Search Results (1,849)

The phenological characteristics of the spring phytoplankton bloom in the mid- and high-latitude oceans, including its initiation, duration, and intensity, can be assessed using various diagnostic methods. However, there is currently a lack of systematic comparisons among these different methods. To elucidate the differences in spring bloom characteristics derived from different approaches and to identify suitable methods for shelf seas, this study comprehensively compares and evaluates the multiple methods for characterizing the spring bloom in the central Yellow Sea, based on satellite-derived chlorophyll-a (Chl-a) data from 2003 to 2020. The methods examined include concentration threshold (CT), cumulative concentration threshold (CCT), rate of change (RoC), and curve-fitting methods for determining bloom initiation; threshold and symmetric methods for estimating duration; and peak, mean, integral, and relative intensity index methods for assessing intensity. The results show that the bloom initiation determined by the CT method occurs earliest (average: Day of Year (DOY) 64), whereas the RoC method identifies a notably later initiation (average: DOY 100), approximately 40 days later. The CCT method yields an intermediate bloom initiation (average: DOY 70), with minimal interannual variability. Notably, curve-fitting methods often produce outliers (e.g., DOY 1) due to the fluctuations in Chl-a time series during winter. The threshold method yields a shorter bloom duration (average: 70 days), while the symmetric method results in a duration of more than 10 days longer. The four intensity assessment methods indicate that bloom intensity initially increased and subsequently decreased from 2003 to 2020, but the peak year varies depending on the method used. Overall, the CCT, symmetric, and relative index methods are more suitable for the Yellow Sea, as their computational results exhibit fewer outliers and relatively low standard deviations. The interannual variations in spring bloom characteristics assessed by different methods display distinct patterns and weak correlations, indicating that methodological choices can lead to divergent interpretations of spring bloom dynamics. Therefore, it is essential to carefully select methods based on research objectives and dataset characteristics. Full article

Optimizing spectral quality is a key strategy in controlled environment agriculture (CEA) to enhance both productivity and nutritional quality in horticultural crops. In this study, we investigated the organ-specific physiological and metabolic responses of celery (Apium graveolens L. cv. Dayehuang) to supplemental blue light at three intensities (10, 20, and 30 μmol·m⁻²·s⁻¹ with red/blue light ratios of 0.76, 0.68, and 0.60, respectively) in a plant factory with artificial lighting. Results showed that a moderate red/blue light ratio of 0.68 significantly enhanced chlorophyll accumulation, PSII quantum efficiency, and net photosynthetic rate, resulting in the highest shoot biomass without inducing photoinhibition. Leaf tissues showed marked increases in flavonoids and total phenolics, while petioles exhibited elevated soluble sugar levels and favorable modulation of volatile compound profiles. Antioxidant enzyme activities, particularly superoxide dismutase and peroxidase, were also enhanced with a moderate red/blue light ratio of 0.68, contributing to improved oxidative stress defense. Composite indices, including functional yield index and antioxidant performance index, confirmed that a moderate red/blue light ratio of 0.68 achieved the optimal trade-off between biomass production and nutritional enhancement. These findings reveal distinct organ-specific responses to supplemental blue light and underscore the value of spectral fine-tuning to simultaneously promote both source (leaf) and sink (petiole) performance in celery grown under CEA systems. Full article

The controlled-environment cultivation of Capsicum chinense Jacq. is a high-value but input-sensitive system, where optimizing fertilization management practices (FMPs) is essential for maximizing yield and fruit quality. We tested the hypothesis that targeted FMPs—biochar, wood vinegar, and Cropmax—enhance vegetative growth, pigment accumulation, and reproductive performance in three genotypes (‘Carolina Reaper’, ‘Trinidad Scorpion’, and ‘Habanero Chocolate’) under containerized greenhouse conditions. Across biometric, pigment, and yield metrics, biochar–Cropmax combinations produced the strongest responses, increasing plant height by up to 22%, leaf number by 51%, and chlorophyll content index by 36% over controls. Yield gains were substantial: ‘Trinidad Scorpion’ reached 301.79 g plant⁻¹ (+46%), ‘Habanero Chocolate’ 142.58 g (+32%), and ‘Carolina Reaper’ showed marked improvement in mean fruit mass (5.58 g). Biochar also elevated dry matter content to 10.31% and soluble solids to 8.35 °Brix. These results demonstrate that integrating biochar-based FMPs can significantly intensify C. chinense greenhouse production while aligning with sustainable horticultural objectives. Full article

Rice is a staple crop for over half the world’s population, and accurate, timely information on its planted area and production is crucial for food security and agricultural policy, particularly in developing nations like Sri Lanka. However, reliable rice monitoring in regions like Sri Lanka faces significant challenges due to frequent cloud cover and the fragmented nature of smallholder farms. This research introduces a novel, cost-effective method for mapping rice-planted area and yield at field scales in Sri Lanka using optical satellite data. The rice-planted fields were identified and mapped using a phenologically tuned image classification algorithm that highlights rice presence by observing water occurrence during transplanting and vegetation activity during subsequent crop growth. To estimate yields, a random forest regression model was trained at the district level by incorporating a satellite-derived chlorophyll index and environmental variables and subsequently applied at the field level. The approach has enabled the creation of two decades (2000–2022) of reliable, field-scale rice area and yield estimates, achieving map accuracies between 70% and over 90% and yield estimates with less than 20% error. These highly granular results, which are not available through traditional surveys, show a strong correlation with government statistics. They also demonstrate the advantages of a rule-based, phenology-driven classification over purely statistical machine learning models for long-term consistency in dynamic agricultural environments. This work highlights the significant potential of remote sensing to provide accurate and detailed insights into rice cultivation, supporting policy decisions and enhancing food security in Sri Lanka and other cloud-prone regions. Full article

In this study, we aimed to evaluate physiological and agronomic traits in 120 sugarcane genotypes under early drought stress conditions in a field trial across various soil types. The experiment used a split-plot arrangement, with a randomized complete block design and two replications. Two different water regimes were assigned to the main plot: (1) non-water stress (CT) and (2) drought (DT) at the early growth stage, during which sugarcane was subjected to drought stress by withholding water for 4 months. The subplot consisted of 120 sugarcane genotypes. The stalk height, stalk diameter, number of stalks, photosynthetic traits including SPAD chlorophyll meter reading (SCMR) and maximum quantum efficiency of photosystem II photochemistry (Fv/Fm), and normalized difference vegetation index (NDVI) were measured at 3, 6, and 9 months after planting (MAP). Yield and yield component parameters were measured at 12 MAP. Drought treatments lead to significant changes in various physiological traits in the sugarcane. Clustering analysis classified 36 sugarcane varieties grown in sandy loam soil and 15 genotypes in loam soil into two main clusters. In sandy loam soils, Biotec4 and CO1287 exhibited outstanding performance in drought conditions, delivering high cane yields. Meanwhile, in loam soil, MPT13-118, MPT07-1, Q47, F174, MPT14-1-902, and UT1 exhibited the best drought tolerance. Under drought conditions, cluster 1 showed higher values for SCMR, NDVI, height growth rate (HGR), cane yield, and drought tolerance index compared to cluster 2. These findings suggest that breeders can utilize these genotypes to enhance drought resistance, and the identified physiological traits can assist in selecting stronger candidates for drought tolerance. Full article

Modern agriculture requires effective and sustainable tools to enhance crop performance while minimizing the environmental impact. In this context, the application of fungal-derived bioactive compounds directly onto seeds represents a promising alternative. In this study, tomato seeds (Solanum lycopersicum) were subjected to mycopriming treatment using two fungal extracts obtained from the mycelium and culture filtrate of Talaromyces ruber. Two independent greenhouse trials were conducted to assess germination dynamics, morphometric traits, and physiological parameters (chlorophyll content, flavonol index, and anthocyanin index). Although germination rates were not significantly affected, root development was consistently enhanced by the treatments compared with the control group in both experiments. In contrast, no clear improvement was observed in shoot growth or leaf physiological parameters. Overall, the application of T. ruber extracts via seed priming proved to be a feasible strategy to stimulate early-stage root development in tomatoes, potentially contributing to improved seedling vigor and agronomic performance. These findings support the potential use of fungal extracts as practical tools for improving seedling quality in commercial nursery production. Full article

Manure application may improve plant growth, yield, and ecological sustainability. This study investigates optimized organic fertilizer application methods for enhancing buckwheat (Fagopyrum esculentum) productivity in semi-arid conditions. Treatments include broadcasting (Br) and subsurface banding (Ba) of poultry (PM) and cattle (CM) manure and foliar spraying (S) of manure extracts (1:5 and 1:10 ratios), urea fertilizer (UF), and a control. Subsurface-banded poultry manure (BaPM) maximized chlorophyll b (4.0 µg/mL), carotenoids (2.30 µmol/mL), anthocyanin (0.02 µmol/mL), leaf area index (2.03), seed nitrogen (3.4%), and spikes per plant (17). BaPM achieved the highest seed yield (646 kg/ha), comparable to BrPM, BaCM, and SPM(1:5). The maximum seed phosphorus content (0.43%) was observed in the BaPM, BrPM, and SCM(1:10) treatments. Dry matter peaked under UF (4870 kg/ha) and BaPM (4641 kg/ha). Banding placement improved nutrient uptake by enhancing root zone retention, while foliar poultry extract (1:5) mitigated phosphorus deficiency. These findings demonstrate that integrating certain manure types with targeted application methods—particularly subsurface banding of poultry manure—optimizes nutrient use efficiency, crop performance, and environmental sustainability in buckwheat cultivation. Full article

Climate change may soon impact popcorn productivity. The aim was to assess physiological and growth traits in two popcorn genotypes with different water use efficiency under water-deficit stress. The plants were grown in a greenhouse under either water stress (WS) or non-water stress (WW) conditions. Gas exchange, chlorophyll fluorescence, and leaf temperature were assessed every three days, for a total of nine measurements. At the end of the assessment period, growth traits and the SPAD index were evaluated. Our hypotheses were as follows: (a) plants of the P7 genotype (water-efficient agronomic genotype) would take longer than L65 plants (water-inefficient agronomic genotype) to reduce photosynthetic rates under water stress conditions; (b) after re-irrigation, P7 plants would recover photosynthetic capacity with values similar to the period without water stress; and (c) P7 plants would recover photosynthetic capacity faster than L65 plants when subjected to the same period of water stress. The P7 genotype (agronomic water-efficient genotype) absorbed water more quickly due to higher root biomass, root length, and root volume. Yet, at 14 days after suspending irrigation (DASI), the P7 genotype had the lowest net CO₂ assimilation rate (A_net), stomatal conductance (g_s), and transpiration rates (E) values. However, L65 (agronomic water-inefficient genotype) had the lowest A_net, g_s, and E values only at 17 DASI. As a consequence of stomatal closure in both genotypes, the E rates were reduced, and there was an increase in leaf temperature for WS plants, while L65 had higher leaf temperature at maximum water stress. No photochemical damage was detected, indicating that the reduced A_net in WS was likely due to stomatal limitations and biochemical disturbances in both genotypes. Photosynthetic recovery occurred gradually, with full restoration of rates in both genotypes at the end of the experiment. Although our initial hypothesis expected the P7 genotype to maintain photosynthesis longer under water stress, our findings showed an earlier decline in A_net compared to L65. This result is likely due to the large root system of P7 exhausting the limited soil water more rapidly in pot conditions, accelerating the onset of stress. Full article

Maize (Zea mays L.) is a key global cereal crop with significant relevance to food security. Maize yield prediction is challenged by cultivar diversity and varying management practices. This preliminary study was conducted at Youyi Farm, Heilongjiang Province, China. Three maize cultivars (Songyu 438, Dika 1220, Dika 2188), two fertilization rates (700 and 800 kg·ha⁻¹), and three planting densities (70,000, 75,000, and 80,000 plants·ha⁻¹) were evaluated across 18 distinct cropping treatments. During the V6 (Vegetative 6-leaf stage), VT (Tasseling stage), R3 (Milk stage), and R6 (Physiological maturity) growth stages of maize, multi-temporal canopy spectral images were acquired using an unmanned aerial vehicle (UAV) equipped with a multispectral sensor. In situ measurements of key agronomic traits, including plant height (PH), stem diameter (SD), leaf area index (LAI), and relative chlorophyll content (SPAD), were conducted. The optimal vegetation indices (VIs) and agronomic traits were selected for developing a maize yield prediction model using the random forest (RF) algorithm. Results showed the following: (1) Vegetation indices derived from the red-edge band, particularly the normalized difference red-edge index (NDRE), exhibited a strong correlation with maize yield (R = 0.664), especially during the tasseling to milk ripening stage; (2) The integration of LAI and SPAD with NDRE improved model performance, achieving an R² of 0.69—an increase of 23.2% compared to models based solely on VIs; (3) Incorporating SPAD values from middle-canopy leaves during the milk ripening stage further enhanced prediction accuracy (R² = 0.74, RMSE = 0.88 t·ha⁻¹), highlighting the value of vertical-scale physiological parameters in yield modeling. This study not only furnishes critical technical support for the application of UAV-based remote sensing in precision agriculture at the field-plot scale, but also charts a clear direction for the synergistic optimization of multi-dimensional agronomic traits and spectral features. Full article

The application of marine algae-derived biostimulants offers a sustainable approach to improving plant performance in aromatic and medicinal crops. This study investigated the effects of four macroalgal extracts and two commercial biostimulant products on the growth, physiology, and essential oil production of Lavandula angustifolia cultivated under greenhouse conditions at CREA, Pescia (Italy). Treatments included extracts from Ascophyllum nodosum (France and Greenland), Laminaria digitata (Iceland), Sargassum muticum (Italy), two commercial formulations (a seaweed-based and an amino acid-based biostimulant), and a control receiving only standard fertilization. Over a 10-week period, plants were evaluated for multiple parameters: plant height, leaf number and area, SPAD index (chlorophyll content), above- and below-ground biomass, flower production, microbial activity in the growth substrate, and essential oil yield. Algae extracts, particularly those from A. nodosum (Greenland) and S. muticum (Venice), significantly enhanced most parameters compared to the control and commercial products. These treatments yielded higher biomass, greater chlorophyll retention, increased flower number, and improved essential oil content. Rhizosphere microbial counts were also elevated, indicating a positive interaction between algae treatments and substrate biology. The study highlights the multifunctional nature of marine algae, whose complex composition of bioactive compounds appears to promote plant growth and secondary metabolism through multiple pathways. The superior performance of cold- and temperate-climate algae suggests a relationship between environmental origin and biostimulant efficacy. Compared to commercial inputs, the tested algae extracts showed broader and more consistent effects. These findings support the integration of macroalgae-based biostimulants into sustainable lavender cultivation strategies. Further research is recommended to optimize formulations, validate field performance, and explore synergistic effects with beneficial microbes or organic inputs. Full article

The photochemical efficiency of photosystem II (PSII) was monitored in two-year-old seedlings from six Chilean woody sclerophyllous species differing in foliage habits (evergreen, deciduous, semi-deciduous) and leaf orientation. A common garden experiment was established in July 2020 in a Mediterranean-type climate site under two watering regimes (2 L⁻¹ seedling⁻¹ week⁻¹ for 5 months versus no irrigation). Chlorophyll a fluorescence rise kinetics (OJIP) and JIP test analysis were monitored from December 2021 to January 2022. The semi-deciduous Colliguaja odorifera (leaf angle of 65°) exhibited the highest performance in processes such as absorption and trapping photons, heat dissipation, electron transport, and level of photosynthetic performance (i.e., parameters PI_ABS F_V/F_M, F_V/F₀, and ΔV_IP). In contrast, the evergreen Peumus boldus (leaf rolling) exhibited the opposite behavior for the same parameters. On the other hand, the deciduous Vachelia caven (small compound leaves and leaf angle of 15°) showed the lowest values for minimal and maximal fluorescence (F₀ and F_M) and the highest area above the OJIP transient (S_m) during the study period. Irrigation decreased S_m and the relative contribution of electron transport (parameter ΔV_IP) by 22% and 17%, respectively, but no clear effects of the irrigation treatments were observed among species and dates of measurement. Overall, V. caven and C. odorifera exhibited the highest photosynthetic performance, whereas P. boldus seemed to be more prone to photoinhibition. We conclude that different foliar adaptations among species influence light protection mechanisms more than irrigation treatments. Full article

The Loess Plateau (LP), Earth’s largest loess deposit, has experienced significant vegetation recovery since 2000 despite water scarcity. Using 2001–2022 satellite-derived normalized difference vegetation index (NDVI) and solar-induced chlorophyll fluorescence (SIF) data, we analyze vegetation structural (greenness) and functional (photosynthesis) responses, addressing critical knowledge gaps in cover expansion—functional enhancement relationships during ecological restoration. Sustained warming and increased moisture have consistently enhanced both the NDVI and SIF across the LP, with water availability remaining the key limiting factor for vegetation structure and function. Notably, the relative trend of SIF (RT_SIF: 3.92% yr⁻¹) significantly exceeded that of the NDVI (RT_NDVI: 1.63% yr⁻¹), producing a mean divergence (ΔRT_SIF-NDVI) of 2.38% yr⁻¹ (p < 0.01) across the LP. This divergence indicates faster functional enhancement relative to structural expansion during vegetation recovery, with grasslands exhibiting the most pronounced difference in ΔRT_SIF-NDVI compared to forests and shrublands. Hydrothermal conditions regulated vegetation structural–functional divergence, with regions experiencing stronger water stress exhibiting significantly greater ΔRT_SIF-NDVI values. These findings demonstrate substantial hydrological constraint alleviation since 2001. Increased precipitation enhanced light use efficiency, accelerating photosynthetic function—especially in grasslands due to their rapid precipitation response. In contrast, forests maintained higher structure–function synchrony (lower values of ΔRT_SIF-NDVI) through conservative strategies. Our findings indicate that grasslands may evolve as carbon sink hotspots via photosynthetic overcompensation, whereas forests remain reliant on sustaining current vegetation and are constrained by deep soil water deficits. This contrast highlights the value of ΔRT_SIF-NDVI as a physiologically based indicator for quantifying restoration quality and predicting carbon sequestration potential across the LP. Full article

Bonellia nervosa is an understory tree with reverse phenology in tropical dry forests (TDFs), where seasonal water and temperature stress typically shape plant phenology and trait expression. This species is heliophytic and phreatophytic, relying on high light availability and deep-water access during the dry season. However, the role of dry-season light variation in influencing leaf traits of species with inverted phenology remains poorly understood. We examined how plant size, reproductive stage, and canopy structure influence trait variation in B. nervosa during the dry season. We measured plant height and diameter, reproductive status, and canopy structure using hemispherical photographs to estimate canopy openness, leaf area index, and transmitted light. Leaf structural traits included specific leaf area (SLA), thickness, water content, and stomatal density, while photochemical performance was assessed via chlorophyll fluorescence and rapid light curves. Principal component analysis and linear regression were used to examine trait–environment relationships. Photosynthetic efficiency was not affected by plant size or reproductive status. No strong trait correlations were observed for leaf water content and stomatal density. A negative relationship between canopy openness, transmitted light, and SLA indicates structural leaf adaptation to light conditions, with lower SLA values occurring under reduced light. In B. nervosa, leaf traits are driven more by light than by water availability during the dry season. This suggests that reverse phenology in phreatophytic species is functionally decoupled from seasonal water stress. Full article

This study employed a pot experiment to compare the effects of varying application rates of chili straw biochar on seed germination and seedling growth of alfalfa (Medicago sativa L.) cultivated in electrolytic manganese residue (EMR) and to elucidate the underlying mechanisms. We aimed to provide a theoretical basis for vegetation restoration and manganese pollution control at EMR disposal sites. Our results indicated that while chili straw biochar did not affect the seed germination rate, it significantly enhanced the germination energy. In addition, treatment with 5% biochar significantly increased the germination index. Biochar application increased alfalfa seedling height (6.13 cm in the control group vs. 6.63–7.20 cm in the treated groups). Concurrently, the aboveground fresh biomass significantly increased by 49–77% compared to the control. Additionally, biochar application elevated chlorophyll content and reduced malondialdehyde content in alfalfa leaves. Correlation analysis revealed that the primary mechanisms underlying biochar-mediated improvement in seed germination and seedling growth involved enhancing the organic matter, available nitrogen, and available phosphorus content in the EMR, while decreasing the available manganese content. Overall, the application of 5% biochar in EMR optimally improved alfalfa plant growth and development. Full article

This study addresses the need for efficient and non-destructive monitoring of the nutrient status of hardy kiwi (Actinidia arguta), a plantation crop native to East Asia. Traditional nutrient monitoring methods are labor-intensive and often destructive, limiting their practicality in precision agriculture. To overcome these challenges, we deployed a rotary-wing unmanned aerial vehicle (UAV) equipped with a multispectral camera to capture monthly images of 10 hardy kiwi orchards in South Korea from June to October 2019. We extracted spectral bands (i.e., red, red-edge, green, and near-infrared) to generate normalized difference vegetation index and canopy chlorophyll content index maps, which were correlated with in situ chlorophyll measurements using a chlorophyll meter. Strong positive correlations were observed between vegetation indexes and actual chlorophyll content, with canopy chlorophyll content index achieving the highest predictive accuracy (average correlation coefficient > 0.84). Regression models based on multispectral data enabled reliable estimation of leaf chlorophyll across months and regions, with an average RMSE of 3.1. Our results confirmed that UAV-based multispectral imaging is an effective, scalable approach for real-time monitoring of nutrient status, supporting timely, site-specific fertilizer management. This method has the potential to enhance fertilizer efficiency, reduce environmental impact, and improve the quality of hardy kiwi cultivations. Full article