining mean relative errors below 10%. Particularly outstanding performance was observed for the organic fertilizer with full irrigation (5.5% error) and the 7:3 organic-inorganic blend with sufficient irrigation (8.0% error), indicating that the CNN network is more suitable for these management regimes. These findings provide a robust technical foundation for precision farming applications in winter wheat production. Future research will focus on integrating this technology into smart agricultural management systems to enable real-time, data-driven decision making at the farm scale. Full article

The insect resistance expression of Bacillus thuringiensis (Bt) cotton (Gossypium hirsutum L.) is unstable due to temporal and spatial variations in the Bt protein content in different organs and growth stages. The aim of this study was to improve the Bt protein content in cotton flowers and investigate the underlying physiological mechanism using biochemical analytical methods. In this study, a split-plot design with three replications was used. The main plots included two Bt cotton cultivars (a conventional cultivar, Sikang1 (S1), and a hybrid cultivar, Sikang3 (S3)), while five soil nitrogen application levels (CK (control check): normal level; N1: 125% of the CK; N2: 150% of the CK; N3: 175% of the CK; N4: 200% of the CK) constituted the subplots. The Bt protein content and related nitrogen metabolism parameters were measured. We found that the Bt protein content increased and then decreased with increasing nitrogen rates. It reached its maximum at N3, with significant increases of 71.86% in 2021 and 39.36% in 2022 compared to the CK. Correlation analysis indicated that the Bt protein content was significantly positively related to the soluble protein and free amino acid contents, as well as the GPT (glutamic pyruvic transaminase), GOT (glutamic oxaloacetic transaminase), GS (glutamine synthetase) and GOGAT (glutamate synthetase) activities. On the other hand, negative correlations were found between the Bt protein content and protease and peptidase activities. In addition, stepwise regression and path analysis indicated that the increased Bt protein content was mainly due to the enhanced GS and GOGAT activities. In summary, appropriately increasing nitrogen fertilizer application is a practical way to increase flower Bt protein content and insecticidal efficacy of Bt cotton. These findings provide an actionable agronomic strategy for sustaining Bt expression during the critical flowering period. Full article

The disadvantages of traditional strip fertilization technology for corn planting in China include low fertilizer utilization rates, unstable operation quality, and environmental pollution. Therefore, in this study, a synchronous hole fertilization device for corn planting based on real-time intelligent control is designed, aiming to reduce fertilizer application and increase efficiency through the precise alignment technology of the seed and fertilizer. This device integrates an electric drive precision seeding unit, a slot wheel hole fertilization unit, and a multi-sensor coordinated closed-loop control system. An STM32 single-chip micro-computer is used to dynamically analyze the seed–fertilizer timing signal, and a double closed-loop control strategy (the position loop priority is higher than the speed loop) is used to correct the spatial phase difference between the seed and fertilizer in real time to ensure the precise control of the longitudinal distance (40~70 mm) and the lateral distance (50~80 mm) of the seed and fertilizer. Through the Box–Behnken response surface method, a field multi-factor test was carried out to analyze the mechanism of influence of the implemented forward speed (A), per-hole target fertilizing amount (B), and plant spacing (fertilizer hole interval) (C) on the seed–fertilizer alignment qualification rate (Y₁) and the coefficient of variation in the hole fertilizing amount (Y₂). The results showed that the order of primary and secondary factors affecting Y₁ was A > C > B, and that the order affecting Y₂ was C > B > A; the comprehensive performance of the device was best with the optimal parameter combination of A = 4.2 km/h, B = 4.4 g, and C = 30 cm, with Y₁ as high as 94.024 ± 0.694% and Y₂ as low as 3.147 ± 0.058%, which is significantly better than the traditional strip application method. The device realizes the precise regulation of 2~6 g/hole by optimizing the structural parameters of the outer groove wheel (arc center distance of 25 mm, cross-sectional area of 201.02 mm², effective filling length of 2.73~8.19 mm), which can meet the differentiated agronomic needs of ordinary corn, silage corn, and popcorn. Field verification shows that the device significantly improves the spatial distribution of the concentration of fertilizer, effectively reduces the amount of fertilizer applied, and improves operational stability and reliability in multiple environments. This provides technical support for the regional application of precision agricultural equipment. Full article

Fertilization has an important effect on soil antibiotic resistance. Most recent studies have focused on antibiotic resistance genes (ARGs) harbored by bacteria (bARGs); however, little is known about ARGs carried by soil bacteriophages (pARGs) under different fertilization treatments. Here, 24 pARG subtypes were quantified in soils with long-term application of different fertilizers using droplet digital PCR (ddPCR). The results showed that the detection rates of the target ARGs in bacteriophages were 66.67%, 70.83%, and 75.00% in unfertilized, chemically fertilized, and organically fertilized soils, respectively. The total abundance of pARGs in soils amended with organic fertilizer was significantly higher than that in unfertilized and chemically fertilized soils. The multidrug resistance gene (mexF) exhibited the highest abundance in soils amended with organic fertilizer. A significant positive correlation was observed between bARGs and pARGs, and the detected pARG subtype abundances were one to two orders of magnitude lower than those of the corresponding bARGs. The results of variation partitioning analysis revealed that the interaction between the bacterial community and soil properties drove the variation in soil pARGs. Our findings indicate that bacteriophages are important vectors of ARGs, in addition to bacteria, in agricultural soils, and their contribution to antibiotic resistance should not be overlooked. Full article

Implementing a variable-rate application (VRA) of fertilization based on real-time crop growth status reduces costs and enhances work efficiency. However, the technical challenges associated with obtaining accurate growth-distribution maps and applying VRA, particularly with agricultural drones, remain underexplored. In this study, we specifically focused on agricultural drone-based VRA fertilization for regulating wheat protein content. First, normalized difference vegetation index (NDVI) distribution maps were obtained using multispectral images captured using a small unmanned aerial vehicle. Subsequently, a prescription map based on the NDVI values was generated to facilitate the implementation of VRA for fertilization. Continuous monitoring of changes in related vegetation indices was conducted from post-topdressing to harvest. Experimental results indicated that selecting targeted experimental survey areas based on different growth conditions can result in accurate predictions of the final yield. However, it is sill ineffective for predicting protein content or protein yield. Additionally, VRA fertilization with less fertilizer in high-NDVI areas and more fertilizer in low-NDVI areas showed no significant difference in final protein content or protein yield compared to conventional uniform fertilization. These findings provide reference data for advancing precision agriculture by addressing field-scale variability for high-quality and uniform production while presenting further research challenges. Full article

Previous research on soil bacteria focused on refining the nitrogen (N) rates during the wheat (Triticum aestivum L.) growth cycle. Studies concerning how additional and split N topdressing applications can affect wheat rhizobacteria are limited. To address this, a two-year field experiment took the cultivar ‘Gaoyou 2018’ of winter wheat as the experimental material from October 2020 to June 2022. Six nitrogen application regimes were established, including no nitrogen application (T1), single topdressing applications of 120 kg ha⁻¹ (T2) and 80 kg ha⁻¹ (T3) at the jointing stage, and split topdressing applications combining 80 kg ha⁻¹ at jointing with 40 kg ha⁻¹ at the booting stage (T4), the flowering stage (T5), and 10th day post-anthesis (T6). The delayed impacts of the split topdressing time on the rhizobacteria diversity were observed in the second year, with T4 exhibiting a 10.5% higher Chao1 index and 2% greater Shannon diversity than T6. Results from both years indicated that the dominant bacterial phylum compositions in the winter wheat rhizosphere were similar across the nitrogen treatments. The additional N treatments fostered 22.9–27.9% Bacteroidita abundance but diminished 24.0–35.9% Planctomycetota, compared to the thenon-fertilized control (T1). T6 increased the α-Proteobacteria abundance by 15.7–22.0% versus T4, while the N topdressing redistribution to the booting stage increased the MND1 genus abundance in Proteobacteria by 31.3–62.5% compared to T2. Redundancy analysis identified that the rhizosphere pH and soil moisture content were the predominant environmental drivers shaping the winter wheat rhizobacteria. Preliminary findings revealed that split nitrogen application during the jointing and booting stages of winter wheat improved the edaphic micro-environment and modulated the proliferation of beneficial rhizobacteria. However, this change was not transmitted to the yield variation. These results suggest that short-term N management strategies may enhance ecological benefits by intensifying soil–plant–microbe interactions, yet they lack direct agronomic yield advantages. Long-term trials are required to establish causality between rhizosphere microbial community dynamics and crop productivity under split N management regimes. Full article

Lettuce is among the 10 most valued vegetables for fresh consumption in Brazil. The use of rock powder in lettuce crops for soil acidity correction or fertilization is an option for reducing production costs. In this context, the objective of this study was to evaluate the effects of rock powder rates mica schist and irrigation water depths on the development and production characteristics of lettuce crops. The study was conducted in the experimental area of the State University of Goiás, using pelletized seeds of the lettuce cultivar Crespa Vanda. A randomized block experimental design with four replications was used, in a 4 × 4 factorial arrangement composed of four irrigation water depths: 50%, 75%, 100%, 125% of crop evapotranspiration (ETc), and four rock powder rates: 6, 8, 10, and 12 tons per hectare (t ha⁻¹), associated with mineral soil fertilizer application, totaling 16 treatments and 64 experimental plots. The variables evaluated were plant height, stem diameter, number of leaves, head diameter, total fresh weight, commercial fresh weight, leaf area index, useful leaf area, estimated yield, chlorophyll a, chlorophyll b, and water use efficiency. The data were subjected to regression analysis and principal component analysis. The variables studied exhibited predominantly low to medium coefficients of variation in all treatments, confirming the homogeneous conditions and precision of the study. The treatment with the highest rock powder rate (12 t ha⁻¹) provided the best results regarding agronomic effects for all lettuce crop variables evaluated. This rate provided better plant growth and development, resulting in improved response for production variables that are agronomically and economically relevant. The highest water use efficiency was found for the water depth of 50% ETc; however, the best lettuce production results were found for the irrigation water depth of 100% ETc. This water depth highlighted the strong correlation of commercial and total fresh weights with commercial and total production, as they are production components of the crop. Full article

The application of phosphate fertilizers significantly influences soil microbial communities and nutrient cycling. Soil enzymes, which are sensitive to nutrient levels, play a critical role in microbial metabolism. However, the impact of phosphate fertilizers on nutrient limitations within the microbial metabolism of agricultural soils remains poorly understood. In this study, soil samples were collected from a depth of 0–20 cm from a wheat crop subjected to a three-year field experiment with six different phosphorus (P) application rates. Soil β-glucosidase (BG) and leucine aminopeptidase (LAP) activities were highest under the P3 (60 kg P₂O₅ ha⁻¹) treatment over the three-year study period. The responses of soil N-acetyl-β-glucosaminidase (NAG) and alkaline phosphatase (AKP) to increasing P additions varied across different years. The EES C:N, C:P, and vector length were significantly greater than 1. Soil nutrient characteristics accounted for 70.71% of the variation in soil enzyme stoichiometry. The vector length and angle of soil enzymes explained by soil nutrient characteristics were 0.65 and 0.73, respectively. Among these factors, ROC exhibited the largest direct and total effect on the soil enzyme vector length and angle. These research findings offer valuable insights for the management of agricultural fertilizers. Consequently, it is recommended to enhance soil carbon levels to alleviate carbon limitations and improve P utilization efficiency. Full article

Coffee production in mountainous regions faces significant challenges to mechanization, particularly in management and fertilization. Fertilizer application remains largely manual, reducing accuracy and failing to meet the demands of variable-rate application (VRA). This study developed a portable VRA fertilizer applicator with an embedded electronic control system. The innovation lies in its electrically driven metering mechanism integrated with an electronic control unit (ECU), enabling site-specific fertilization based on prescription maps or predefined rates while recording application coordinates. The mechanism was tested under laboratory and field conditions, evaluating its performance across four fertilizer types, varying inclination angles, and rotational speeds. Results showed a coefficient variation of 0.41% for doses above 24 g, demonstrating high consistency irrespective of fertilizer type or terrain slope. Field tests using potassium chloride (KCl) prescriptions (55, 123, and 185 g/plant; 220, 492, and 740 kg/ha) revealed minimal deviations, with the largest at 22.72 g and the smallest at 0.384 g. These findings demonstrate the applicator’s precision and efficiency, addressing the challenges of mountainous terrains. This system provides technological advancement for sustainable coffee production, enhancing resource optimization and supporting precision agriculture in challenging environments. Full article

Nitrous oxide (N₂O) is a major greenhouse gas (GHG) responsible for global warming. Improper fertilization in agricultural fields, particularly excessive nitrogen (N) application, accelerates soil N₂O emissions. Though partial substitution with organic fertilizer has been implemented to mitigate these emissions, the effect on perennial systems, such as tea plantations, remains largely unexplored. Therefore, the present study monitored soil N₂O emissions for a year in a tea plantation in South China under the following treatments: no N fertilizer (control, CK), chemical fertilizer alone (CF), replacing 40% of chemical fertilizer with organic fertilizer (CF + OF), and organic fertilizer alone (OF). Our results showed that the annual cumulative N₂O emissions from the plantation soil ranged from 1.03 to 3.43 kg N₂O-N ha⁻¹. The cumulative N₂O emissions, the yield-scaled N₂O emissions (YSNE), and the N₂O-N emission factor (EF) from the soil were the highest under the CF + OF treatment but the lowest under the OF treatment. Further analysis revealed that fertilization, mainly chemical fertilization, increased the soil ammonium (NH₄⁺-N) and nitrate (NO₃⁻-N) levels by 182–387% and 195–258%, respectively, and tea yields by 120–170%. However, tea yield decreased gradually with increasing organic substitution. These results prove that complete organic substitution reduces soil N₂O emissions and tea yield and suggest adopting an appropriate substitution rate for optimal effect. Further random forest (RF) modeling identified water-filled pore space (WFPS; 20.27% of total variation), soil temperature (Tsoil; 19.29%), and NH₄⁺-N (18.27%) as the key factors significantly contributing to the changes in soil N₂O flux. These findings provide a theoretical foundation for optimizing fertilization regimes for sustainable tea production and soil N₂O mitigation. Full article

In China, there are around 36.7 million hectares of saline–alkali lands that hold utilization potential. Precision fertilization stands as a vital measure for enhancing the quality of saline–alkali soil and promoting a significant increase in crop yields. The performance of the fertilization device is a decisive factor in determining the effectiveness of fertilization. To optimize the fertilizer utilization rate in coastal saline–alkali soils and substantially reduce fertilizer waste, it is imperative to transport fertilizers to the deep soil layers and execute layered variable-rate fertilization. In light of this, a chisel-type variable-rate layered electronically controlled deep-fertilization device specifically designed for saline–alkali soils has been developed. Extensive experimental research on its fertilization performance has also been carried out. Drawing on the principles of soil dynamics, this paper meticulously investigates the structures of key components and the operating parameters of the fertilization device. Key parameters such as the penetration angle of the fertilizer shovel, the penetration clearance angle, the curvature of the shovel handle, the angle between the fertilizer baffle and the fertilizer pipe wall, the angle between the fertilizer pipe and the horizontal plane, and the forward speed are precisely determined. Moreover, this study explores the quantitative relationship between the fertilizer discharge amount of the fertilizer applicator and the effective working width. Simultaneously, this research mainly focuses on analyzing the impact of the forward speed on the operational effect of layered and variable-rate fertilization. Through a series of field experiments, it was conclusively determined that the optimal fertilization effect was attained when the forward speed was set at 6 km/h. Under this condition, the average deviation in the fertilization amount was merely 2.76%, and the average coefficients of variation in the fertilizer amount uniformity in each soil layer were 7.62, 6.32, 6.06, and 5.65%, respectively. Evidently, the experimental results not only successfully met the pre-set objectives, but also fully satisfied the design requirements. Undoubtedly, this article can offer valuable methodological references for the research and development of fertilization devices tailored for diverse crops cultivated on saline–alkali lands. Full article

To reveal the changes in crop yield and contribution rate of black soil productivity under long-term different fertilization conditions in black soil areas and to find the important significance of fertilization for sustainable and stable crop yield, high yield, and improving the contribution rate of black soil nutrients. Based on the long-term experiment of black soil fertility in Harbin, the Ministry of Agriculture and Rural Affairs, under the maize–wheat–soybean rotation system, crop yield, sustainability and stability of yield, the contribution rate of black soil productivity, and natural nutrient supply capacity under 10 fertilization treatments (CK, NP, NK, PK, NPK, M, MNP, MNK, MPK, and MNPK) were analyzed. Results showed that, compared with the treatment of chemical fertilizer, yields of maize, wheat, and soybeans increased under treatment of organic fertilizer combined with chemical fertilizer, among which the yields of maize and wheat changed the most. As the rotation period lengthened, the sustainable yield index (SYI) values of chemical fertilizer treatment and its combination with organic fertilizer treatment gradually decreased. During the rotation period, the SYI value follows: chemical fertilizer combined with organic fertilizer > chemical fertilizer > organic fertilizer. The coefficient of variation (CV) of yield stability showed an overall trend of increasing first and then decreasing, with individual treatments showing a gradual increasing trend (NP and NPK; MNP and MNPK). Under different rotation periods, the overall contribution rate of soil productivity of long-term organic fertilizer combined with chemical fertilizer treatment was higher than that of single chemical fertilizer treatment. With the extension of the rotation period, the contribution rate of soil productivity of NPK treatment was higher and slightly increased, while other treatments showed a downward trend. Although the contribution rate of soil productivity of organic–inorganic fertilizer combined treatment (MNP and MNK) showed a downward trend, it still remained at a high level (97.2% and 95.9%). In addition, the black soil has strong phosphorus and potassium supply capacity; nitrogen was lower than those two elements, with an average natural potassium supply capacity of 94.0–97.1%. Therefore, the combination of organic and inorganic fertilizers is one of the most effective fertilization measures to stabilize crop yield in the black soil region. Nitrogen fertilizer, as a limiting factor for crop growth in the black soil region, should be emphasized in its application. Full article

Ammonium (NH₄⁺) content is one of the most important parameters in manure assessment. The accurate and rapid determination of this inorganic form of nitrogen is therefore important not only in agronomy, when calculating fertilizer application rates, but also in scientific studies, for example, in the study of greenhouse gas emissions from stored manure. There is not enough research to assess which analytical method is the most appropriate for the determination of (NH₄⁺) in manure with additives such as perlite, vermiculite, or peat. We compared three analytical methods for NH₄⁺ determination: distillation, ionometry, and spectrophotometry. The results showed that the distillation method had the lowest average coefficient of variation (Cv) between the two laboratory replicates, with a Cv = 0.77%, while the ionometry and spectrophotometry methods had average Cv values of 1.83% and 3.97%, respectively. A lower coefficient of variation indicates that the analytical method is less sensitive to various interferences, resulting in more reliable data. Experimental data also show that storing manure for 40 days reduces the NH₄⁺ content from about 21,000 ppm to about 7000 ppm and that the use of additives such as perlite, vermiculite, or peat did not significantly affect NH₄⁺ retention compared with control samples (without additives). Based on the results of our study, we recommend using the distillation method for the determination of NH₄⁺ in the manure with additives in agrochemical and scientific laboratories. Full article

Considerable variation in soil often occurs within and across production fields, which can significantly impact farming input management strategies. Optimizing resource utilization while enhancing crop productivity is critical for achieving Sustainable Development Goals (SDGs). This paper proposes a low-cost retrofittable Variable Rate Applicator Controller (VRAC) designed to leverage soil variability and facilitate the adoption of Variable Rate Technologies. The controller operates using a Raspberry Pi platform, RTK—Global Navigation Satellite System (GNSS), a stepper motor, and an anti-slip wheel encoder. The VRAC allows precise, on-the-fly control of the Variable Rate application of farming inputs utilizing an accurate GNSS to pinpoint geographic coordinates in real time. A wheel encoder measures accurate distance travel, providing a real-time calculation of speed with a slip-resistant wheel design for precise RPM readings. The Raspberry Pi platform processes the data, enabling dynamic adjustments of variability based on predefined maps, while the motor driver controls the motor’s RPM. It is designed to be plug-and-play, user-friendly, and accessible for a broader range of farming practices, including seeding rates, dry fertilizer, and liquid fertilizer application. Data logging is performed from various field sensors. The controller exhibits an average of 0.864 s for rate changes from 267 to 45, 45 to 241, 241 to 128, 128 to 218, and 218 to 160 kg/ha at speeds of 8, 11, 16, 19, 24, and 32 km/h. It has an average coefficient of variation of 4.59, an accuracy of 97.17%, a root means square error (RMSE) of 4.57, an R square of 0.994, and an average standard deviation of 1.76 kg for seeding discharge. The cost-effectiveness and retrofitability of this technology offer an increase in precision agriculture adoption to a broader range of farmers and promote sustainable farming practices. Full article

The Northeastern Black Soil Region in China is recognized as one of the three major black soil regions globally and is often regarded as a cornerstone of national food security. However, prolonged agricultural practices have led to increasingly severe soil degradation, and the mechanisms and driving factors behind the degradation of soil quality remain unclear. Therefore, this study examines the historical and current characteristics of soil quality, focusing on major influencing factors, such as the 70-year history of reclamation and climate change. By accessing different databases, reviewing the relevant literature, and performing Pearson correlation and redundancy analyses (RDA), this study investigated the variation patterns of significant soil quality indicators and their driving factors in the 0–20 cm soil layer along the latitudinal direction (Nenjiang, Beian, Hailun, and Harbin) in the typical black soil region of Northeast China. The main conclusions are as follows: the soil organic matter (SOM) content experienced a rapid decline in the 30 years preceding cultivation (1950~1980), with the greatest decline rate in the Beian area (about 1.10 g/kg per year). The SOM in the Beian, Hailun, and Harbin areas decreased from north to south, changing at rates of 9.40–21.67 g/kg/degree and 0.15–0.34 g/kg/m with latitude and elevation, respectively. Elevation impacts the annual rate of change in soil quality indicators through its influence on the annual mean maximum temperature (AMXT) and annual atmospheric pressure (AP). AMXT and AP exhibit a linear relationship with elevation, based on which regression models were established. The key factors influencing soil quality indicators in the black soil region include cultivation years (Y), annual mean maximum and minimum temperatures (AMXT and AMNT), annual relative humidity (ARH), and AP. An increase in chemical fertilizer application is among the critical factors affecting soil pH. Additionally, the extensive use of agricultural machinery can reduce soil porosity and cause water and salt accumulation, ultimately leading to a decline in soil pH. This study offers theoretical support for mitigating soil degradation in Northeast China’s black soil region, thereby contributing to national food security and promoting sustainable development. Full article