Search Results (690)

The fraction of absorbed photosynthetically active radiation (FAPAR) stands as a pivotal parameter within the Earth system, quantifying the energy exchange between vegetation and solar radiation. Accordingly, there is an urgent need for comprehensive validation studies to accurately quantify uncertainties and improve the reliability of FAPAR-based applications. This study validated five global FAPAR products, MOD15A2H, MYD15A2H, VNP15A2H, GEOV2, and GEOV3, over four boreal forest sites in North America. Qualitative quality flags (QQFs) and quantitative quality indicators (QQIs) of each product were analyzed. Time series high-resolution reference FAPAR maps were developed using the Harmonized Landsat and Sentinel-2 dataset. The reference FAPAR maps revealed a strong agreement with the in situ FAPAR from AmeriFlux (correlation coefficient (R) = 0.91; root mean square error (RMSE) = 0.06). The results revealed that global FAPAR products show similar uncertainties (RMSE: 0.16 ± 0.04) and moderate agreement with the reference FAPAR (R = 0.75 ± 0.10). On average, 34.47 ± 6.91% of the FAPAR data met the goal requirements of the Global Climate Observing System (GCOS), while 54.41 ± 6.89% met the threshold requirements of the GCOS. Deciduous forests perform better than evergreen forests, and the products tend to underestimate the reference data, especially for the beginning and end of growing seasons in evergreen forests. There are no obvious quality differences at different QQFs, and the relative QQI can be used to filter high-quality values. To enhance the regional applicability of global FAPAR products, further algorithm improvements and expanded validation efforts are essential. Full article

Carbon dioxide (CO₂) emissions due to human activities are responsible for approximately 80% of the drivers of global warming, resulting in a 1.1 °C increase above pre-industrial temperatures. This study quantified the CO₂ assimilation and productivity of the brown macroalgae Lessonia spicata in the central Pacific coast of Chile, across seasonal and daily cycles, under different environmental stressors, such as temperature and solar irradiance. Measurements were performed using an infra-red gas analysis (IRGA) instrument which had a chamber allowing for precise quantification of CO₂ concentrations; additional photophysiological and biochemical responses were also measured. CO₂ assimilation, along with the productivity and biosynthesis of proteins and lipids, increased during the spring, coinciding with moderate temperatures (~14 °C) and high photosynthetically active radiation (PAR). Furthermore, the increased production of photoprotective and antioxidant compounds, including phenolic compounds, and carotenoids, along with the enhancement of non-photochemical quenching (NPQ), contribute to the effective photoacclimation strategies of L. spicata. Principal component analysis (PCA) revealed seasonal associations between productivity, reactive oxygen species (ROSs), and biochemical indicators, particularly during the spring and summer. These associations, further supported by Pearson correlation analyses, suggest a high but seasonally constrained photoacclimation capacity. In contrast, the reduced productivity and photoprotection observed in the summer suggest increased physiological vulnerability to heat and light stress. Overall, our findings position L. spicata as a promising nature-based solution for climate change mitigation. Full article

Agrivoltaic (Agri-PV) systems face the critical challenge of balancing photovoltaic energy generation with crop productivity, yet systematic approaches to quantifying the trade-offs between these objectives remain scarce. In this study, we identify nine essential design indicators: panel tilt angle, elevation, photovoltaic coverage ratio, shading factor, land equivalent ratio, photosynthetically active radiation (PAR) utilization, crop yield stability index, water use efficiency, and return on investment. We introduce a novel dual matrix Analytic Hierarchy Process (AHP) to evaluate their relative significance. An international panel of eighteen Agri-PV experts, encompassing academia, industry, and policy, provided pairwise comparisons of these indicators under two objectives: maximizing annual energy yield and sustaining crop output. The high consistency observed in expert responses allowed for the derivation of normalized weight vectors, which form the basis of two Weighted Influence Matrices. Analysis of Total Weighted Influence scores from these matrices reveal distinct priority sets: panel tilt, coverage ratio, and elevation are most influential for energy optimization, while PAR utilization, yield stability, and elevation are prioritized for crop productivity. This methodology translates qualitative expert knowledge into quantitative, actionable guidance, clearly delineating both synergies, such as the mutual benefit of increased elevation for energy and crop outcomes, and trade-offs, exemplified by the negative impact of high photovoltaic coverage on crop yield despite gains in energy output. By offering a transparent, expert-driven decision-support tool, this framework enables practitioners to customize Agri-PV system configurations according to local climatic, agronomic, and economic contexts. Ultimately, this approach advances the optimization of the food energy nexus and supports integrated sustainability outcomes in Agri-PV deployment. Full article

Leaf phenology is key to ecosystem functioning by regulating carbon, water, and energy fluxes and influencing vegetation productivity. Yet, detecting land surface phenology (LSP) in drylands using remote sensing remains particularly challenging due to sparse and heterogeneous vegetation cover, high spatiotemporal variability, and complex spectral signals. Unlike the Northern Hemisphere, these challenges are further compounded in the Southern Hemisphere (SH), where several regions experience year-round moderate temperatures. When combined with irregular rainfall, this leads to highly variable vegetation activity throughout the year. However, LSP dynamics in the SH remain poorly understood. This study presents a review of remote sensing-based phenology research in drylands, integrating (i) a synthesis of global methodological advances and (ii) a systematic analysis of peer-reviewed studies published from 2015 through April 2025 focused on SH drylands. This review reveals a research landscape still dominated by conventional vegetation indices (e.g., NDVI) and moderate-spatial-resolution sensors (e.g., MODIS), though a gradual shift toward higher-resolution sensors such as PlanetScope and Sentinel-2 has emerged since 2020. Despite the widespread use of start- and end-of-season metrics, their accuracy varies greatly, especially in heterogeneous landscapes. Yet, advanced products such as solar-induced chlorophyll fluorescence or the fraction of absorbed photosynthetically active radiation were rarely employed. Gaps remain in the representation of hyperarid zones, grass- and shrub-dominated landscapes, and large regions of Africa and South America. Our findings highlight the need for multi-sensor approaches and expanded field validation to improve phenological assessments in dryland environments. The accurate differentiation of vegetation responses in LSP is essential not only for refining phenological metrics but also for enabling more realistic assessments of ecosystem functioning in the context of climate change and its impact on vegetation dynamics. Full article

Ratoon rice is a sustainable planting model, and its yield is closely linked to the light and temperature use efficiency. The photothermal quotient (PQ), a key parameter for evaluating the light and temperature use efficiency, significantly influences ratoon rice yield. However, research on how different stubble heights affect PQ and the utilization efficiency of light and temperature resources remains limited. Here, we conducted a two-year field experiment to investigate the radiation use efficiency (RUE), effective accumulated temperature use efficiency (TUE), PQ, interception percentage (IP), intercepted photosynthetically active radiation (IPAR), and total dry weight (TDW) of six ratoon rice varieties under two stubble height treatments (HS: high stubble, LS: low stubble) during the ratoon season. This study aimed to analyze how different stubble heights impact ratoon rice yield by evaluating light and temperature resource utilization efficiency and investigates the relationship between PQ and ratoon rice yield. The results showed that the HS treatment significantly increased ratoon season yield compared to LS treatment, with average yield increases of 21.2% and 28.1% in 2022 and 2023, respectively. This yield enhancement was attributed to improved TDW under HS treatment, driven by increased IP, IPAR, RUE, and TUE. Notably, PQ was significantly lower under HS than under LS treatment. This reduction was primarily attributed to the decreased duration available for light and heat accumulation, consequently lowering PQ. Correlation analysis revealed a significant positive association between main season yield and PQ, while ratoon season yield exhibited a negative correlation with PQ. In conclusion, the HS treatment increased IP and IPAR, enhanced TUE and RUE, and reduced PQ, collectively contributing to higher ratoon season yields. Importantly, our findings indicate that PQ can more effectively predict yield changes in the ratoon season under HS treatment, providing a theoretical basis for optimizing light and temperature resource utilization in ratoon rice. Full article

Typhoons are major climate disturbances that significantly impact coastal ecosystems, particularly mangrove forests. This study examines the effects of typhoons on mangrove communities at different stages of recovery, focusing on how environmental factors influence carbon storage and net ecosystem exchange (NEE). Three mangrove sites were selected based on their recovery age: young, moderately restored, and mature. The results revealed that typhoons had the most pronounced effect on young mangroves, resulting in significant reductions in both above-ground and soil carbon storage. In contrast, mid-aged and mature mangroves demonstrated greater resilience, with mature mangroves recovering most rapidly in terms of community structure and carbon storage. Key factors such as wind speed, heavy rainfall, and changes in photosynthetically active radiation (PAR) contributed to carbon storage losses, particularly in young mangrove forests. This study underscores the importance of recovery age in determining mangrove resilience to extreme weather events and offers insights for enhancing restoration and conservation strategies to mitigate the impacts of climate change on coastal carbon sequestration. Full article

Increased market demand for plant herbs has prompted growers to ensure a continuous and assured supply of superior nutritional quality over the years. Apart from the nutritional value, culinary herbs contain phytochemical benefits that can improve human health. However, a significant amount of research has focused on enhancing yield, frequently overlooking the impact of production practices on the antioxidant and phytonutritional content of the produce. Thus, the study aimed to evaluate the yield, phytonutrients, and essential mineral profiling in selected aromatic herbs and their intricate role in nutritional quality when grown under different production systems. Five selected aromatic herbs (coriander, rocket, fennel, basil, and moss-curled parsley) were evaluated at harvest when grown under three production systems: in a gravel-film technique (GFT) hydroponic system and in soil, both under the 40% white shade-net structure, as well as in a soilless medium using sawdust under a non-temperature-controlled plastic tunnel (NTC). The phytonutritional quality properties (total phenolic, flavonoids, β-carotene-linoleic acid, and condensed tannins contents) as well as 1,1-diphenyl-2-picrylhydrazyl (DPPH) were assessed using spectrophotometry, while vitamin C and β-carotene were analyzed using HPLC-PDA, and leaf mineral content was evaluated using ICP-OES (Inductively Coupled Plasma Optical Emission Spectrometry). The results show that the health benefits vary greatly owing to the particular culinary herb. The fresh leaf mass (yield) of coriander, parsley, and rocket was not significantly affected by the production system, whereas basil was high in soil cultivation, followed by GFT. Fennel had a high yield in the GFT system compared to in-soil and in-soilless cultivation. The highest levels of vitamin C were found in basil leaves grown in GFT and in soil compared to the soilless medium. The amount of total phenolic and flavonoid compounds, β-carotene, β-carotene-linoleic acid, and DPPH, were considerably high in soil cultivation, except on condensed tannins compared to the GFT and soilless medium, which could be a result of Photosynthetic Active Radiation (PAR) values (683 μmol/m²/s) and not favoring the accumulation of tannins. Overall, the mineral content was greatly influenced by the production system. Leaf calcium and magnesium contents were highly accumulated in rockets grown in the soilless medium and the GFT hydroponic system. The results have highlighted that growing environmental conditions significantly impact the accumulation of health-promoting phytonutrients in aromatic herbs. Some have positive ramifications, while others have negative ramifications. As a result, growers should prioritize in-soil production systems over GFT (under the shade-net) and soilless cultivation (under NTC) to produce aromatic herbs to improve the functional benefits and customer health. Full article

Evapotranspiration (ET) is an important part of agricultural water consumption, yet little is known about nocturnal evapotranspiration (ETN) patterns. An eddy covariance system was used to observe ET over five consecutive years (2020–2024) during the growing season in a dry farming area of the Loess Plateau. Daytime and nocturnal evapotranspiration were partitioned using the photosynthetically active radiation threshold to reveal the changing characteristics of ETN at multiple time scales and its control variables. The results showed the following: (1) In contrast to the non-significant trend in ETN on the diurnal and daily scales, monthly ETN dynamics exhibited two peak fluctuations during the growing season. (2) The contribution of ETN to ET exhibited seasonal characteristics, being relatively low in summer, with interannual variations ranging from 10.9% to 14.3% and an annual average of 12.8%. (3) The half-hourly ETN, determined by machine learning methods, was driven by a combination of factors. The main driving factors were the difference between surface temperature and air temperature (Ts-Ta) and net radiation (Rn), which have almost equivalent contributions. Regression analysis results suggested that Ta was the main factor influencing ETN/ET at the monthly scale. This study focuses on the nighttime water loss process in dry farming fields in Northwest China, and the results provide a basis for rational allocation and efficient utilization of agricultural water resources in arid regions. Full article

Background: Understanding canopy light interception is essential for optimizing forage production and improving the efficiency of grazing systems. Accurate quantification of photosynthetically active radiation (PAR) intercepted by the canopy allows for better estimation of crop coefficients and growth dynamics. This study aimed to assess the forage mass and nutritional value of Guinea grass pastures managed under two grazing frequencies, defined by 90% and 95% light interception (LI) measured using AccuPar equipment, and two post-grazing stubble heights (30 and 50 cm). Evaluations were conducted during both the rainy season and a dry year to capture seasonal variability in pasture performance. Methods: The experimental design was of completely randomized blocks with four replications. Results: The treatment whit 90% LI resulted in higher values of crude protein and digestible. However, 95% LI resulted in higher values of neutral detergent insoluble nitrogen and acid detergent insoluble nitrogen values in grass pastures Guinea. The highest value of forage mass in Guinea grass was reported with 95% LI in association with a post-grazing height of 30 cm. Conclusions: Management of light interception at 90% provided a reduced amount of forage with better nutritional value. Pasture management considering the light interception technology with the AccuPar equipment was efficient as a pattern for interrupting pasture regrowth in the vegetative phase. Full article

As an essential part of terrestrial ecosystems, forests are key to sustaining ecological balance, supporting the carbon cycle, and offering various ecosystem services. In recent years, forests in Southwest China have experienced notable greening. However, the rising occurrence and severity of droughts present a significant threat to the stability of forest ecosystems in this region. This study adopted the near-infrared reflectance of vegetation (NIRv) and the lag-1 autocorrelation of NIRv as indicators to assess the dynamics and resilience of forests in Southwest China. We identified a progressive decline in forest resilience since 2008 despite a dominant greening trend in Southwest China’s forests during the last 20 years. By developing the eXtreme Gradient Boosting (XGBoost) model and Shapley additive explanation framework (SHAP), we classified forests in Southwest China into coniferous and broadleaf types to evaluate the driving factors influencing changes in forest resilience and mapped the spatial distribution of dominant drivers. The results showed that the resilience of coniferous forests was mainly driven by variations in elevation and land surface temperature (LST), with mean absolute SHAP values of 0.045 and 0.038, respectively. In contrast, the resilience of broadleaf forests was primarily influenced by changes in photosynthetically active radiation (PAR) and soil moisture (SM), with mean absolute SHAP values of 0.032 and 0.028, respectively. Regions where elevation and LST were identified as dominant drivers were mainly distributed in coniferous forest areas across central, eastern, and northern Yunnan Province as well as western Sichuan Province, accounting for 32.9% and 20.0% of the coniferous forest area, respectively. Meanwhile, areas where PAR and SM were dominant drivers were mainly located in broadleaf forest regions in Sichuan and eastern Guizhou, accounting for 29.9% and 27.7% of the broadleaf forest area, respectively. Our study revealed that the forest greening does not necessarily accompany an enhancement in resilience in Southwest China, identifying the driving factors behind the decline in forest resilience and highlighting the necessity of differentiated restoration strategies for forest ecosystems in this region. Full article

Short fruiting branch cotton (SFBC) has a compact plant architecture suitable for dense planting. Plant population density (PPD) and topping are important agronomic practices to achieve high yielding by optimizing cotton plant structure. However, their individual and interactive effects on SFBC growth and yield are poorly understood. This study aimed to explore cotton growth and yield responses to various combinations of PPD and topping time (TT) and the underlying physio-ecological mechanism. Four combinations were included in a two-year field experiment (2023–2024) involving two PPD levels (5.3 plants m⁻², low density LD; 8 plants m⁻², high density HD) and two TT levels (early topping for leaving ten sympodials per plant ET; late topping for leaving fifteen sympodials per plant LT), and compared in terms of biomass accumulation, photosynthetically active radiation capture, and leaf senescence during entire reproductive growth period. Compared to the other three combinations, the combination of HD and LT (HDLT) achieved a higher lint yield due to a greater biological yield, which was predominantly attributed to the higher average rate during the rapid biomass increasing period. Owing to delayed leaf senescence caused by the HD and the LT, the HDLT performed better in leaf senescence-related attributes at the late growth stage. Moreover, these improved attributes also contributed to a higher radiation interception rate and photosynthetic efficiency at the late growth stage. Taken together, combining high density with later topping tends to increase the lint yield of SFBC through increasing dry matter accumulation, delaying leaf senescence, and enhancing canopy radiation interception rate at the late growth. Full article

Agriphotovoltaic (Agri-PV) systems are a dual-purpose solution for resolving land utilization conflicts through combining agricultural practices and photovoltaic power generation. However, the reduced light intensities and altered microclimatic conditions under PV modules may have negative effects on the productivity of crops. This study investigated whether incorporating arbuscular mycorrhizal fungi (AMF) inoculation into Agri-PV systems could mitigate such limitations for mint cultivation (Mentha arvensis and Mentha × piperita). A field trial was conducted in Bandırma, Türkiye, where both mint species were grown under and between PV panels, with and without AMF. The photosynthetically active radiation (PAR), temperature, fresh biomass, nutrient uptake, and essential oil content were evaluated. PAR was reduced by more than 90% under panels, while air temperatures were 1.0–1.6 °C lower than those in the between-panel areas. AMF inoculation significantly improved the yield and quality. In Mentha arvensis, the fresh herb yield increased by 43.4% (from 10,620 to 15,230 kg ha⁻¹), and the essential oil content reached 10.08% under between-panel mycorrhizal conditions. For Mentha × piperita, the highest menthol concentration (30.38%) was observed exclusively in between-panel plots with AMF. In contrast, the highest oil content (4.50%) was achieved under shaded, mycorrhizal conditions, indicating that both light exposure and microbial interactions shape biochemical responses. This is the first study to demonstrate the synergistic impact of AMF inoculation and agrivoltaic shading on essential oil crops. This paper presents a novel and sustainable model that enhances crop productivity and biochemical quality in solar-integrated agriculture. Full article

Photosynthetically Active Radiation (PAR) is critical for sustaining plant growth in the ground and on building surfaces, but how to accurately predict PAR availability in a complex urban environment can be a challenge. Using an advanced ray-tracing software (Radiance 4.0) and local weather data, this study presents a dynamic analysis of the effects of layout, façade orientation and height on PAR availability in four high density residential areas in Shanghai city, China. A metric system was also adopted using three light level requirements of outdoor plants (low, medium, high light levels). Key findings included: (1) the urban layout with the highest ratio of building height to north–south facing adjacent building separation achieved the higher levels of PAR availability for low/medium light level plants and the lower levels of PAR availability for high-light plants for middle and low façades and the ground, while high façades in all layouts could see similar PAR availability for all plants. (2) The PAR availability for low/medium-light plants decreased with the increasing façade height, while the PAR availability for high-light plants showed the opposite trend. (3) The north façade and its ground had higher levels of PAR availability for low/medium-light plants and lower levels of PAR availability for high-light plants than other façades. (4) All layouts offered more opportunities to apply high-light and medium-light plants at façades and the ground. Full article

With the advent of the big data era in ocean remote sensing and fisheries, there is a growing demand for finer temporal scales to predict spatial distribution of the jumbo flying squid (Dosidicus gigas). This can help reduce fuel costs and provide higher quality and faster decision-making. Therefore, this study employed a deep neural network (DNN) model, using sea surface temperature, sea surface height, sea surface salinity, and photosynthetically active radiation as input factors, with catch per unit effort as the output factor. We construct five cases with temporal scales of 3, 6, 10, 15, and 30 days using data spanning 10 years (2012–2021). Additionally, the performance of DNN was compared with those of traditional methods such as generalized additive model (GAM), extreme gradient boosting (XGBoost), and artificial neural network (ANN). The results demonstrated that the DNN model had the best performance. As the temporal scale decreased, the mean squared error and the mean absolute error increased, whereas the area under the precision−recall curve decreased, indicating a decline in model performance. The interpretability analysis indicated that spatial and temporal factors significantly contributed to the model, with longitude exhibiting the highest contribution. To improve the accuracy of finer temporal scales, future research should focus on reducing noise in the data and address the presence-only nature of fishery data, particularly by cleaning the unsampled portions. Full article

Photosynthetically active radiation (PAR) is crucial for plant growth, influencing photosynthesis efficiency and crop yield. The increasing adoption of controlled-environment agriculture (CEA) necessitates precise PAR monitoring. The high cost of commercial PAR sensors, however, limits their accessibility and widespread use, creating a growing need for a low-cost alternative capable of reliable deployment in diverse agricultural environments. Building on recent advancements in PAR sensing using multi-channel spectral sensors such as the AS7341 and AS7265, this study develops the electronics for an AS7341-based, open-source, cost-effective (~USD 50) PAR sensor validated across a broad PPFD range and conditions, ensuring reliability and ease of replication. It uses a relatively simple multi-linear regression that offers real-time applications without energy intensive machine learning. The developed sensor is calibrated against the industry-standard Apogee SQ-500SS PAR sensor in four distinct farming environments: (i) horizontal grow lights, (ii) vertical agrotunnel lighting, (iii) agrivoltaics, and (iv) in greenhouses. A mean error ranging from 1 to 5% indicates its suitability for controlled environment farming and continuous data logging. The open-source hardware design and systematic installation guidelines enable users to replicate, calibrate, and integrate the sensor with minimal background in electronics and optics. Full article