Planting Patterns Research Articles

Application of Jarwo Planting System and Fertiphos Fertilizer on The Growth and Yield of Black Rice Mutant M4

This study aims to examine the interaction between the dose of Fertiphos fertilizer and the JARWO (JARWO) planting pattern on the growth and yield of black rice mutant rice. The experiment was conducted in Jorong Labuah, Agam Regency, and the Seed Science and Technology Laboratory, Andalas University, Padang, from February to June 2024. A Completely Randomized Design (CRD) with two factors was used, namely the JARWO planting system (2:1, 3:1, 4:1) and the dose of Fertiphos fertilizer (0 kg/ha, 100 kg/ha, 200 kg/ha, 300 kg/ha). Data were analyzed using the F test at the 5% level, followed by Duncan's New Multiple Range Test (DNMRT) if significant. The results showed a significant interaction between the dose of Fertiphos fertilizer and the JARWO planting pattern on the growth and yield of black rice mutant rice. Fertiphos fertilizer dose of 200 kg/ha gave the best results on the total number of grains per panicle, the number of filled grains per panicle, the total weight of grains per panicle, and the weight of filled grains per clump. The JARWO 2:1 planting pattern gave the best results on the total number of tillers, the total number of grains per panicle, the number of filled grains per panicle, and the total weight of grains per panicle.

Distribution, species richness, and relative importance of different plant life forms across drylands in China

Studies on plant diversity are usually based on the total number of species in a community. However, few studies have examined species richness (SR) of different plant life forms in a community along large-scale environmental gradients. Particularly, the relative importance (RIV) of different plant life forms in a community and how they vary with environmental variables are still unclear. To fill these gaps, we determined plant diversity of ephemeral plants, annual herbs, perennial herbs, and woody plants from 187 sites across drylands in China. The SR patterns of herbaceous plants, especially perennial herbs, and their RIV in plant communities increased with increasing precipitation and soil nutrient content; however, the RIV of annual herbs was not altered along these gradients. The SR and RIV of ephemeral plants were affected mainly by precipitation seasonality. The SR of woody plants had a unimodal relationship with air temperature and exhibited the highest RIV and SR percentage in plant communities under the harshest environments. An obvious shift emerged in plant community composition, SR and their critical impact factors at 238.5 mm of mean annual precipitation (MAP). In mesic regions (> 238.5 mm), herbs were the dominant species, and the SR displayed a relatively slow decreasing rate with increasing aridity, which was mediated mainly by MAP and soil nutrients. In arid regions (< 238.5 mm), woody plants were the dominant species, and the SR displayed a relatively fast decreasing rate with increasing aridity, which was mediated mainly by climate variables, especially precipitation. Our findings highlight the importance of comparative life form studies in community structure and biodiversity, as their responses to gradients differed substantially on a large scale.

Competition for nutrient niches within the apple blossom microbiota antagonizes the initiation of fire blight infection.

Changes in the plant microbiota composition are intimately associated with the health of the plant, but factors controlling the microbial community in flowers are poorly understood. In this study, we used apple flowers and fire blight as a model system to investigate the effects of floral microbiota and microbial competition on disease development and suppression. To compare changes in microbial flora with the RNA expression patterns of plants, the flower samples were collected in three different flowering stages (Bud, Popcorn, and Full-bloom). Using advanced sequencing technology, we analyzed the data and conducted both in vitro and in vivo experiments to validate our findings. Our results show that the Erwinia amylovora use arabinogalactan, which is secreted on the flowers, for early colonization of apple flowers. Pantoea agglomerans was more competitive for arabinogalactan than E. amylovora. Additionally, P. agglomerans suppressed the expression of virulence factors of E. amylovora by using arabinose, which is a major component of arabinogalactan, which induces virulence gene expression. The present data provide new insights into developing control strategies for diverse plant diseases, including fire blight, by highlighting the importance of nutrients in disease development or suppression.

Ant sharing by plant species bearing extrafloral nectaries has a low impact on plant herbivory in a tropical system

Abstract Plant species bearing extrafloral nectaries (EFNs) may indirectly influence other plant species by sharing protective ants, potentially altering herbivory levels. However, the propagation of indirect effects in this type of mutualism has seldom been investigated. We investigated indirect effects via ant sharing among 21 EFN‐bearing plant species of the tribe Bignonieae distributed on 28 plots in the central Brazilian Amazon. We used an ecological network index to quantify potential indirect effects among plant species through shared dominant and subordinate ant species. Plant species that were more attractive to ants (promoter species) had the highest potential to indirectly influence ant visitation to less attractive plant species (receptor species) in the community, primarily through changes in the attraction of dominant ant species. However, these potential indirect effects did not result in significant differences in herbivory patterns among the studied plants. Ant attendance and herbivory levels were similar among promoter species, neighbouring plants, and non‐neighbouring plants. Unlike other mutualisms involving plants (e.g., pollination), the indirect effects among plant species that share protective ants had limited consequences. The low levels of herbivory and the small foraging areas of shared ant defenders could be responsible for the observed limited impact of indirect interactions among plant species in this system. Synthesis: This study demonstrates that plant species with EFNs can indirectly influence other plant species through ant sharing. The attractiveness of certain plants to ants enables them to affect the ant visitation patterns of less attractive plants in the community. However, these indirect effects did not significantly alter herbivory levels among plants. Overall, this study advances ecological understanding by showing that the sharing of protective ants among plant species can in some cases confer limited costs and benefits, leading indirect interactions to have minimal impact on herbivory patterns.

Diversity patterns of herbaceous community in environmental gradients of dehesa ecosystems

Dehesa is a unique ecosystem associated with high biodiversity, that integrates trees, livestock, and pasture, making agro-pastoral production compatible with sustainability. However, in the last few decades, a manifold of factors have caused a decline in tree vitality, density, and coverage, leading to long-term changes in species composition and ecosystem structure. This study aims to determine changes in the diversity of the herbaceous plant community in relation to environmental characteristics, the phytosanitary state of the holm oak (Quercus ilex L. subsp. ballota (Desf.) Samp.), and possible interactions with biotic agents, including Phytophthora cinnamomi. For this purpose, the floristic composition and alpha diversity of the understory were assessed in two dehesa stands in Southern Spain. Additionally, the spatial heterogeneity (beta diversity) patterns of herbaceous plants were evaluated in relation to a climatic gradient and subplot orientation at the regional, plot, tree, and subplot scales. Our findings show that microsite features and climate substantially impact the herbaceous plant community in dehesa stands. Annual precipitation is a crucial factor affecting the diversity and biomass of herbaceous plants on a broader, regional scale, consistent with its role as a limiting factor in the Mediterranean climate. However, site-level differences, such as soil clay content and plot slope angle, positively correlate with plant biodiversity, growth, and richness, varying with the Biodiversity Index considered. Moreover, microsites resulting from the combined effects of plot and tree are the main drivers of dissimilarities between samples, as expressed by beta diversity. Contrary to our initial hypothesis, our results reveal no significant association between tree health and herbaceous biodiversity decline.

Investigating the impact of dietary guidelines transition on cardiometabolic risk profile: a forensic analysis using diet quality metrics

Evaluating dietary guidelines using diet quality (DQ) offers valuable insights into the healthfulness of a population’s diet. We conducted a forensic analysis using DQ metrics to compare the Malaysian Dietary Guidelines (MDG-2020) with its former version (MDG-2010) in relation to cardiometabolic risk (CMR) for an adult Malaysian population. A DQ analysis of cross-sectional data from the Malaysia Lipid Study (MLS) cohort (n = 577, age: 20-65yrs) was performed using the healthy eating index-2015 (HEI-2015) framework in conformation with MDG-2020 (MHEI2020) and MDG-2010 (MHEI2010). Of 13 dietary components, recommended servings for whole grain, refined grain, beans and legumes, total protein, and dairy differed between MDGs. DQ score associations with CMR, dietary patterns and sociodemographic factors were examined. Out of 100, total DQ scores of MLS participants were ‘poor’ for both MHEI2020 (37.1 ± 10.3) and MHEI2010 (39.1 ± 10.4), especially among young adults, males, Malays, and those frequently ‘eating out’ as well as those with greatest adherence to Sugar-Sweetened Beverages pattern and lowest adherence to Food Plant pattern. Both metrics shared similar correlations with CMR markers, with MHEI2020 exhibiting stronger correlations with WC, BF%, TG, insulin, HOMA2-IR, and smallLDL than MHEI2010, primarily attributed to reduced refined grain serving. Notably, participants with the highest adherence to MHEI2020 scores exhibited significantly reduced odds for elevated TG (AOR 0.44, 95% CI 0.21–0.93, p = 0.030), HOMA2-IR (AOR 0.44, 95% CI 0.21–0.88, p = 0.022), and hsCRP (AOR 0.54, 95% CI 0.31–0.96, p = 0.040, compared to those with the lowest adherence. Each 5-unit increase in MHEI2020 scores reduced odds for elevated BMI (− 14%), WC (− 9%), LDL-C (− 32%), TG (− 15%), HOMA2-IR (− 9%) and hsCRP (− 12%). While MHEI2020 scores demonstrated better calibration with CMR indicators, the overall sub-optimally ‘poor’ DQ scores of this population call for health promotion activities to target the public to achieve adequate intake of healthful fruits, non-starchy vegetables and whole grain, and moderate intake of refinedgrain, added sugar and saturated fat.

A Novel Hierarchical Clustering Sequential Forward Feature Selection Method for Paddy Rice Agriculture Mapping Based on Time-Series Images

Timely and accurate mapping of rice distribution is crucial to estimate yield, optimize agriculture spatial patterns, and ensure global food security. Feature selection (FS) methods have significantly improved computational efficiency by reducing redundancy in spectral and temporal feature sets, playing a vital role in identifying and mapping paddy rice. However, the optimal feature sets selected by existing methods suffer from issues such as information redundancy or local optimality, limiting their accuracy in rice identification. Moreover, the effects of these FS methods on rice recognition in various machine learning classifiers and regions with different climatic conditions and planting structures is still unclear. To overcome these limitations, we conducted a comprehensive evaluation of the potential applications of major FS methods, including the wrapper method, embedded method, and filter method for rice mapping. A novel hierarchical lustering sequential forward selection (HCSFS) method for precisely extracting the optimal feature set for rice identification is proposed. The accuracy of the HCSFS and other FS methods for rice identification was tested with nine common machine learning classifiers. The results indicated that, among the three FS methods, the wrapper method achieved the best rice mapping performance, followed by the embedded method, and lastly, the filter method. The new HCSFS significantly reduced redundant features compared with eleven typical FS methods, demonstrating higher precision and stability, with user accuracy and producer accuracy exceeding 0.9548 and 0.9487, respectively. Additionally, the spatial distribution of rice maps generated using the optimal feature set selected by HCSFS closely aligned with actual planting patterns, markedly outperforming existing rice products. This research confirms the effectiveness and transferability of the HCSFS method for rice mapping across different climates and cultivation structures, suggesting its enormous potential for classifying other crops using time-series remote sensing images.

Transgenerational effects of stress on reproduction strategy in the mixed mating plant Lamium amplexicaule

BackgroundThe theory of Condition Dependent Sex predicts that – everything else being equal – less fit individuals would outcross at higher rates compared with fitter ones. Here we used the mixed mating plant Lamium amplexicaule, capable of producing both self-pollinating closed flowers (CL), alongside open flowers (CH) that allow cross pollination to test it. We investigated the effects of abiotic stress – salt solution irrigation – on the flowering patterns of plants and their offspring. We monitored several flowering and vegetative parameters, including the number and distribution of flowers, CH fraction, and plant size.ResultsWe found that stressed plants show an increased tendency for self-pollination and a deficit in floral and vegetative development. However, when parentally primed, stressed plants show a milder response. Un-stressed offspring of stressed parents show reversed responses and exhibit an increased tendency to outcross, and improve floral and vegetative development.ConclusionsIn summary, we found that stress affects the reproduction strategy in the plants that experienced the stress and in subsequent offspring through F2 generation. Our results provide experimental evidence supporting a transgenerational extension to the theories of fitness associate sex and dispersal, where an individual’s tendency for sex and dispersal may depend on the stress experienced by its parents.

Sugarcane/Soybean Intercropping with Reduced Nitrogen Application Synergistically Increases Plant Carbon Fixation and Soil Organic Carbon Sequestration.

Sugarcane/soybean intercropping and reduced nitrogen (N) application as an important sustainable agricultural pattern can increase crop primary productivity and improve soil ecological functions, thereby affecting soil organic carbon (SOC) input and turnover. To explore the potential mechanism of sugarcane/soybean intercropping affecting SOC sequestration, a two-factor long-term field experiment was carried out, which included planting pattern (sugarcane monocropping (MS), sugarcane/soybean 1:1 intercropping (SB1), and sugarcane/soybean 1:2 intercropping (SB2)) and nitrogen addition levels (reduced N application (N1: 300 kg·hm-2) and conventional N application (N2: 525 kg·hm-2)). The results showed that the shoot and root C fixation in the sugarcane/soybean intercropping system were significantly higher than those in the sugarcane monocropping system during the whole growth period of sugarcane, and the N application level had no significant effect on the C fixation of plants in the intercropping system. Sugarcane/soybean intercropping also increased the contents of total organic C (TOC), labile organic C fraction [microbial biomass C (MBC) and dissolved organic C (DOC)] in the soil during the growth period of sugarcane, and this effect was more obvious at the N1 level. We further analyzed the relationship between plant C sequestration and SOC fraction content using regression equations and found that both plant shoot and root C sequestration were significantly correlated with TOC, MBC, and DOC content. This suggests that sugarcane/soybean intercropping increases the amount of C input to the soil by improving crop shoot and root C sequestration, which then promotes the content of each SOC fraction. The results of this study indicate that sugarcane/soybean intercropping and reduced N application patterns can synergistically improve plant and soil C fixation, which is of great significance for improving crop yields, increasing soil fertility, and reducing greenhouse gas emissions from agricultural fields.

Effects of intercropping with Fenlong tillage “145” mode on ratoon sugarcane photosynthesis, growth, and yield

AbstractSoil compaction and resource competition are bottlenecks in the improvement of sugarcane productivity in intercropping systems. Fenlong tillage improves crop yields by alleviating soil compaction and ensuring water supply. Wide‐narrow rows are an effective solution for light competition. An efficient intercropping system with Fenlong tillage technology as the core needs to be constructed. A two‐cycle field study was conducted to investigate the effects of planting methods [sole ratoon sugarcane (S) and ratoon sugarcane‐soybean intercropping (I)] combined with tillage [conventional rotary tillage (RT), Fenlong tillage “145” mode (FL145)] on soil physical characteristics, photosynthesis, and growth of ratoon sugarcane, as well as crop yields. For the ratoon sugarcane, compared to RT‐I, FL145‐I decreased bulk density and increased porosity in the 0–40 cm soil layer. Root growth parameters were improved under FL145‐I in the 0–20 cm soil layer. FL145‐I positively affected the stomatal conductance, causing increases in the net photosynthetic and transpiration rates. The increased leaf area index, chlorophyll relative content, and photosynthesis under FL145‐I caused higher dry matter accumulation. The increased single stalk weight under FL145‐I resulted in 17.13%–22.55% higher stalk yield with similar quality. Intercropping under the wide‐narrow row planting pattern had no negative effects on the growth and stalk yield of ratoon sugarcane. For the soybean, compared to RT‐I, the increased 100‐seed weight under FL145‐I resulted in 11.14% higher seed yield with similar quality. Therefore, FL145‐I presents a promising and novel management practice for sustainably increasing ratoon sugarcane productivity in China.

Rediscovering the location of agricultural production: Spatial linkage of farmland use intensity and labor opportunity costs in Central China

Agricultural location theory was the earliest work to reveal the land use and agricultural layout of urban suburbs; however, there is an increasing difference between Dunn's theoretical model and modern agricultural layouts, and there is thus an urgent need to establish new theoretical relationships. In this work, we sought to reveal new patterns of modern suburban agricultural land use using remote sensing data and land economics knowledge. We used remote sensing data to obtain first-hand land-use information while considering the attractiveness of the urban center to labor, and we explored the impact of agricultural opportunity costs on agricultural land use. We found that agricultural land use in suburbs in Central China have four obvious layers: dominance of built-up areas, dominance of single cropping, dominance of double cropping, and dominance of triple cropping. From the perspective of planting patterns, with increasing distance from the city center, the proportion of single-cropping areas decreases from 60% to 20%, that of double-cropping areas increases from 20% to 70%, that of triple-cropping areas always remains below 10%, and the multiple-cropping index increases from 120% to 180%. From the perspective of land economics and considering labor cost, planting profits decrease with increasing distance from the city center. The increasing attractiveness of the urban center to migrant workers significantly weakens farmers' willingness to plant. From the perspective of the circle structure, before 2000, farmers' planting profits were higher than the opportunity costs in all regions; after 2000, farmers with arable land within a 40-km radius of the center may have been more inclined to choose farming, while those with land outside this 40-km radius may have been more inclined to work elsewhere. Under changing agricultural policies, farmers' planting profits increased to a historical high, but profits became negative in all regions after 2015, and the willingness of people to farm reached a historical low. With this work, we continue the development of the hierarchical structure model of The Location of Agricultural Production and summarize new laws of modern agricultural land use from the perspectives of remote sensing data and land economics, supplementing and enriching agricultural location theory.

MATNet: multiattention Transformer network for cropland semantic segmentation in remote sensing images

ABSTRACT Remote sensing image semantic segmentation methods have become the main approach for extracting cropland information. However, in the mountainous regions of southwestern China, croplands exhibit narrow and fragmented shapes, as well as complex planting patterns, making it difficult for traditional semantic segmentation methods to accurately delineate fine-grained cropland boundaries. To address these challenges, a multiattention Transformer network named MATNet is proposed in this paper, for fine-grained extraction of cropland at the parcel level in complex scenes. MATNet built upon the fusion of CNN encoder and Transformer decoder. In the encoder, spatial and channel reconstruction units are introduced, reducing information redundancy in the convolutional layers. The Transformer decoder incorporates multiple attention mechanisms, this design feature enhances the attention window's perception of local content and improves the model's ability to extract features from fine-grained cropland parcels through optimized computationnal al location. Taking the experimental results of the Dali cropland dataset as an illustration, MATNet achieved the highest values across five evaluation metrics, including mIoU. Specifically, the Recall, F1, and mIoU scores were 94.68%, 94.69%, and 89.92%, respectively. Compared with six other advanced models, MATNet consistently performed best in terms of extracting fine-grained cropland parcels.

Mixed Eucalyptus plantations enhance soil organic carbon accumulation and chemical stability through soil microbial community and multifunctionality

Forest conversion can impact soil organic carbon (SOC) fixation and ecosystem functions. The newly proposed “evenness of SOC chemical components” index can indicate the permanence of stored SOC during environmental disturbances. However, how the mixing of tree species impacts SOC accumulation and persistence and changes in soil microbial communities and multifunctionality remain unknown. Thus, we conducted a field experiment (11 years) of monospecific Eucalyptus urophylla × E. grandis plantation for evaluating the influences of the mixed planting of a non-nitrogen (N)-fixing tree, Castanopsis hystrix, and an N-fixing tree, Dalbergia odorifera, on SOC accumulation and chemical stability. Compared with pure plantations, mixed Eucalyptus plantations (particularly those mixed with D. odorifera) exhibited significantly increased SOC concentrations by 28.60–33.71 % and increased SOC chemical component evenness by 3.96–4.67 % (P < 0.05). We also found that the concentrations and chemical component evenness of SOC were strongly linked with litter quality, soil N, phosphorus and their availability, multifunctionality, microbial activity, carbon use efficiency (CUE), biomass, diversity, and network complexity. Furthermore, tree species mixing increased litter quality, soil nutrient availability, microbial biomass, activity, diversity, CUE, and network complexity. Soil microbial anabolism, community characteristics and multifunctionality influenced the SOC concentrations and SOC chemical components evenness. Specifically, microbial diversity enhanced the concentrations and chemical component evenness of SOC by increasing network complexity and soil multifunctionality. These findings revealed differential responses and mechanistic controls of SOC accumulation and chemical stability in different Eucalyptus planting patterns. Overall, mixed plantations, particularly those in which N-fixing species were introduced, effectively improved SOC accumulation and stabilization by positively altering soil quality and microbial properties, potentially representing a sustainable forestry management strategy to improve soil C benefits and multifunctionality in forest ecosystems.

Integrated approach for seismic wave prediction and structural evaluation of Oya tuff quarry underground spaces: Field observations and numerical modeling

This study evaluates the structural stability of large underground spaces in seismic conditions, represented by the Oya underground stone mining plant. By directly monitoring the seismic response of the underground mining site, significant earthquake activities at the plate boundaries of the Tokyo region and Ibaraki Prefecture offshore area were observed. Additionally, through an in-depth analysis of seismic records from different locations within the underground structure, the dynamic characteristics and motion patterns of the Oya underground stone mining plant were revealed, revealing its movement trajectory during earthquakes. Additionally, this study innovatively applied seismic waves measured at the original site as input parameters and artificially generated seismic waves based on their response spectra. A numerical analysis was performed after ensuring the model's high correlation with the original site was met. The findings demonstrate that the results of both parameter input methods are confirmable and valuable. Under severe seismic conditions, instability was observed in some regions of the underground mining site. The study also discusses the location and damage mechanisms of the mining site's structure under seismic effects, providing valuable insights for the safety assessment of similar large underground spaces and proposing new approaches for selecting input parameters in seismic analysis.

Soil moisture prediction based on integrating the CEEMDAN decomposition technique with LSTM in the proximity of Prosopis Juliflora

Human-made adaptations in plant diversity, particularly the introduction of alien invasive plant species, can result in problems such as depletion of groundwater, extraction of natural water resources, and modifications in the local biodiversity. In addition to regulating ecosystems and accurate farming, precise forecasting of soil moisture in the vicinity of these exotic plant species can greatly assist in various other agricultural applications. In this study, we present an improved approach for predicting soil moisture levels at different depths in the vicinity of Prosopis Juliflora (IAPS) by integrating long short-term memory (LSTM) and complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN). CEEMDAN is employed as a preprocessing and denoising technique to decompose the initial soil moisture data into several intrinsic mode functions (IMF). After that, LSTM is used to predict all the IMF (Intrinsic Mode Function) parts from the CEEMDAN process. The individual prediction outcomes of each IMF are combined to obtain the final prediction results. Soil moisture measurements were collected continuously in the Coimbatore area of Tamil Nadu at multi-layer soil depths of 10 cm, 30 cm, 60 cm, and 100 cm. The provided data was utilized for training models and achieving optimal accuracy in forecasting soil moisture levels one month prior. The proposed CEEMDAN-LSTM model achieved the highest R2, ranging from 0.985 to 0.995 at various depths when compared to RNN, LSTM, EMD-LSTM, EEMD-LSTM models, and existing literature models. The results show that the proposed method works well at predicting soil moisture at different depths, which can help improve the planting pattern and schedule of native species to increase the area’s green cover.

Crop mapping and quantitative evaluation of cultivated land use intensity in Shandong Province, 2018–2022

AbstractIndustrialization and urbanization have intensified land‐use pressures on agroecosystems. Monitoring cultivated land use intensity (CLUI) is crucial for implementing sustainable agriculture. However, current agroecosystem management in Shandong Province lacks high‐resolution CLUI information. To address this gap, this study measured and analyzed CLUI at a 1‐km scale in Shandong Province from 2018 to 2022, using self‐produced crop maps and the human appropriation of net primary production (HANPP) framework. The spatial autocorrelation model was used to analyze the spatiotemporal pattern and aggregation characteristics of cultivated land use intensity. The influencing factors of CLUI were analyzed using the propensity score matching method, which helps reduce the interference of confounding factors. The results are as follows: (1) The wheat‐maize planting pattern in Shandong Province has remained relatively stable, with a notable trend toward intensified cultivation in the western region. (2) CLUI exhibited notable spatial and temporal heterogeneity, with low and medium values predominantly located in the western region. CLUI increased from 1.13 to 1.24, exceeding the global average of 0.84. (3) CLUI showed significant spatial aggregation characteristics. In 2018, 2020, and 2022, the western region was mainly characterized by high‐high and high‐low types. In 2019 and 2021, it was mainly characterized by the low‐low type, with less prevalence of low‐high type. The center of gravity of high‐high and low‐high types shifted southwest, whereas that of high‐low and low‐low types shifted northeast. (4) Chemical fertilizers, pesticides, and plastic mulch exhibited significant positive correlations with CLUI, whereas temperature and precipitation showed significant negative correlations. Favorable natural conditions can mitigate human interference, leading to lower CLUI.

Effects of Restricted Irrigation and Straw Mulching on Corn Quality, Soil Enzyme Activity, and Water Use Efficiency in West Ordos

Groundwater overexploitation in West Ordos necessitates sustainable irrigation practices. This study evaluated three irrigation levels—W1 (3300 m3 · ha−1), W2 (2850 m3 · ha−1), and W3 (2400 m3 · ha−1)—by modifying the wide-width planting pattern of maize. Additionally, two levels of straw mulch were analyzed: F1 (9000 kg · ha−1) and F2 (no mulch). The study aimed to investigate the effects of these treatments on corn growth dynamics, soil water temperature, soil enzyme activity, yield, grain quality, and water use efficiency. The results indicated a decline in growth indices, enzyme activities, grain quality, and yield under the limited irrigation levels W2 and W3 compared to W1. The highest corn yields were observed with W1F1 (6642.54 kg · ha−1) and W2F1 (6602.38 kg · ha−1), with the latter showing only a 0.6% decrease. Notably, water use efficiency in the W2F1 treatment improved by 4.69%, 12.08%, 10.27%, 12.59%, and 12.96% compared to W1F1, W3F1, W1F2, W2F2, and W3F2, respectively. Straw mulch (F1) significantly elevated the soil temperature, increasing the effective accumulated temperature during the growth period by 10.11~85.79 °C, and boosted the soil enzyme activity by 10–25%. Under limited irrigation, the W2 (2850 m3 · ha−1) and F1 (9000 kg · ha−1 straw) treatments achieved the highest water productivity of 2.48 kg·m⁻3, maintaining a high yield of 6602.38 kg · ha−1 while preserving nutrients essential to the corn’s quality. This approach presents a viable strategy for wide-width corn planting in groundwater-depleted regions, offering a scientifically grounded and sustainable water management solution for efficient corn production in West Ordos.

Growth dynamics and climate sensitivities in alpine cushion plants: insights from Silene acaulis in the Swiss Alps

AbstractUnderstanding alpine plants’ growth dynamics and responses to warming is essential for predicting climate change impacts on mountain ecosystems. Here, we examine growth determinants in the alpine cushion plant Silene acaulis in the Swiss Alps, exploring ontogeny, elevation, and climate influences. We collected 40 Silene individuals and 159 individuals from 38 co-occurring alpine species across 2200–3130 m elevations in the Swiss Alps, analyzing age and growth histories through annual growth rings. While comparing growth rates, we found that Silene was relatively slow-growing. However, Silene exhibited a dual growth strategy, initially rapid and then slowing after ~ 20 years, challenging perceptions of its longevity. Similar ontogenetic trends were observed in other alpine species, albeit with variations based on species and elevation. The consistent unimodal growth-elevation pattern in Silene and other alpine plants, peaking at ~ 2400 m, underscores shared environmental constraints on alpine plant growth. Additionally, cross-dating growth ring series and correlating with daily climate data enabled the precise assessment of warming impacts on growth. Silene’s growth is influenced by year-to-year climate variability, with warming-induced moisture stress and overheating during spring and summer adversely affecting its growth. Despite being low-statured, Silene is not completely decoupled from atmospheric influences. The heat-trapping function of Silene, effective in mature and well-formed cushions, makes it susceptible to adverse effects as temperatures rise. This sensitivity raises concerns about the potential dieback of Silene cushions, as witnessed during recent heatwaves, and emphasizes the broader ecological implications for alpine ecosystems, given Silene’s role as a crucial nurse plant.

Analysis of the beneficial effects of prior soybean cultivation to the field on corn yield and soil nitrogen content.

Corn-soybean rotation is a cropping pattern to optimize crop structure and improve resource use efficiency, and nitrogen (N) fertilizer application is an indispensable tool to increase corn yields. However, the effects of N fertilizer application levels on corn yield and soil N storage under corn-soybean rotation have not been systematically studied. The experimental located in the central part of the Songnen Plain, a split-zone experimental design was used with two planting patterns of continuous corn (CC) and corn-soybean rotations (RC) in the main zone and three N application rates of 0, 180, and 360 kg hm-2 of urea in the secondary zone. The research has shown that RC treatments can enhance plant growth and increase corn yield by 4.76% to 79.92% compared to CC treatments. The amount of N fertilizer applied has a negative correlation with yield increase range, and N application above 180 kg hm-2 has a significantly lower effect on corn yield increase. Therefore, a reduction in N fertilizer application may be appropriate. RC increased soil N storage by improving soil N-transforming enzyme activity, improving soil N content and the proportion of soil organic N fractions. Additionally, it can improve plant N use efficiency by 1.4%-5.6%. Soybeans grown in corn-soybean rotations systems have the potential to replace more than 180 kg hm-2 of urea application. Corn-soybean rotation with low N inputs is an efficient and sustainable agricultural strategy.

The Impact of Tree Density on Automated Oil Palm Tree Counting Accuracy

The rapid development of oil palm plantations in Kualuh Leidong Subdistrict, Labuhanbatu Utara District, North Sumatra Province has led to an increased need for effective and efficient monitoring and supervision of oil palm trees. One method that supports such monitoring and supervision is the use of an automatic counting method using orthophoto data. This orthophoto data was used for automatic tree counting using a deep learning method with the Faster R-CNN algorithm. The study considered two planting patterns: regular planting patterns with spacing of 4 to 9 meters, and random planting patterns with varying spacing. Data processing involved an epoch value of 80 and a batch size value of 4. The accuracy of the automatic oil palm tree counting was evaluated based on the density of the spacing between trees with reference to the ground truth. The findings indicated that the deep learning Faster R-CNN algorithm achieved higher accuracy in automatic calculations for regular planting patterns.