In order to systematically evaluate the comprehensive performance of the agronomic traits of maize varieties, this study took the maize varieties (in the high-density group) participating in the summer maize regional trials in Anhui Province from 2011 to 2023 as the research objects. Thirteen key agronomic traits, including plant height, ear height, ear length, ear diameter, bald tip length, 1000-grain weight, and yield, were measured, and a comprehensive evaluation system was constructed through multi-dimensional statistical analysis methods. Firstly, correlation analysis was used to reveal the correlations among traits. The results showed that the yield had an extremely significant positive correlation with the ear diameter and the number of grains per row (r=0.869, (r=0.836), a significant positive correlation with the ear length and the grain yield rate (r=0.626, (r=0.573), and a significant negative correlation with the bald tip length (r=-0.558). Furthermore, principal component analysis was adopted to extract five principal components (with a cumulative contribution rate of 87.96%), which respectively reflected the yield potential, morphological characteristics, and stress resistance, and a comprehensive evaluation model of principal components was constructed. Based on cluster analysis, the varieties were divided into high-yield and stable-yield type (Type I) and wide-adaptability type (Type II). Combined with the grey relational analysis, the relational degrees of various traits with the ideal variety were quantified (relational order: yield > number of rows per ear > ear length > ear diameter > growth period), and the varieties in the years with the best comprehensive performance, namely 2023, 2017, and 2019 (relational degree > 0.82), were screened out. Through the integration of multiple methods, this study established an evaluation model for the agronomic traits of maize varieties, providing a theoretical basis for variety breeding and production promotion.
To accelerate the improvement and renewal of soybean varieties in Shandong Province, increase soybean yield, enhance stress resistance, and promote the sustainable development of the soybean industry, this study used 73 summer soybean varieties developed in Shandong Province from 2019 to 2024 as materials to systematically analyze the evolution trends in major agronomic traits and quality indicators. The results showed that the yields of regional and multi-location trials of recently approved soybean varieties in Shandong Province exhibited extremely significant increasing trends (P=1.1e-6**, P<2.2e-16**); 100-grain weight and growth period also showed extremely significant upward trend (P=2.6e-4**, P=2.4e-4**). Among them, regional trial yield was significantly positively correlated with effective branching (r=0.24, P=0.04), and multi-location trial yield was extremely significantly positively correlated with 100-grain weight and growth period (r=0.46, P<1e-4; r=0.52, P<1e-4). However, overall, the yield potential in regional and multi-location trials showed a declining trend. To reduce the risk of lodging, the plant height and number of main stem nodes of soybean varieties developed in Shandong Province in recent years have been decreased; from a yield-increase perspective, the internode length should be appropriately shortened while reducing plant height to maintain a stable number of main stem nodes. Correlation analysis showed that the number of grains per plant was significantly negatively correlated with protein content (r=-0.24, P=0.046), 100-grain weight was significantly positively correlated with protein content (r=0.27, P=0.02), and the number of effective branches was significantly negatively correlated with fat content (r=-0.24, P=0.046). In summary, increasing the number of effective branches, improving 100-grain weight, and appropriately delaying maturity are key approaches to enhance soybean yield potential in Shandong Province in recent years. In addition, coordinating the relationship between yield and quality is also an important direction in soybean genetic improvement.
This paper aimed to seek the suitable harvesting period for different uses of Zanthoxylum armatum var. Novemfolius, providing reference for enterprises and farmers to determine suitable harvesting time for Z. armatum var. Novemfolius. Z. armatum var. Novemfolius variety ‘Jiuyeqing’ was used as the test material. Samples were collected approximately every 6 days to test yield and quality index, after Z. armatum var. Novemfolius entering fruit expansion period (from April 12th to July 1st). The results showed that the fruit size was increased by 77% at the end of rapid expansion period compared to the beginning of the period. Thousand fruit weight was still increasing after expansion period. By early June, thousand fruit weight was significantly increased by 228% compared to the beginning of the period. The rate of kernel/seed was significantly deceased as a delay of the harvesting period due to increasing seed weight. A mass of volatile oil and amide compounds accumulated after fruit expanded, and content of which showed a rising trend in early stage of harvesting periods and smooth trend in later. In fresh Z. armatum var. Novemfolius, content variations of volatile oil and amide compounds were 0.6-2.8 mL/100 g, 2.5-16.7 mg/g. The total content of main aroma components in volatile oil, such as Linalool, Limonene and Myrcene, increased gradually with the harvest period and then decreased. The trends of total alcohol ketone were rising continuously in early stage and reached the peak at 58.59% on June 19th, and then began to decrease slowly. These conclusions indicate that the suitable time for harvesting Z. armatum var. Novemfolius for sauce is from the end of April to early-May. The suitable time for harvesting fresh Z. armatum var. novemfolius is after early June for better quality, because contents of volatile oil and amide compounds approach or reach the peaks. The suitable time for harvesting Z. armatum var. novemfolius to dry is after late June. The suitable time for harvesting Z. armatum var. novemfolius for oil is mid-July in order to ensure full aroma, numb flavor.
The study aims to compare the population characteristics of Rattus norvegicus and Rattus tanezumi, and provide theoretical basis for their population prediction and scientific prevention and control. In the first half of every month, the rat situation in residential areas, paddy fields and dry farming areas was investigated by night trapping method, and the rat situation of R. norvegicus and R. tanezumi in agricultural areas of Sandu County, Guizhou Province from 2012 to 2024 was compared and analyzed. The results showed that the average weight of R. norvegicus was (98.95±42.37) g, while that of R. tanezumi was (84.95±31.95) g. The weight, carcass weight and body length of R. norvegicus were significantly higher than that of R. tanezumi. The average capture rate of R. norvegicus was 1.17%, which was significantly higher than that of R. tanezumi (0.37%). R. norvegicus had three population peaks in March, June and September, and R. tanezumi had two population peaks in March and June. The reproductive ability of R. norvegicus and R. tanezumi was different in the local area. The average pregnancy rate of R. norvegicus was 15.69%, which was lower than that of R. tanezumi by 23.57%. The average number of offspring of R. norvegicus was 7.89, which was higher than that of R. tanezumi by 5.88. The average testicular decline rate of R. norvegicus was 51.52%, which was lower than that of R. tanezumi by 59.04%. The average fatness of R. norvegicus was 2.65±0.40 g/cm3, which was lower than that of R. tanezumi (2.78±0.45) g/cm3. It can be seen that the morphological characteristics of body weight, body length, tail length and ear height can be used as a reference for identifying and distinguishing R. norvegicus and R. tanezumi, and March, June and September are the key periods for the control of R. norvegicus and Rattus flavipectus.
The study aims to explore the effects of different thicknesses of garden waste branches and leaves on the composition and diversity of soil bacterial communities, and to provide a scientific basis for the resource utilization of urban garden waste and soil ecological management. A controlled experimental design was adopted, with bare soil without garden waste branches and leaves as the control group (S), and four treatment groups with different coverage thicknesses were set up, including 3 cm (A), 5 cm (B), 10 cm (C) and 15 cm (D). High-throughput sequencing technology was used to sequence and analyze the bacterial communities in soil samples from different treatment groups, comparing the differences in bacterial structure, basic functions, and composition distribution among the groups. The results showed that compared with the control group (S), the soil pH value, organic matter content, total nitrogen, available potassium and available phosphorus content increased in all four treatment groups (A to D), indicating that branch and leaf coverage had a significant impact on soil physicochemical properties. With increasing coverage thickness, the number of bacterial species classifications and sequence counts showed an overall increasing trend, demonstrating relatively rich bacterial diversity. Across all treatment levels, the Shannon index increased over time, while the Simpson index initially increased and then decreased. The gene abundance of various bacterial phyla in all treatment groups was higher than that in the control group. Significant differences were observed in both the quantity of bacterial species and the composition of dominant species under different coverage thicknesses. The treatment group with 10 cm coverage (C) showed the highest Shannon and Simpson indices, with the most stable dominant species in the soil bacterial community. At 15 cm coverage (D), the gene abundance of all bacterial phyla reached maximum levels, exceeding 2.0×105. In the control group (S), Pseudomonas was the dominant genus, while in groups with thicker coverage (B, C and D), bacteria such as Streptomyces and Rhizobium gradually became dominant. The study demonstrates that moderate garden waste coverage (5-10 cm) effectively promotes soil bacterial community richness and diversity, whereas excessive coverage may adversely affect bacterial survival.
To protect agricultural land and improve the efficiency of agricultural land use in Pingyin County, a suitability evaluation of agricultural land in Pingyin County was conducted. Based on the data of land use status of the third land survey in Pingyin County, this study selected nine evaluation factors, including topography, soil, water resources, and human and social factors, to construct an evaluation index system. Using the principal component analysis method to determine the factor weight, combined with GIS spatial analysis and natural breakpoint classification method, the suitability evaluation of cultivated land, garden land and forest land in Pingyin County was carried out. The results show that: (1) the proportion of highly suitable farmland in Pingyin County is 33%, concentrated along the northwest bank of the Yellow River and the southeast bank of the Hui River. (2) The proportion of areas suitable for gardens and forests is around 11%, distributed relatively loosely, while the southern central mountainous region is generally less suitable. (3) Due to the influence of mountainous terrain, the suitability of agricultural land varies among townships, with uneven spatial distribution. In particular, more than half of the arable land in Xiaozhi Township is highly suitable. This GIS comprehensive suitability assessment aims to identify potential agricultural land and provide support for scientific planning and optimization of agricultural land spatial layout.
To address the dual challenges of soil degradation caused by long-term chemical fertilizer application in citrus orchards and livestock and poultry waste pollution, this study systematically reviews the biological configuration technologies of grass cultivation in citrus orchards, the assimilation potential of aquaculture waste, and the ecological and productive effects, aiming to construct an " citrus-grass-livestock" ecological recycling model and achieve resource utilization of agricultural waste. The results indicate that: (1) suitable grass species for citrus intercropping should be adapted according to tree age and season; young orchards are suitable for light-loving and high-yield forage grasses (e.g., peanut, ryegrass), while mature orchards prioritize shade-tolerant and dwarf forage grasses (e.g., white clover, bahiagrass); spatiotemporal configuration requires optimization of sowing dates and mowing frequency (ryegrass is suitable for autumn sowing, with 3-4 mowings annually). (2) Significant differences exist in nutrient requirements between citrus and forage grasses; citrus orchards of varying yields can assimilate cattle manure at 9.62-24.04 t/hm² and pig manure at 6.58-16.45 t/hm², while ryegrass demonstrates assimilation capacities of 9.21 t/hm² for pig manure and 13.4 t/hm² for cattle manure. (3) This model significantly improves soil properties (reducing bulk density by 17.26% and increasing organic matter by 39.6%), promotes growth of both citrus and forage grasses, with maximum citrus yield increase of 19.5%, and elevates fruit soluble solids content from 101.1 g/kg to 108.7 g/kg (a 7.6% improvement). In conclusion, the citrus grass cultivation model, through scientific biological configuration, efficiently assimilates livestock waste while simultaneously achieving soil improvement and yield-quality enhancement, representing a circular agriculture model that balances ecological and economic benefits. This study provides theoretical support for the promotion of the "citrus-grass-livestock" model; future research should focus on regional adaptability, long-term application risks, and the establishment of technical standards.
As an important agricultural measure for soil warming and moisture retention, the long-term application of plastic film mulching has drawn much attention for its impact on soil quality. This study took the uncovered area, open-field mulched area and greenhouse mulched area in Xi’an as research objects, and systematically analyzed the regulatory effects of different mulching patterns on soil organic carbon (SOC), dissolved organic matter (DOM) and enzyme activities. The results showed that (1) mulching significantly increased the total nitrogen (TN) and total phosphorus (TP) contents in the surface soil (0-20 cm), with the greatest increase observed in the mulched greenhouse plots. (2) All mulching treatments significantly increased soil organic carbon (SOC) content, especially in the topsoil layer (0-10 cm). (3) The distribution of dissolved organic carbon (DOC) showed spatial differences. In the 0-10 cm soil layer, the DOC content in the open-field mulched plots was lower than that in the non-mulched plots, while in the greenhouse mulched plots, the DOC content was higher than that in the non-mulched plots. In the soil layer of 10 to 30 cm, the DOC content in both mulched soils was higher than that in the non-mulched treatment. (4) Three-dimensional fluorescence spectroscopy revealed that mulching enhanced the fluorescence intensity of the humification component (V region) in DOM, especially in the soil layer of 10 to 20 cm, which had a positive effect on soil humification. (5) Enzyme activity analysis showed that both mulching treatments stimulated the activity of soil β-1,4-glucosidase (BG) and alkaline phosphatase (ALP), and greenhouse mulching also increased the activity of N-acetyl-β-D-glucosaminidase (NAG). The results of this study reveal the effects of the film mulching technology on SOC, DOM and enzyme activity, providing a theoretical basis for the rational use of plastic films and offering technological support for a deeper understanding of the migration and transformation of SOC, DOM and enzyme activity under the influence of film mulching.
To accurately monitor the distribution and scale of rice cultivation, address the needs for rapid assessment of rice yields, agricultural water management, and decision support, this study utilizes domestic satellite data to develop a rapid identification strategy for county-level adaptive rice planting areas. It conducts an in-depth analysis of the scattering characteristics and spectral changes of rice echoes. Combining multi-temporal high-resolution images from the Gaofen-2 satellite with normalized vegetation index (NDVI) and other information, the study initially identifies rice planting areas. Based on this, synthetic aperture radar (SAR) images are used to extract the backscattering characteristics of various ground objects under VV polarization mode, generating time-series feature curves. Savitzky-Golay filtering technology is applied to reduce noise interference. Finally, a random forest classification model is used to extract spatial distribution information of rice planting. This study has specifically designed a rice recognition scheme, achieving a completeness accuracy of 92.65% and a quality of 92.82%, surpassing the precision of conventional foreign satellite recognition methods. The research verifies the technical advantages of domestic satellites in fine crop identification, and provides an efficient solution for food security monitoring, farmland management optimization and disaster loss assessment.
The study aims to solve the problems of rapid deterioration of water environment and susceptibility to diseases in the sole breeding of largemouth black bass or yellow catfish, and to improve the aquaculture efficiency in this area. Based on the ecological niche difference between largemouth black bass and yellow catfish, the self-bred largemouth black bass fries with a specification of 71-83 g/tail and the purchased yellow catfish ‘Quanxiong No.2’ fries with a specification of 25-33 g/tail were used as experimental materials. By setting up double exquisite aquaculture of largemouth black bass and yellow catfish with different feeding densities, implementing targeted feeding strategies, implementing water quality management and disease prevention methods, the double exquisite aquaculture of largemouth black bass and yellow catfish was carried out and comparative experiment of nutritional effects was conducted. The results showed that bacterial hemorrhagic edema disease occurred in the No.3 pond where only yellow catfish were kept, with a survival rate of only 60%, while the survival rate of other experimental groups was above 80%. After about 160 days of breeding, the average sizes of largemouth black bass harvested from ponds 1, 2, 5, and 6 were 557.45g, 556.00 g, 565.33 g, and 571.31 g, with yields of 5663.25 kg, 5237.99 kg, 5359.46 kg, and 5469.22 kg, respectively. The average sizes of yellow catfish harvested from ponds 2, 5, 6, and 3 were 148.67 g, 162.10 g, 170.22 g, and 119.87 g, with yields of 883.64 kg, 727.58 kg, 547.53 kg, and 863.06 kg, respectively. According to the benefit analysis, the income of control pond No.1 is 203580 yuan/hm2; the control pond No.3 incurred a loss of 31507 yuan/hm2; the revenue of experiment pond No.2 is 217579 yuan/hm2, with an increase of 13999 yuan/hm2 compared to experiment pond No.1; the revenue of the experimental pond No.5 is 231221 yuan/hm2, with an increase of 27641 yuan/hm2 compared to the 1st pond; the revenue of the experimental pond No.6 is 233633 yuan/hm2, with an increase of 30053 yuan/hm2 compared to the 1st pond. It can be seen that double exquisite aquaculture has a better effect than single breeding. In pond breeding, it is recommended to release largemouth black bass with a density of about 27000 /hm2 and yellow catfish with a density of 9000-13500 /hm2 to achieve better benefits.
In order to explore a more accurate and effective method for predicting the initial stage of full flowering of rose, based on the observation data and meteorological data in Pingyin County, Shandong Province from 1994 to 2024, the time changing trend of the initial stage of full flowering of rose was analyzed. The key meteorological factors were selected through correlation analysis, which was used to establish the prediction model by BP neural network, and was compared with stepwise multiple linear regression method. Root mean square error (RMSE), relative error (RE) and coefficient of determination (R2) were used to evaluate the prediction accuracy of the model. The results showed that the initial stage of full flowering of rose was advanced in 1994-2024, with an average advance of 0.4 days per 10 years. From 1994 to 2020, 16 meteorological factors were significantly correlated with the ordinal number of the initial stage of full flowering (P<0.01), among which the heat condition in mid-early April was the main meteorological factor affecting the flowering period. The RMSE, RE and R2 of the training set of BP neural network model were 0.75 d, 0.62% and 0.92, and the mean absolute error was 0.44 d. The RMSE, RE and R2 of the stepwise multiple linear regression model were 1.31 d, 1.08%, 0.77, and the mean absolute error was 1.04 d. Both models can forecast the initial stage of full flowering of roses in late April. Data from 2021-2024 were used to verify the prediction effect of the model. The years in which the forecast values of the BP neural network model were consistent with the actual values accounted for 75.0%; the years in which the forecast values of the stepwise multivariate linear regression model were consistent with the actual values accounted for 25.0%. In summary, BP neural network model has better prediction effect than stepwise multiple linear regression model, and has higher reliability and application potential in the initial stage of full flowering of rose forecast.
The simulation of the growth stages of Myrica rubra in protected cultivation is a key aspect in understanding the interaction between the growth of the plant and environmental factors. To explore the impact of the microclimate in protected cultivation on the growth stages of Myrica rubra and accurately predict the evolution of these stages, this study utilized growth and development data of Myrica rubra from 2022 to 2024 in Lanxi of Zhejiang, along with concurrent meteorological data on light, temperature, and other factors. Three methods were employed for the growth stage simulation: growing degree day (GDD), physiological development time (PDT), and the clock model. The models were validated based on their performance. The results indicated that the clock model exhibited higher predictive accuracy and adaptability in simulating the various growth stages of Myrica rubra, particularly during the reddening stage and maturity stages, where the prediction errors were significantly smaller compared to GDD and PDT methods. The root mean square errors (RMSE) for the wintering, flowering, fruit setting, reddening stage, and maturity stages in the clock model were 2.83 d, 3.32 d, 4.24 d, 2.38 d, and 2.16 d, respectively. The normalized root mean square errors (nRMSE) were 0.47, 1.11, 0.47, 0.48, and 0.54, respectively. These results demonstrate that the clock model provides a more accurate reflection of the growth stage evolution of Myrica rubra, offering scientific support for optimizing cultivation management strategies. This can effectively promote the implementation of refined management practices, improving both management efficiency and effectiveness. In the future, the parameters of wintering period can be optimized and extended to multi-variety and multi-region applications.
To address the issue of relying on experience and lacking quantitative simulation tools in the production management of flue-cured tobacco in central Henan, in order to clarify the applicability of WOFOST model in Xuchang flue-cured tobacco production area, the parameter sensitivity analysis was carried out by OAT (one-at-a-time) method, and the localization calibration and independent verification of the model were completed by ' trial and error method '. The study was based on the field observation and meteorological data of Jian'an District and Xiangcheng County of Xuchang, Henan Province from 2021 to 2022, and the model's simulation accuracy for leaf dry weight (WLV), above-ground biomass (AGP), and leaf area index (LAI) was evaluated using the coefficient of determination (R2), consistency index (d), and normalized root mean square error (NRMSE). The main conclusions are as follows. (1) In the calibration of leaf dry weight (WLV), the simulation values from the WOFOST model showed a significant linear relationship with the observed values, indicating high accuracy in simulating leaf dry weight. The calibration accuracy for above-ground biomass (AGP) was also good. However, the calibration of the leaf area index (LAI) was less accurate, with NRMSE ranging from 20% to 30%. (2) The model was validated using data from Xuchang in 2021, Xuchang and Xiangcheng in 2022, and the simulation results were good for the most important biomass, leaf dry weight. Overall, the WOFOST model showed high accuracy in validation. The R2 and consistency index d of 90 % (8 / 9) validation data were higher than 0.8, nearly 80 % (7 / 9) were higher than 0.9, and NRMSE was between 10 % and 20 %. The correlation and consistency between simulated and measured values were good. (3) After calibration and verification, the WOFOST model could effectively simulate the growth process of tobacco in Xuchang, Henan, providing a foundation for quantitative and digital management of tobacco production. Subsequently, remote sensing data can be coupled to carry out research on crop growth monitoring and yield forecasting.
