Vegetative Growth Research Articles

Study on the Spatial–Temporal Variation of Groundwater Depth and Its Impact on Vegetation Coverage in Ejina Oasis

Ejina, a representative inland river basin situated in the arid region of northwest China, exhibits a delicate ecological environment and its vegetation coverage is intrinsically linked to regional ecological security. Based on MOD13Q1-NDVI data from 2018 to 2023 and groundwater depth monitoring data during the same period, this study analyzed the spatial–temporal variation characteristics of vegetation coverage and its relationship with groundwater depth in Ejina. It is found that the vegetation coverage in Ejina is generally low and mainly distributed along the riverbanks in the form of strips. During the study period, the overall trend of vegetation coverage showed a fluctuating pattern of first increasing and then decreasing, revealing the fragility of the regional ecology. The groundwater depth shows the characteristic of being higher in the east river than the west, and the trend of groundwater depth along the river flow is first increasing and then decreasing. The spatial groundwater depth indicates that the east river is higher than that of the west river, and the groundwater depth along the river flow first increases and then decreases. In terms of inter-annual changes, the groundwater depth experiences a process of first decreasing and then stabilizing. Further analysis indicates that vegetation growth and coverage in Ejina are significantly affected by water conditions, and areas with high Normalized Difference Vegetation Index (NDVI) values are mainly distributed along the riverbanks. In addition, there is a certain degree of correlation between groundwater depth and NDVI. When the depth of groundwater is too deep or too shallow, the positive correlation between NDVI and groundwater depth increases slightly and the negative correlation decreases slightly. The findings of this study are of great significance for understanding and predicting the response of vegetation coverage to groundwater changes in arid areas, and provide a scientific basis for water resources management and ecological protection in Ejina.

Impacts of terrestrial mammalian herbivores on vegetation change in the arctic

AbstractThere are increasing concerns about regional ecosystem shifts in the Arctic due to climate change. Notably, warming-induced increases in Arctic vegetation cover can have important consequences for surface energy balance, habitat changes, permafrost, and more. Mammalian herbivory is an important potential force to counteract this effect. In this systematic literature review, we examine the role of terrestrial mammalian herbivory on warming-induced increases in Arctic vegetation. We analyse the effects of terrestrial mammalian herbivory on vegetation cover, abundance, growth, survival, and ecosystem productivity. Our results show that herbivory has an overall significant negative influence on Arctic vegetation, particularly on vegetation biomass, growth, and productivity, as indicated by the Normalised Difference Vegetation Index (NDVI). Importantly, we demonstrated a significant role of herbivores in controlling carbon dioxide exchange and carbon uptake, whilst acknowledging that the relationship between herbivory and ecosystem productivity is highly complex and site-dependent. Our results confirm the important role that herbivory can play in buffering observed and predicted warming-induced Arctic vegetation increases. We also find that this is strongly affected by plant palatability, trampling occurrence, and herbivore density. Graphical Abstract

Assessment of Pesticide Residues in Fruits and Vegetables Grown in Abidjan, Ivory Coast

Introduction: The presence of pesticide residues in primary and derived agricultural products raises serious health problems for consumers. The aim of this study was to assess the level of pesticide residues in commonly consumed vegetables. Methods: Pesticide residues were extracted from market garden products (Solanum lycopersicum, Capsicum sp, Cucumis sativus and Lactuca sativa) by the QuEchERS method and analyzed by high performance liquid chromatography (HPLC-UV) technique. Results: These analyzes made it possible to detect 32 pesticide residues. All market garden products contained pesticide residues, 12.82% of which exceeded the maximum residue limits (MRLs). The pesticide families found were triazines (34.34%), urea derivatives (31.25%), organophosphorus residues (9.37%), organochlorines (9.37%), triazinones (9.37%) and carbamates (6.25%). Among the market garden products, only lettuce was contaminated by residues from all families with concentrations of pesticide residues exceeding their limits of quantification at the level of 5 molecules: Chlorpropham (0.016 mg/kg), Linuron (0.02 mg/kg), Chlorfenvinphos (0.026 mg/kg) Parathion-ethyl (0.014) and Metolachlor (0.013 mg/kg) which is an organochlorine pesticide. Organochlorines are among the prohibited pesticides. Among agrochemicals used, some were not approved. Conclusion: The results indicate the presence of pesticide residues in commonly consumed vegetables and highlight the urgent need to develop comprehensive intervention measures to reduce the potential health risk to consumers. The need for regular monitoring of pesticide residues and raising farmers' awareness of better pesticide safety practices are actions to be taken for the health of consumers.

Assessment of lake Markakol’s physical and chemical condition with consideration of eutrofication

The study was conducted in 2023 and comprised a comparative assessment of the state of Lake Markakol’s aquatic ecosystems in surface and bottom water strata. The analysis of bottom water temperatures showed correlation between this parameter and dissolved oxygen concentrations, indicating that pollution caused by organic impurities leads to lake eutrophication, in turn, pro-pelling the extinction of aquatic life. Although the main water physicochemical parameters of Markakol Lake correspond to the oligotrophic type, the shifts in dissolved oxygen and phos-phate content, as well as growth of aquatic vegetation indicate its transition to the mesotrophic type. Higher phosphate content in water is a consequence of pollution disturbing the biological balance, as well as stimulating the reservoir’s eutrophication and increased biological productivity, i.e. algal bloom. In addition, phosphate ions serve an informative indicator of Hazard Class 3 (organoleptically hazardous) anthropogenic pollution. Based on the correlation factor (r), two statistical models were considered for the target lake: 1) Water Pollution: nutri-ent concentrations depending on surface and bottom water temperatures (Model 1); and 2) changes in Water Pollution Indices (biogenic, heavy metals, mean) because of air temperature growth due to global warming of 0.25°C/decade (Model 2).

Identification and Gene Fine Mapping of the Bisexual Sterility Mutant Meiosis Abnormal Bisexual Sterility 1 in Rice

Exploring the genes regulating rice fertility is of great value for studying the molecular mechanisms of rice reproductive development and production practices. In this study, we identified a sterile mutant from the mutant library induced by ethyl methanesulfonate (EMS), designated as meiosis abnormal bisexual sterility 1 (mabs1). The mabs1 mutant exhibits no phenotypic differences from the wild-type during the vegetative growth phase but shows complete sterility during the reproductive growth phase. Phenotypic observations revealed that both pollen and embryo sac fertility are lost in mabs1. Notably, in mabs1, the development of the anther inner and outer walls, tapetum degeneration, and callose synthesis and degradation all proceed normally, yet meiosis fails to form normal tetrads. Genetic analysis indicated that this mutant trait is controlled by a single recessive nuclear gene. By constructing a genetic segregation population, we successfully mapped the MABS1 gene to a 49 kb region between primer markers Y7 and Y9 on chromosome 1. Resequencing revealed a single-nucleotide substitution in the exon of the LOC_Os01g66170 gene, which resulted in a change from Valine to Isoleucine. Subsequent sequencing of this locus in both wild-type and mabs1 mutants confirmed this mutation. Therefore, we have identified the gene at LOC_Os01g66170 as a candidate for MABS1, a previously unreported novel gene involved in rice meiosis. Through RT-qPCR, we found that the expression levels of multiple meiosis-related genes were significantly changed in the mabs1 mutant. Therefore, we believe that MABS1 is also involved in the process of rice meiosis. This study lays the groundwork for a functional study of MABS1.

Effects of biochar, N-enriched biochar and urea on tomato seed germination, vegetative growth, and fruit traits.

Agronomic uses of biochar have been intensely explored in the last 15 years. Recently, a new generation of biochar-based fertilizers has been developed. Raw biochar (BCH), nitrogen-enriched biochar (N + BCH) or urea were added to a coir fiber-based substrate for tomato cultivation, to assess seed germination, growth and fruiting of two cultivars (Cuarenteno and Moneymaker). BCH stimulated seed germination and early radicle growth, possibly because of the presence of karrikins detected in both BCH and N-BCH (0.039 and 0.044 mg kg-1, respectively). However, BCH reduced growth in adult plants in both cultivars, probably because of ammonium retention, causing low-N-stress-related symptoms such as accumulation of flavonoids in the leaf. Urea was toxic for seed germination because of the fast release of ammonium, but caused a positive effect on adult plant growth and yield, increasing chlorophyll in both cultivars, quantum yield and ascorbic acid in cv. Cuarenteno, and decreasing flavonoids and peroxide in leaves of both cultivars. Unlike urea, N + BCH showed a positive impact on plant growth and yield, but without releasing high amounts of ammonium or negatively affecting seed germination. Nitrogen-rich amendments reduced phosphorus and increased iron leaf content in both cultivars. BCH can be effectively used as a growth medium constituent in nurseries for seedling production, whereas N + BCH offers a promising alternative to urea or other nitrogen mineral fertilizers for crop cultivation. © 2024 The Author(s). Journal of the Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Overexpression of vacuolar H+-pyrophosphatase from a recretohalophyte Reaumuria trigyna enhances vegetative growth and salt tolerance in transgenic Arabidopsis thaliana

Reaumuria trigyna, a wild and endangered salt-secreting small shrub, is distributed in arid and semi-arid areas of Inner Mongolia, China. An H+-pyrophosphatase gene (RtVP1) was isolated from R. trigyna according to transcriptomic data, which encoded a plasma membrane and tonoplast-localized protein. RtVP1 was quickly upregulated by NaCl and exogenous abscisic acid treatment and rescued the sucrose deficiency sensitive phenotype of the AtVP1 mutant (avp1). Transgenic Arabidopsis overexpressing RtVP1 exhibited a higher leaf area, plant height, fresh weight, root length, and soluble carbohydrate accumulation compared to the wild type (WT) under normal conditions. RtVP1 overexpression increased the seed germination rate and decreased the reduction rate of fresh weight, root length, and chlorophyll content in transgenic plants under salt stress. Catalase enzyme activity, proline content, relative water content, and soluble sugar content were significantly increased in transgenic Arabidopsis under salt stresses, but the malondialdehyde content was dramatically decreased. More K+ and less Na+ were accumulated in transgenic Arabidopsis leaves, resulting in a relatively lower Na+/K+ ratio. In transgenic Arabidopsis roots, K+ was unchanged, but Na+ and the Na+/K+ ratios were reduced compared to those in WT. More Na+ and K+ were accumulated in the intracellular of transgenic yeast, and the Na+/K+ ratio was significantly reduced compared to the control. These results showed that R. trigyna RtVP1 promotes the vegetative growth of plants, mainly by regulating carbohydrate metabolism, and confers salt tolerance in transgenic Arabidopsis by maintaining Na+/K+ homeostasis and enhancing the antioxidant and osmotic regulatory capacity. These results indicated that RtVP1 can serve as an important candidate gene for genetic improvement of crop yield and salt tolerance.

Exploring the Synergistic Effects of Biostimulant and Hydrogel Combinations on Brinjal Growth: An Assessment of Growth Parameters

Background: This study at Lovely Professional University, Phagwara, Punjab, evaluates the combined effects of hydrogel and Arka Vegetable biostimulants on brinjal (Solanum melongena L.) production. Brinjal’s high water and nutrient needs make it sensitive to water scarcity and seasonal variations. Hydrogel enhances soil moisture retention, reducing irrigation needs, while Arka Vegetable biostimulants improve plant growth and stress tolerance. Using both together aims to optimize water management and plant health, addressing key challenges in brinjal cultivation. Methods: In the study, the hydrogel was applied during the sowing stage, while Arka Vegetable Special was sprayed twice, with a 15-day interval after transplanting. The treatment designated as V2H2 (5 g/L + 1.5 kg/acre) was utilized, where ‘V’ represents concentration in grams per liter and ‘H’ denotes application rate in kilograms per acre. This treatment is aimed at optimizing vegetative growth. Various levels of Arka Vegetable Special and hydrogel application were tested to observe their effects on growth characteristics. Result: The study’s findings revealed the effectiveness of the V2H2 treatment in enhancing vegetative growth. Application of Arka Vegetable Special and hydrogel at different levels significantly improved all the studied growth characteristics. This suggests the potential of integrating biostimulants and Hydrogel practices to optimize Brinjal production, offering a sustainable solution to meet year-round vegetable demand and mitigate water scarcity challenges in agricultural systems.

Microbiome and nutrient dynamics of organic manures for precision NPK management in sunflower (Helianthus annuus L.)

AbstractOrganic manure plays an important role in soil fertility, microbial communities and sustainable agricultural strategies. In organic cultivation of crops, manures are mostly used without any calculation of the nutrients added to soil through their application. The quantities of nutrients supplied by the organic manures to the crop have to equalize the quantity of nutrients supplied by inorganic chemical fertilizers, in order to replace chemical fertilizers in organic farming. Since the organic manures release nutrients slowly into the soil over a period of time, the availability of nutrients to the standing crop requires precise estimation. In the present study, the amount of nutrients available in the soil as well as in all the manures was calculated. Moreover, the study included metagenomic analysis of different organic manures used by farmers and gives an insight to the role the microbiome plays in plant growth. Using a formula of STCR‐IPNS (soil test crop response integrated plant nutrition system), the quantities of different combinations of organic manures required to supply nitrogen, phosphorus and potassium (NPK) to sunflower plants were calculated. Organic manure combinations using animal bone meal, neem cake, farmyard manure and vermicompost recorded better growth and yield responses in sunflower plants compared to inorganic chemical fertilizers. Based on the estimation of NPK in the individual manures and in the soil, pot experiments were carried out to understand the effect of organic manures as well as inorganic fertilizers in the vegetative and reproductive growth of sunflower.

Impact of climate change on vegetation growth trends in a citrus farmland in the south-eastern Sicily

Abstract. The environmental repercussions of climate change triggered substantial alterations in existing ecosystem balances leading to a gradual reduction in biodiversity and the increasing degradation of soil and the built environment. This has a direct effect on agricultural production in particular, leading to increased crop water requirements, the spread of new pests and pathogens that are difficult to manage, and, thus, a general reduction in productivity. Through the analysis of multispectral data remotely sensed with latest generation of optical sensors (RGB, thermal, NIR and multi-spectral cameras), it is possible to recognize the health status and growth stages of crops. In fact, in relation to the amount of radiation reflected in the different bands it is possible to calculate spectral indices, or vegetation indices. The main vegetative indices are NDVI, SAVI, MSAVI2, GNDVI and NDRE, which are calculated by differentially combining the ultraviolet spectrum, the visible range, and the near and mid-infrared band.In this paper the outcomes of a multi-year monitoring of a citrus grove field near Rosolini (Syracuse), in south-eastern Sicily-Italy, are presented. This monitoring activity was conducted to highlight areas of productive greenery under stress, on which to act as a priority with specific agronomic interventions. In parallel with the direct monitoring phases of the citrus grove, the trend of average monthly and annual temperature and precipitation values over the past 24 years was also studied to more specifically contextualize the possible presence of significant variations in climatic trends and relate them to the results returned by the calculation of the indices.

Interannual variations of normalized difference vegetation index and potential evapotranspiration and their relationship in the Baghdad area

Abstract A monthly correlation between urban vegetation growth and potential evapotranspiration (PET) is needed for better knowledge of controlling water resources and organized irrigation processes. This study aims to explore their relationship within an urban area like Baghdad, using a linear regression model to derive a best-fit line drawn in a scatterplot on a monthly time scale. Based on two different monthly data sources: weather variables (e.g., air temperature, solar radiation, and relative humidity) and Sentinel-2 satellite imagery of 2 years, 2018 and 2021, this study presented the interannual variations of PET and normalized difference vegetation index (NDVI). The choice of these years has a significant feature of climatic differences, which are arid and semi-arid, respectively. PET values were estimated by the Truc method, while the areas of vegetation (represented by NDVI) were calculated using the Geographic Information Sensing program. The results show that the maximum PET in both years was found in the summer months (June and July) with mean values of about 8.8 mm/day, while their minimum mean values of about 1.5 mm/day occurred in winter months (January and December). From the spatial distribution of NDVI, it was found that at positive pixels when NDVI >0.2, vegetation cover in March, April, and December 2018 had large areas with more than 200 km2 in 2018, while they were largest only in May 2021 with 197.8 km2. There was a linear correlation with slope (0.03) and intercept (= 1.8) and a strong correlation, R 2 = 0.72. The practical implications of the findings contribute to enhancing a solid scientific basis for improving agricultural water management, especially under dry conditions.

Early evaluation of salt-stress tolerance of new released olive cultivars based on physiological and biomass allocation indicators

The evaluation of salt-tolerant olive tree genotypes released from breeding program has become intrinsic in order to develop sustainable agriculture in these regions. The current study aims to i) evaluate the tolerance of two new released olive cultivars (Zeitoun Ennour and Zeitoun Ennwader), issued from a Tunisian breeding program in comparison with the main olive cultivar ‘Chemlali Sfax’, and ii) identify suitable salt-tolerance indicators for this evaluation. The trial was conducted under controlled conditions in a greenhouse, for six months, and plants were irrigated with half-strength Hoagland nutrient solution containing NaCl at various levels (0, 75, 150 and 225 mM). Vegetative growth, biomass allocation and biochemical parameters were considered for the assessment of salt-tolerant capacity. Results revealed that growth and biomass should be considered as useful indicators for early evaluation method of salt-stress tolerance. ‘Chemlali Sfax’ displayed a gradual significant decrease of vegetative growth with increasing salinity. The reduction of shoot elongation and trunk diameter was most evidently at 150 mM with 43.2 % and 80.8 %, respectively. However, the new released cultivars showed unaffected vegetative growth, despite a slight decrease at the salt level of 225 mM. Moreover, results demonstrated the importance of certain physiological and biochemical indicators such as ions contents. The new released cultivars maintained a high K+/Na+ ratio at moderate salinity then a significant decrease occurred at 150 mM. In conclusion, vegetative growth, biomass allocation and K+/Na+ ratio seemed to be the suitable salt-tolerance indicators for early evaluation. Based on these indicators, ‘Zeitoun Ennour’ seems to be the most salt tolerant genotype and ‘Zeitoun Ennwader’ proves to have a similar salt tolerant capacity as ‘Chemlali Sfax’, which is a valuable information for olive growers in arid region.

Understanding soil and ecosystem respiration in a dune-meadow cascade ecosystem

Arid and semi-arid regions, which account for more than 30% of the Earth's land area, increasingly dominate the spatiotemporal trends in global carbon fluxes. The Horqin Sandy Land is a typical semi-arid fragile ecosystem in northern China. Understanding the components of the carbon budget in ecosystems under conditions of extreme soil moisture limitations provides a foundation for comprehending the carbon balance in semi-arid ecosystems. The seasonal and diurnal variations in soil respiration (Rs) in semi-mobile dune (SD) and meadow wetland (MW) ecosystems of the Horqin Sandy Land were examined, and the sources of CO2 emissions from Rs were identified using stable carbon isotopes. The responses of Rs and ecosystem respiration (Reco) to environmental temperature, moisture and leaf area index (LAI) were revealed. The results showed that on a seasonal scale, in SD with soil moisture content (Ms) below field capacity (FC), Ms had a greater influence on Rs than soil temperature (Ts) during the growing season. Changes in the LAI during the middle and late growth period affected Rs by altering root carbon supply. In MW, the most favorable Ms for Rs was near FC. The increase in LAI before mowing could effectively promote root and soil microbial respiration, and the decomposition of litter driven by Ts was the main form of Rs at this time. After mowing, root respiration and soil microbial respiration were the main processes contributing to CO2 emissions. On a daily scale, relative humidity (RH) dominated the Rs variation under dry conditions, whereas in other conditions, the Rs was adequately explained by temperature in SD and MW. The overall Reco was larger than Rs, but occasionally Rs was greater than Reco. The effects of temperature, moisture and LAI on Reco and Rs varied with growing season. Adding factors, such as ecosystem type, vegetation growth, water, and heat, to the carbon cycle model can improve predictions of carbon emissions, and aid in further management decisions in arid and semi-arid areas.

The Impact of Seasonal Climate on Dryland Vegetation NPP: The Mediating Role of Phenology

Dryland ecosystems are highly sensitive to climate change, making vegetation monitoring crucial for understanding ecological dynamics in these regions. In recent years, climate change, combined with large-scale ecological restoration efforts, has led significant greening in China’s arid areas. However, the mechanisms through which seasonal climate variations regulate vegetation growth are not yet fully understood. This study hypothesizes that seasonal climate change affects net primary productivity (NPP) of vegetation by influencing phenology. We focused on China’s Windbreak and Sand-Fixation Ecological Function Conservation Areas (WSEFCAs) as representative regions of dryland vegetation. The Carnegie–Ames–Stanford Approach (CASA) model was used to estimate vegetation NPP from 2000 to 2020. To extract phenological information, NDVI data were processed using Savitzky–Golay (S–G) filtering and threshold methods to determine the start of season (SOS) and end of season (EOS). The structural equation model (SEM) was constructed to quantitatively assess the contributions of climate change (temperature and precipitation) and phenology to variations in vegetation NPP, identifying the pathways of influence. The results indicate that the average annual NPP in WSEFCAs increased from 55.55 gC/(m2·a) to 75.01 gC/(m2·a), exhibiting uneven spatial distribution. The pathways through which seasonal climate affects vegetation NPP are more complex and uneven. Summer precipitation directly promoted NPP growth (direct effect = 0.243, p < 0.001) while also indirectly enhancing NPP by significantly advancing SOS (0.433, p < 0.001) and delaying EOS (−0.271, p < 0.001), with an indirect effect of 0.133. This finding highlights the critical role of phenology in vegetation growth, particularly in regions with substantial seasonal climate fluctuations. Although the overall ecological environment of WSEFCAs has improved, significant regional disparities remain, especially in northwestern China. This study introduces causal mediation analysis to systematically explore the mechanisms through which seasonal climate change impacts vegetation NPP in WSEFCAs, providing new insights into the broader implications of climate change and offering scientific support for ecological restoration and management strategies in arid regions.

The Effect of Vegetation Ecological Restoration by Integrating Multispectral Remote Sensing and Laser Point Cloud Monitoring Technology

This research aims to evaluate and monitor the effectiveness of vegetation ecological restoration by integrating Multispectral Remote Sensing (MRS) and laser point cloud (LPC) monitoring technologies. Traditional vegetation restoration monitoring methods often face challenges of inaccurate data and insufficient coverage, and the use of MRS or LPC techniques alone has its limitations. Therefore, to more accurately monitor the vegetation restoration status, this study proposes a new monitoring method that combines the advantages of the large-scale coverage of MRS technology and the high-precision three-dimensional structural data analysis capability of LPC technology. This new method was applied in the Daqing oilfield area of China, aiming to provide effective ecological restoration assessment methods through the precise monitoring and analysis of regional vegetation growth and coverage. The results showed that there was a negative correlation between the vegetation humidity index and vegetation growth in the Daqing oilfield in 2023. The estimated monitoring effect of the research method could reach over 90%, and the coverage area of hydrangea restoration in the monitoring year increased by 7509 km2. The research technology was closer to the actual coverage situation. The simulation image showed that the vegetation coverage in the area has significantly improved after returning farmland to forests. Therefore, the technical methods used can effectively monitor the ecological restoration of vegetation, which has great research significance for both vegetation restoration and monitoring.

Effects of vertical forest stratification on precipitation material redistribution and ecosystem health of Pinus massoniana in the Three Gorges Reservoir area of China.

Vertical stratification of forest plays important roles in the local material balance and in maintaining forest health by distributing and redistributing precipitation materials through adsorption, fixation, and release. Differences in runoff nutrient concentrations among vertical layers are closely related to vertical stratification (factors such as the trunk, canopy, forest litter, and soil physical and chemical properties). Long-term forest observations revealed significant spatial differences in Pinus massoniana (Pinus massoniana Lamb.) forests in the Three Gorges Reservoir area. Pinus massoniana forests on downslopes were characterized by a dense canopy, green needles, and rich forest vegetation, while those on upslopes were characterized by low vegetation cover, dead trees, and decreases in the tree height, diameter at breast height, and volume per plant with increasing slope. By analyzing the soil at different sites, we found that the pH of the forest land soil differed significantly among different slope positions. Soil on upper slopes was significantly more acidic than soil on lower slopes, indicating that acidic substances were intercepted by filtration through the broad litter layer and the soil surface layer. This filtration process resulted in a normal rhizosphere environment suitable for the absorption of nutrients by vegetation on the lower slopes. In this way, downhill sites provided a good microenvironment for the growth of Pinus massoniana and other vegetation. Our results show that direct contact between needles and acid rain was not the main cause of root death. Instead, the redistribution of rainfall substances by forest spatial stratification caused changes in the soil microenvironment, which inhibited the absorption of nutrients by the roots of Pinus massoniana and the growth of understory plants in Pinus massoniana forests on upper slopes. These findings emphasize that increasing land cover with forests with vertical structural stratification plays an important role in woodland material redistribution and forest conservation.

Optimizing Vegetative Growth and Flowering in Fuchsia x hybrida: The Role of Media, Pinching, and Growth Regulators

The present investigation was carried out at the experimental farms of Horticultural Regional training station and Krishi Vigyan Kendra at Kandaghat (Solan) Himachal Pradesh, India under polyhouse conditions. It was laid out in a Completely Randomized Design (CRD) with 24 combinations of growing media M1: Soil+ Sand+ FYM (1:1:1v/v), M2:Cocopeat+Soil+Sand+ Leafmould+FYM (2:1:1:1v/v), M3:Cocopeat+Perlite+Vermiculite+Vermicompost (2:1:1:1 v/v), M4:Cocopeat + Vermicompost + Leafmould (2:1:1 v/v), growth regulator [G1: Control (0 ppm), G2:Benzyl adenine (150 ppm),G3: CPPU (10 ppm)] and pinching methods [P1:Single pinch and P2:Double pinch] which were replicated thrice each having 10 pots accommodating one plant per pot. Plants were raised through terminal cutting and were planted in 6-inch size pots. Study revealed that maximum plant height (33.13 cm), plant spread (33.37 cm), length of side shoots (24.67 cm) and minimum number of days taken for visible bud formation (92.40 days), number of days taken for peak flowering (160.60 days) was recorded when the single pinched plants were grown in media consisting cocopeat + Vermicompost + Leafmould (2:1:1 v/v) and sprayed with 150 ppm of benzyl adenine. However, maximum number of side shoots (27.33), number of flowers per plant (55.67), number of flowers per plant open at a time (42.93), duration of flowering (24.67days) was recorded when double pinched plants were grown in growing media consisting of cocopeat + vermicompost + Leafmould (2:1:1 v/v) and were sprayed with 150 ppm of benzyl adenine. The maximum flower diameter (4.61 cm) was recorded when single pinched plants were grown in medium consisting cocopeat + vermicompost + leafmould (2:1:1 v/v) and sprayed with 10 ppm of CPPU. Based on the present investigation findings, double pinched plants of Fuchsia x hybrida grown in pots consisting of growing media i.e., cocopeat + vermicompost+ leafmould (2:1:1 v/v), sprayed with 150 ppm of benzyl adenine is recommended to obtain quantitative and attractive pot plants of Fuchsia x hybrida.

Forest Fire Severity and Koala Habitat Recovery Assessment Using Pre- and Post-Burn Multitemporal Sentinel-2 Msi Data

Habitat loss due to wildfire is an increasing problem internationally for threatened animal species, particularly tree-dependent and arboreal animals. The koala (Phascolartos cinereus) is endangered in most of its range, and large areas of forest were burnt by widespread wildfires in Australia in 2019/2020, mostly areas dominated by eucalypts, which provide koala habitats. We studied the impact of fire and three subsequent years of recovery on a property in South-East Queensland, Australia. A classified Differenced Normalised Burn Ratio (dNBR) calculated from pre- and post-burn Sentinel-2 scenes encompassing the local study area was used to assess regional impact of fire on koala-habitat forest types. The geometrically structured composite burn index (GeoCBI), a field-based assessment, was used to classify fire severity impact. To detect lower levels of forest recovery, a manual classification of the multitemporal dNBR was used, enabling the direct comparison of images between recovery years. In our regional study area, the most suitable koala habitat occupied only about 2%, and about 10% of that was burnt by wildfire. From the five koala habitat forest types studied, one upland type was burnt more severely and extensively than the others but recovered vigorously after the first year, reaching the same extent of recovery as the other forest types. The two alluvial forest types showed a negligible fire impact, likely due to their sheltered locations. In the second year, all the impacted forest types studied showed further, almost equal, recovery. In the third year of recovery, there was almost no detectable change and therefore no more notable vegetative growth. Our field data revealed that the dNBR can probably only measure the general vegetation present and not tree recovery via epicormic shooting and coppicing. Eucalypt foliage growth is a critical resource for the koala, so field verification seems necessary unless more-accurate remote sensing methods such as hyperspectral imagery can be implemented.

Identification and Application of Streptomyces rapamycinicus CQUSh011 against Potato Late Blight.

Using chemical fungicides is the main strategy for controlling potato late blight (PLB), a devastating pre- and postharvest disease caused by Phytophthora infestans, resulting in environmental pollution and health risks. It is of great importance to develop a biofungicide from microorganisms. Through isolating potato rhizosphere microorganisms, CQUSh011 was found to have antioomycete activity with strong inhibition on vegetative growth and virulence of P. infestans. Morphological and molecular identification indicated that CQUSh011 belongs to Streptomyces rapamycinicus. Based on genome, metabolome, and HPLC quantification, rapamycin and salicylic acid were found to be the two active metabolites against P. infestans. Continuous field trials showed that CQUSh011 has sustainable control efficiency against PLB, and the efficiency was better when combined with Infinito, along with an increased endophytic microbial community and biodiversity in potato roots. The results demonstrated the potential of CQUSh011 as a biofungicide against PLB and provided an alternative strategy for reducing the application of chemical fungicides.

Novel Approach in Vegetation Detection Using Multi-Scale Convolutional Neural Network

Vegetation segmentation plays a crucial role in accurately monitoring and analyzing vegetation cover, growth patterns, and changes over time, which in turn contributes to environmental studies, land management, and assessing the impact of climate change. This study explores the potential of a multi-scale convolutional neural network (MSCNN) design for object classification, specifically focusing on vegetation detection. The MSCNN is designed to integrate multi-scale feature extraction and attention mechanisms, enabling the model to capture both fine and coarse vegetation patterns effectively. Moreover, the MSCNN architecture integrates multiple convolutional layers with varying kernel sizes (3 × 3, 5 × 5, and 7 × 7), enabling the model to extract features at different scales, which is vital for identifying diverse vegetation patterns across various landscapes. Vegetation detection is demonstrated using three diverse datasets: the CamVid dataset, the FloodNet dataset, and the multispectral RIT-18 dataset. These datasets present a range of challenges, including variations in illumination, the presence of shadows, occlusion, scale differences, and cluttered backgrounds, which are common in real-world scenarios. The MSCNN architecture allows for the integration of information from multiple scales, facilitating the detection of diverse vegetation types under varying conditions. The performance of the proposed MSCNN method is rigorously evaluated and compared against state-of-the-art techniques in the field. Comprehensive experiments showcase the effectiveness of the approach, highlighting its robustness in accurately segmenting and classifying vegetation even in complex environments. The results indicate that the MSCNN design significantly outperforms traditional methods, achieving a remarkable global accuracy and boundary F1 score (BF score) of up to 98%. This superior performance underscores the MSCNN’s capability to enhance vegetation detection in imagery, making it a promising tool for applications in environmental monitoring and land use management.