Plant Density Research Articles

Reduced Nitrogen Application with Dense Planting Achieves High Eating Quality and Stable Yield of Rice.

Rational nitrogen (N) application can enhance yield and improve grain eating quality in rice. However, excessive N input can deteriorate grain eating quality and aggravate environmental pollution, while reduced N application (RN) decreases rice yield. Reduced N application with dense planting (RNDP) is recommended for maintaining rice yield and improving N use efficiency. However, the effects of RNDP on the rice grain eating quality and starch structure and properties remain unclear. A two-year field experiment was conducted to investigate the effects of RNDP on the rice yield, grain eating quality, and starch structure and properties. Compared to conventional N treatment, RN decreased significantly the rice yield, while RNDP achieved a comparable grain yield. Both the RN and RNDP treatments improved significantly the rice eating quality. The high eating quality of RNDP was attributed to increased gel consistency, pasting viscosity, and stickiness after cooking as well as decreased protein content. A further analysis of starch structure and properties revealed that RNDP decreased the relative crystallinity, lamellar intensity, gelatinization enthalpy, and retrogradation enthalpy of starch. Therefore, RNDP achieved a stable rice yield and enhanced rice eating quality. These findings provide valuable insights into obtaining optimal quality and consistent yield in rice production under reduced N conditions.

The use of highly functional phytobiotic additives in the feeding of sturgeon

Growing fish in artificial ecosystems increases the relevance of the issue of intoxication of the body under constant stress with high planting density, as well as the negative impact on the metabolic processes of low-quality feed. This affects the intensity of metabolic processes and reduces productivity, preventing the realization of genetic growth potential. It is possible to increase the efficiency of sturgeon fish cultivation by including phytobiotics in the feed. At the moment, this is a promising area of feed production, since the active ingredients of phytobiotic additives are involved in the protection of feed lipids, preventing autooxidation reactions. At the same time, there is no chemical load and no negative effect on metabolic processes in the body of fish, which positively affects the factor of environmentally safe fish products. Thus, phytobiotics, as natural plant components, have antioxidant properties. During the study, the effectiveness of the Flavitol dietary supplement was tested when introducing various concentrations of the drug into sturgeon feed in addition to vitamin E (50.0 mg/kg). The positive result of using this drug containing dihydroquercin (a flavonoid with high antioxidant activity obtained from Siberian larch) was confirmed by higher growth rates (18.9–22.3% higher than the control group) and survival (100.0%) with a lower feed ratio (1.4 units). The obtained data from physiological and biochemical blood tests indicate a positive effect of the source of dihydroquercetin — dietary supplement Flavitol and vitamin E on the metabolic processes of cultured fish, which is confirmed by the compliance of the ESR level with the normative values (2.03–2.64 mm/h), higher (by 9.4–12.7%) hemoglobin level (58.07–60.32 g/l) and the amount of total whey protein (30.7–32.46 g/l).

Multi-scale hybrid modeling of plant growth in response to environmental conditions and soil nutrients availability

Crop modeling plays a crucial role in agriculture, aiding our understanding and prediction of crop growth and yield in diverse environmental conditions. This study aims to develop a comprehensive mathematical model describing plant growth in response to environmental conditions and soil nutrient availability. To achieve this, we relied on a field experiment with lettuce plants under varying environmental conditions. Employing growth models such as logistic, Gompertz, Aikman & Scaife, and Scaife, Cox & Morris, we assessed the influence of time, day-degrees, and effective-day-degrees across different plant densities and during distinct periods throughout the year. In general, describing plant growth in terms of day-degrees or effective-day-degrees yielded an improved model fit and more precise estimations of growth parameters. As a result, we described the growth of plant length in terms of effective-day-degrees instead of time in the equations of the Bessonov-Volpert system. Additionally, we modified the equation describing plant length growth using previously fitted functions. By incorporating these adjustments, we characterized the one-dimensional growth of plant weight under varying environmental conditions without branching, using the Bessonov-Volpert model. This study contributes valuable insights into crop modeling techniques, refining our understanding of optimizing plant growth under different environmental conditions.

Performance and Evaluation of Hanski 227 Oriental Tobacco in Dak Lak Region, Vietnam from 2022 - 2024

With the results of selecting Oriental tobacco varieties suitable for natural conditions in Vietnam, with potential for raw material quality and raw material production capacity in Vietnam, from 6 oriental tobacco varieties originating from Bulgaria, the Tobacco Institute has been testing in Ninh Thuan province from 2019 to 2021, and Dak Lak from 2021 to 2022. The results of the trial planting show that oriental tobacco varieties are good growth, and are quite suitable for the soil and climate conditions in Ninh Thuan and Dak Lak provinces, and have selected 2 the best oriental tobacco varieties as Basma 16 and Hanski 227. In which, Hanski 227 variety is evaluated to have outstanding prospects due to its good growth ability, high yield, characteristic aroma and good smoking properties. The Hanski 227 variety has less harvested leaves, larger leaf size and mass than Basma 16 variety, so the labor costs for cultivation, harvesting and preliminary processing are lower. To evaluate the ability to expand the oriental area in Vietnam, we continue to trial planting the Hanski 227 oriental variety in Dak Lak in 2023 - 2024, with a fertilizer level and a planting density corresponding to 50N + 30P2O5 + 80K2O (N: NH4NO3, P: (Ca(H2PO4)2 and K: K2SO4) and 110,000 plants/ha. The experimental trial results show the Hanski 227 variety has good growth, high yield, and good quality, with yield fluctuating 1.52 - 1.66 tons/ha, nicotine content: 0.81 - 1.38%, and reducing sugar content: 8.9 - 12.1%, and the oriental material has a characteristic aroma and good smoking properties. Based on the trial results shows that the quality of Hanski 227 grown in Dak Lak are the same the oriental tobacco importing from Bulgaria, Türkiye and Greece. Therefore, the Dak Lak province is the most suitbale region for producing good quality oriental tobacco in Vietnam compared to Ninh Thuan region. Because materials in Ninh Thuan has the high clorua content reducing material quality. In 2025, we continue to grow the Hanski 227 oriental tobacco variety in Dak Lak region on a large area and complete the preliminary processing process, with the goal of producing Oriental tobacco raw materials domestically, with appropriate production costs.

The influence of planting density on the oil and fatty acids content of soybean in hydroponic and soil conditions of the Ararat Valley

Background: Plant seed oils are major renewable resources from nature that can be used in multiple applications. Oils and fats are a vital component of human diets. About 1/3 of the daily energy requirements of a healthy diet come from fats. Each branch of the food industry has its own demands for the fatty acid composition of seed oils. High amounts of polyunsaturated fatty acids are a requirement of healthy diets. However, food manufacturers need highly saturated fatty acids because they need oil that is resistant to high temperatures and oxidation. Soybean oil is second only behind palm oil as the most commercially abundant plant oil globally. Soybean has been recognized for its agricultural importance and their various positive effects on human health. Objective: to identify the quantitative changes of soybean fatty acids depending on the planting density and growing conditions in the Ararat Valley of Armenia. Methods: Soybean was grown in hydroponic and soil conditions of the Ararat Valley. The seeds were sown in the middle of April. Experiments were carried out in hydroponic equipment and soil with different planting densities (30, 50, 70 and 90 plants/m2). The oil content was measured by using the pulsed nuclear magnetic resonance method. The composition of fatty acids in seed oil was analyzed by chromatographic method on "Chromatec Crystal 5000" GC. Results: Oil content ranged from 19.6% to 24.4% in all variants. The maximum content was registered in soil with 30 plant/m2 planting density. Linoleic acid content ranged from 46.35 to 51.28% of the total fatty acid content, regardless of planting density and growing media. The content of linolenic acid ranged from 4.13 to 5.11% in all variants. The maximum content of ω-3 and the minimal content of ω-9 was recorded in hydroponics at 30 plants/m2 planting density. The highest percentage of stearic acid was observed in the soil variant with a planting density of 30 plants/m2. Interestingly, the variants did not differ in the total content of the 5 main fatty acids (98.84-98.95%). Growing medium had no significant effect on the total saturated fatty acids content; in all variants it ranged from 14.29% to 14.83%. Total unsaturated fatty acids content ranged from 85.2% to 85.7%. The hydroponic variant with a planting density of 30 plants/m2 had the lowest ratio of ω-6 and ω-3 fatty acids (10:1). Conclusion: Planting density and growing media had a significant influence on the content of monounsaturated and polyunsaturated fatty acids. Under hydroponic conditions the lowest content of monounsaturated and the highest content of polyunsaturated fatty acids were observed at the lowest planting density (30 plants/m2), which can be used as a functional food for daily consumption. Keywords: Glycine max (L.) Merr., soilless culture, ω-3, ω-6, ω-9, saturated acids.

Unveiling the intricacies of the rice-Rhizoctonia pathosystem: a comprehensive review of host-pathogen interactions, molecular mechanisms, and strategies for sustainable management

Sheath blight disease in rice, induced by the necrotrophic basidiomycetes Rhizoctonia solani, has emerged as a significant menace to global rice cultivation, especially with the widespread adoption of high-yielding varieties. The pathogen’s capacity to endure unfavorable conditions and its wide host range contribute to the increased challenge for management. The occurrence of sheath blight in rice is intensified when high-yielding semi-dwarf cultivars are employed, coupled with dense planting and the application of substantial amounts of nitrogenous fertilizers. Managing this pathogen is a formidable challenge due to its broad host range, substantial genetic variability, and the absence of satisfactory levels of natural resistance in the existing rice germplasm. Due to the absence of complete resistance sources, the predominant approach for managing sheath blight has been through chemical control methods. It is imperative to explore solutions to combat this pathogen, in order to reduce rice yield losses and safeguard global food security. Developing genetic resistance provides an alternative to the use of potentially harmful chemical fungicides. This review crucially delivers efforts to enhance the understanding of the host–pathogen relationship, which involves identification of gene loci/markers associated with resistance responses, modification of host genome through transgenic approaches, examining the wide host range, epidemiology and its managemental approaches. Recent advancements and current research on the R. solani–rice pathosystem, along with a gap analysis, are presented.

Effect of local habitat and landscape attributes on bird communities in shade coffee plantations in the Colombian Andes

Agroforestry is increasingly promoted to support biodiversity conservation by increasing tree cover in agricultural landscapes, but the extent to which landscape context affects how benefits accrue remains uncertain. We used shade-coffee systems to ask how the proximity and extent of forest and forest-agriculture mosaic in the landscape influenced bird communities in 160 coffee plantations that differed in coffee plant density and shade tree richness and abundance in two departments of Colombia with differing regional forest cover. Our findings suggest that regional forest cover and landscape conditions can mediate the response of birds to local habitats on plantations. Avian richness and community completeness was positively related to the amount of forest-agriculture mosaic within landscapes surrounding coffee plantations only within the comparatively forested department of Antioquia (mean 32 % regional forest cover), particularly where plantations had high richness and abundance of trees. In the largely deforested department of Cauca (mean 1 %), neither distance to forest nor cover by forest-agriculture mosaics explained avian richness and community completeness, both of which were positively related only to local tree richness and abundance. We show that biodiversity benefits from increasing habitat quality at local and landscape scales, and habitat quality within plantations becomes increasingly influential as the amount of habitat in the broader landscape declines. Our results emphasize the role of landscape context in conservation planning to promote biodiversity in coffee-growing regions.

Variation of magnesium drives plant adaption to heterogeneous environments by regulating efficiency in photosynthesis on a large scale

Abstract Magnesium (Mg) is a vital nutrient for plants, and its role in photosynthesis, enzyme regulation and resistance to environmental stress is becoming increasingly evident. However, there is a paucity of knowledge regarding the characteristics of Mg (content, density and stock) on a large scale, particularly at the community level, which is essential for linking to ecosystem functions. A leaf‐branch‐trunk‐root‐matched database of the Mg content (mg g−1) and biomass density (g m−2) of plant organs across 1972 sampling sites in China was constructed based on field surveys and data compilation. Using machine learning algorithms, we comprehensively explored the spatial patterns and main influencing factors of plant Mg content and density (g m−2). Furthermore, a new index, leaf Mg productivity (LMP), was developed to determine the Mg use efficiency, defined as the ratio of gross primary productivity to leaf Mg density. The Mg contents in the leaves, branches, trunks and roots were 2.80, 0.87, 0.23 and 1.66 mg g−1, respectively. Deserts exhibited higher Mg content, with the primary influencing factors being high temperatures and soil Mg supply. Higher LMP values observed in grasslands and deserts indicate that Mg use is more efficient in these relatively stressful environments, whereas forests require more Mg for unit biomass productivity. This change was driven by the minimum temperature, aridity and soil Mg content. Synthesis. We systematically explored spatial variation in plant community Mg and its correlation with the photosynthetic capacity of plant communities. The aridity and soil Mg content have negative effects on LMP. This suggests that Mg is used more efficiently in photosynthesis under conditions of resource scarcity, indicating that resources become more valuable when they are limited. Photosynthesis in forests is more sensitive to Mg and more Mg is required for biomass production; therefore, Mg is not just a nutrient but a potential bottleneck in optimizing photosynthetic efficiency. Our findings highlight the pivotal role of Mg in photosynthesis and offer a foundation for optimizing ecosystem management through Mg regulation.

Accelerated development of maize inbred lines suitable for high density through doubled haploid technology

Aim: Doubled haploid technology was utilized to accelerate the development of maize lines with traits suitable for high planting density, enabling the identification of potential parental lines for hybrid development under these conditions. Methodology: Two F1 populations (PML-119 x PML-185 and PML-95 x PML-172) were used to generate doubled haploid lines, confirmed using polymorphic markers phi115 and umc1887. These lines were phenotypically evaluated under high density (60 cm x 15 cm) and normal density (60 cm x 20 cm) conditions. Results: Using doubled haploid technology, 67 lines were developed from two source populations with traits such as narrow leaf angle, moderate plant height, and sparse tassel for high planting density stress tolerance. Molecular marker screening confirmed the homozygosity of these lines. Agronomic evaluation under narrow plant-to-plant spacing (15 cm) identified eight potential donor lines amenable to high planting density stress, ready for use as parents in breeding high-density tolerant hybrids. Interpretation: Potential donor doubled haploid lines viz. DH2-4, DH2-8, DH2-9, DH2-11, DH2-14, DH2-15 derived from Population-3 X CIM2GTAIL P2 and DH2-4, DH2-23 derived from Population-9 X CIM2GTAIL P2 were identified for utilization as putative parents of hybrids suitable for planting under high planting density conditions. Key words: Doubled haploid, High plant density, Maize, Plant architecture, Yield

(Bromus rigidus)من خلال معرفة كثافة الحشائش(Triticum aestivum L)استخدام تحليل امسار للتنبؤ بفقدان نباتات القمح

The research explores the use of path analysis to predict the effect of brome grass (Bromus rigidus Roth) density on wheat (Triticum aestivum L.) yield loss. It also studies the relationship between weed density and wheat productivity. The research was conducted during the fall 2020 and spring 2021 seasons. Data were collected from experiments conducted under different densities of weeds and wheat. The statistical analysis program SPSS was used to determine the effect of competition on the amount of loss in wheat and brome productivity, using the Cousens equation and to calculate the competition coefficient between species using the Steward equation. Then, path analysis was used to predict the effect of internal and external variables on plant traits, biomass, and productivity. The results showed that increasing grass density led to a decrease in wheat productivity. The study emphasizes the importance of taking physiological factors into account in crop productivity. Recommendations include implementing measures to control weed density, adjusting wheat planting density to compete effectively with weeds, using weed-resistant wheat varieties, adopting comprehensive farm management practices, and conducting further research to enhance understanding of the interaction between wheat and weeds.

Optimizing daylily (Hemerocallis citrina Baroni) cultivation: integrating physiological modeling and planting patterns for enhanced yield and resource efficiency

IntroductionOptimizing the dynamics of daylily (Hemerocallis citrina Baroni) growth under various planting patterns is critical for enhancing production efficiency. This study presents a comprehensive model to simulate daylily growth and optimize planting patterns to maximize bud yield while minimizing land resource utilization.MethodsThe model incorporates source-sink relationship specific to daylilies into physiological process modeling, considering environmental factors such as micro-light and temperature climate, and CO2 concentration. Spatial factors, including planting pattern, row spacing, plant spacing, and plant density were examined for their impact on light interception, photosynthesis, and resource efficiency. Employing partial least square path modeling (PLS-PM), we analyzed the interrelations and causal relationships between planting configurations and physiological traits of daylily canopy leaves and buds. Through in situ simulations of 36 planting scenarios, we identified an optimal configuration (Scenario ID5) with a density of 83,000 plants·ha−1, row spacing of 0.8 m, and equidistant planting with a plant spacing of 0.15 m.Results and discussionOur research findings indicate that increased Wide+Narrow row spacing can enhance yield to a certain extent. Although planting patterns influence daylily yield, their overall impact is relatively minor, and there is no clear pattern regarding the impact of plant spacing on individual plant yield. This modeling approach provides valuable insights into daylily plant growth dynamics and planting patterns optimization, offering practical guidance for both farmers and policymakers to enhance daylily productivity while minimizing land use.

Enhancing nitrogen and phosphorus removal in plant-biochar-pyrite stormwater bioretention systems: Impact of temperature and high-frequency heavy rainfall

Global climate change and rapid urbanization have resulted in more frequent and intense rainfall events in urban areas, raising concerns about the effectiveness of stormwater bioretention systems. In this study, we optimized the design by constructing a multi-layer filler structure, including plant layer, biochar layer, and pyrite layer, and evaluated its performance in nitrogen (N) and phosphorus (P) removal under different temperatures (5–18 °C and 24–43 °C), rainfall intensity (47.06 mm rainfall depth), and frequency (1–5 days rainfall intervals) conditions. The findings indicate that over 775 days, the plant system consistently removed 62.3% of total nitrogen (TN) and 97.0% of total phosphorus (TP) from 103 intense rainfall events. Temperature fluctuations had minimal impact on nitrate nitrogen (NO3−-N) and TP removal, with differences in removal rates of only 1.0% and 0.6%, respectively, among plant groups. Across the multi-layer structure, plant roots mitigated the impact of temperature differences on NO3−-N removal, while high-frequency rainfall fluctuated the stability of NO3−-N removal. Dense plant roots reinforced N and P removal by facilitating denitrification in the vadose zone (biochar) and strengthening denitrification processes. Biochar and pyrite contributed to stable microenvironments and diverse ecological functions, enhancing NO3−-N and PO43− removal. In summary, the synergistic effects of the multi-layer filler structure improved and stabilized N and P removal, providing valuable insights for addressing runoff pollution in bioretention systems amidst rapid urbanization and climate change challenges.

Effect of potassium supply and plant density on maize (Zea mays L.) yields and nutrient contents: a case study in a Hungarian long-term field trial set up on calcareous chernozem soil

Effect of potassium supply and plant density on maize (Zea mays L.) yields and nutrient contents: a case study in a Hungarian long-term field trial set up on calcareous chernozem soil

Monitoring aboveground organs biomass of wheat and maize: A novel model combining ensemble learning and allometric theory

Accurate monitoring of crop organ biomass facilitates optimizing agronomic strategies to maximize yield or economic benefit. Unmanned aerial vehicle (UAV) is extensively employed for aboveground biomass (AGB) monitoring at the farm scale, but previous studies have mostly concentrated on total AGB rather than individual organ biomass. Furthermore, film-mulched crops, a widely used cropping pattern in northwest China, have received less attention for AGB monitoring. We aim to develop a novel model to precisely estimate the AGB of leaf (AGBLeaf), stem (AGBStem), and reproductive organs (AGBR) by UAV for film-mulched wheat and maize. The maize-wheat rotation field experiments with treatments of five nitrogen application amounts and three planting densities were conducted from 2021 to 2023, respectively. Firstly, we constructed allometric models at jointing, heading (tasseling), and grain filling stages by ground sampling data in 2021–2022. Next, the input feature set was obtained by feature selection methods (Lasso and Boruta) using UAV image data, and three traditional methods (partial least squares, ridge regression, and support vector machine) and three ensemble learning models (random forest, extreme gradient boosting, and local cascade ensemble (LCE)) were trained for AGBLeaf inversion based on the physically-based PROSAIL model simulation dataset. Finally, the optimal AGBLeaf inversion hybrid model was coupled with the allometric model to estimate the AGBStem and AGBR in 2022–2023. The results indicated that both wheat and maize organ biomass conformed to the allometric pattern. While feature selection helped reduce computation and complexity, but didn’t improve monitoring accuracy. The normalized root mean square error (NRMSE) of the optimal hybrid model (PROSAIL + Boruta + LCE) on the measured wheat and maize AGBLeaf datasets were 12.72 %–24.93 % and 19.65 %–25.16 %, respectively. After coupling the allometric model, the coefficient of determination (R2) of wheat and maize AGBStem were 0.64–0.85 and 0.63–0.68, and the NRMSE were 15.05 %–25.28 % and 24.10 %–27.06 %, respectively; and the corresponding R2 of AGBR was 0.67–0.76 and 0.72, and the NRMSE were 16.81 %–22.12 % and 21.66 %, for wheat and maize, respectively. Overall, the novel model performed well in film-mulched wheat and maize, providing a cost-effective approach for organ biomass monitoring. In the future, further validation of the model’s transferability is necessary to increase the potential for generalization in production practice.

Spatial Analysis of Air Pollutants in an Industrial City Using GIS-Based Techniques: A Case Study of Pavlodar, Kazakhstan

The given research employs high-resolution air quality monitoring and contemporary statistical methods to address gaps in understanding the urban air pollution in Pavlodar, a city with a significant industrial presence and promising touristic potential. Using mobile air quality sensors for detailed spatial data collection, the research aims to quantify concentrations of particulate matter (PM2.5, PM10), carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), and ground-level ozone (O3); assess their distribution; and identify key influencing factors. In this study, we employed Geographic Information Systems (GISs) for spatial analysis, integrating multi-level B-spline interpolation to model spatial variability. Correlation analysis and structural equation modeling were utilized to explore the relationships between variables, while regression analysis was conducted to quantify these relationships. These techniques were crucial for accurately mapping and interpreting spatial patterns and their underlying factors. The study identifies PM2.5 and NO2 as the primary contributors to air pollution in Pavlodar, with NO2 exceeding the 24 h threshold in 87.38% of locations and PM2.5 showing the highest individual air quality index (AQI) in 75.7% of cases. Correlation analysis reveals a positive association between PM2.5 and AQI and a negative correlation between NO2 and AQI, likely due to the dominant influence of PM2.5 in AQI calculations. Structural equation modeling (SEM) further underscores PM2.5 as the most significant impactor on AQI, while NO2 shows no significant direct impact. Humidity is positively correlated with AQI, though this relationship is context-specific to seasonal patterns observed in May. The sectoral analysis of landscape indices reveals weak correlations between the green space ratio (GSR) and air quality, indicating that while vegetation reduces pollutants, its impact is minimal due to urban planting density. The road ratio (RR) lacks sufficient statistical evidence to draw conclusions about its effect on air quality, possibly due to the methodology used. Spatial variability in pollutant concentrations is evident, with increasing PM2.5, PM10, and AQI towards the east-northeast, likely influenced by industrial activities and prevailing wind patterns. In contrast, NO2 pollution does not show a clear geographic pattern, indicating vehicular emissions as its primary source. Spatial interpolation highlights pollution hotspots near industrial zones, posing health risks to vulnerable populations. While the city’s overall AQI is considered “moderate”, the study highlights the necessity of implementing measures to improve air quality in Pavlodar. This will not only enhance the city’s attractiveness to tourists but also support its sustainable development as an industrial center.

Adjusting Sowing Date and Seeding Rate for Cultivated Lentil to Contrasting Rainfall Conditions in a Semi-arid Region

Adjusting the sowing date and seeding rate of lentils are important practices, which largely affect plant performance and need greater focus under semi-arid conditions. Our study aimed to optimize the sowing window and plant density specific to dry and wet conditions. A two-year field experiment was carried out under dry and wet cropping seasons (2016/2017 and 2017/2018). Two commercial lentil varieties (Syrie229 and Idleb2) were sown at early (late October/early November), normal (December), and late (January) sowing dates and with low (90 seeds/m2), medium (120 seeds/m2) and high (150 seeds/m2) seeding rate. Several traits were recorded namely plant height at first filled pod (HFFP), plant height (PH), days to flowering (DTF), days to maturity (DTM), stem diameter (SD), weight of 100 seeds (100-SW) and seed yield (SY). Our results revealed that the dry year considerably reduced all trait values except the weight of 100 seeds compared to the wet year. Sowing date had a significant effect on most traits, with the highest values being found for early sowing date compared to normal and late dates, including seed yield (1.83 vs. 1.36 and 0.94 ton/ha, respectively). It is worth noting that the difference among sowing dates was detected only under wet years for most traits. The seeding rate affected only HFFP and stem diameter under a wet year, where a high seeding rate increased HFFP while a low seeding rate increased stem diameter. To conclude, cropping season was the main driver of growth and yield, and then the effect of sowing date was dependent on climatic conditions. Our results highlight the importance of adjusting the sowing window and seeding rate to cope with the future climatic change effects.

Spatial distribution of shrubs and perennial plants under grazing disturbance in the desert steppe of Inner Mongolia

The desert steppe is unique as a transition zone from the steppe to the desert of the Eurasian Steppe. The spatial distribution of shrubs and perennial plants has changed due to long-term disturbance caused by overgrazing in the ecosystem. This study aimed to determine the degree of patchiness of shrubs and perennial plants under grazing disturbance, which is of great significance to better understand the succession mechanism of plant community in the desert steppe. This study investigated the spatial distribution of shrubs and perennial plants under four stocking rates (no grazing, CK, 0 sheep·hm−2·half year−1; light grazing, LG, 0.93 sheep·hm−2·half year−1; moderate grazing, MG, 1.82 sheep·hm−2·half year−1; heavy grazing, HG, 2.71 sheep·hm−2·half year−1) in the desert steppe of Inner Mongolia, primarily using geostatistical methods. The density of perennial grasses increased with increasing stocking rate, while its height decreased (except for HG). The density and height of the shrubs and the perennial forbs showed an exponential or gradual decline. The spatial distribution of shrubs and perennial plants is mainly affected by structural factors such as topography, soil parent material, and climate, and the density of shrubs and perennial plants is most sensitive to changes in stocking rate. An appropriate stocking rate increases the spatial heterogeneity of shrubs and perennial plants, but heavy grazing reduces the spatial heterogeneity of shrubs and perennial plants.

Efisiensi Kerapatan Tananaman Pakcoy (Brassica Rapa) terhadap Kualitas Air untuk Mendukung Kelangsungan Hidup Ikan Nila

Asnan Ridoanrisna. Efficiency Of Pakcoy Plants (Brassica Rapa) In Maintaining Water Quality To Support The Survival Rate Of Tilapia. Under Guidance By Robin And Novita Mz. Tilapia is a freshwater fish commodity with high economic value. According to data from the Central Bureau of Statistics (BPS), tilapia exports reached 12.29 thousand tons with a value of USD 78.44 million. Tilapia farming faces the risk of mortality which can lead to economic losses, one of which is caused by organic pollution. To address this issue, this research employs phytoremediation methods with varying plant densities to improve water quality and tilapia survival. The study was conducted with four treatments: A75 (plant density 75% of the aquarium surface area), A50 (50%), A25 (25%), and A0 (no plants), using an aquarium size of 60 x 30 x 50 cm³. Each treatment received chicken manure at 1.8 grams per aquarium and 40 tilapia fish per aquarium. Observations were made over 15 days in March 2023, measuring physical and chemical water parameters including DO, pH, TDS, temperature, and ammonia, as well as calculating the survival rate of tilapia. Using a Completely Randomized Design (CRD), the study found that treatment A75 achieved the highest survival rate at 62.5%. This result indicates that higher plant density in the phytoremediation method is more effective in maintaining water quality and supporting tilapia survival.

Influence of Different Planting Methods and High-Density Planting on Yield and Economic Parameters in Banana cv. Williams

High density planting is one of novel concepts and it’s effectively increase productivity of per unit area without affecting the fruit quality. Gross yield of banana per hectare mainly depends on yield of per plant and number of plants per hectare. The study was carried out at ICAR- All India Coordinated Research Project on Fruits, Kittur Rani Channamma College of Horticulture, Arabhavi in Belgavi district, Karnataka to study influence of different planting density on both yield and economic parameters of banana cv. Williams during 2021-22. It was laid out in Randomized Complete Block Design with three replications and eight treatments. The results revealed that, the highest values for bunch parameters like bunch length (97.77 cm), bunch width (93.57 cm), number of hands per bunch (11.93), number of fingers in third hand (21.53) and weight of third hand (2.97 kg) was recorded in wider spacing treatment T4 (Single row - 2.4×1.8 m). Regarding to yield parameters like highest bunch weight per hill (36.09 kg) was recorded in T6 (3 plants per hill- 2.7×1.8×0.3 m). While, highest yield per hectare (108.75 t/ha) was found in treatment T8 (Paired row with zig-zag - 2.1×1.2×1.2 m). With respect to the highest gross returns (10,33, 125.00 Rs/ha), net returns (5, 53,725.00 Rs/ha) and highest benefit cost ratio (2.15) was observed in T8 (paired row system of with zig-zag planting).

Advances in breeding, biotechnology, and nanotechnological approaches to combat sheath blight disease in rice.

Sheath blight, caused by the fungus Rhizoctonia solani, is a major problem that significantly impacts rice production and can lead to substantial yield losses. The disease has become increasingly problematic in recent years due to the widespread use of high-yielding semi-dwarf rice cultivars, dense planting, and heavy application of nitrogenous fertilizers. The disease has become more challenging to manage due to its diverse host range and the lack of resistant cultivars. Despite utilizing traditional methods, the problem persists without a satisfactory solution. Therefore, modern approaches, including advanced breeding, transgenic methods, genome editing using CRISPR/Cas9 technology, and nanotechnological interventions, are being explored to develop rice plants resistant to sheath blight disease. This review primarily focuses on these recent advancements in combating the sheath blight disease.