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In Ghana, maize (Zea mays) is a crop crucial to achieving food and nutrition security. Maize consumption has increased exponentially over the past decades and contributes to 25% of the caloric consumption in the country. In order to assist in decision-making and guide investment in sustainable intensification of maize production, this study set out to identify the determinants of yield and to arrive at potential interventions for closing the maize yield gap. These were quantified using analytical approaches that combine a light use efficiency crop model (LINTUL-1) with statistical and geospatial analyses. Legacy data, auxiliary covariables, and maize fertilizer trials on eight experimental stations in Ghana were used in this study. Overall, the maize yield gap across the stations and trial treatments ranged from 17% to 98%. The variation in yield gap within a single station indicates a significant scope for closing the yield gap through site-specific nutrient management. Multiple linear regression models that explained 81% of the variability in maize yield gap identified soil organic matter, soil water-holding capacity, root zone depth, rainfall, sulfur fertilizer, and nitrogen fertilizer, in that order of importance, as the major determinants for closing the yield gap in the major agroecological zones of Ghana. The yield gap decreased by 1.4 t ha-1 with a 1% increase in soil organic matter. A 1 mm increase of the soil waterholding capacity reduced the yield gap by 1.06 t ha-1, while an increase in pH and in the application of potassium fertilizer widened the gap. These results suggest that both soil physical and chemical properties, together with weather data, should be taken into consideration to arrive at site-specific fertilizer recommendation and other agronomic practices. [ABSTRACT FROM AUTHOR]

The development of models for yield prediction in greenhouse sweet peppers may help improve yield and labour productivity. We aimed to monitor the growth and yield of hydroponically grown sweet pepper plants without destructive sampling. First, we constructed a prediction model and validated it in a cultivation experiment. In the developed model, daily node appearance and light use efficiency were predicted from daily mean air temperature and daytime carbon dioxide (CO2) concentration. The daily light interception was obtained by non-destructive leaf area estimation. Second, we validated the model through the cultivation experiment. The predicted total dry matter production at 200 days after transplanting (DAT), 1,379 g/m2, fell within the range of the observed value, 1,353 ± 46 g/m2 (mean ± SE). The predicted and observed yields at 200 DAT were 7.90 kg/m2 and 7.73 ± 0.82 kg/m2, respectively. We approximately predicted node appearance, total dry matter production, and fruit yield, while partially succeeding in predicting leaf area index and dry matter partitioning to fruit. Our non-destructive prediction model can be an effective tool for growers and to improve the yield of sweet pepper production.

The Photochemical Reflectance Index (PRI) and solar induced fluorescence (SIF) provide information on plant photosynthetic activity. PRI and SIF are both strongly influenced by irradiance, but uncertainties related to the interpretation of these light responses at large spatial scales remain, partly due to a shortage of suitable data from aircraft or satellite platforms. The goal of this study was to explore interpretations of the PRI- and SIF-light responses of trees owing to species, functional types (evergreen and deciduous) and season. Using airborne hyperspectral and ultraspectral imagery in a North American urban forest, we derived PRI, SIF, and albedo (an indicator of illumination) at the 1-m pixel level. We then quantified crown-level PRI and SIF light responses of ten different tree species at three time points from late-summer to autumnal senescence using hierarchical models. Our results confirmed that both PRI and SIF were strongly influenced by illumination with PRI decreasing and SIF increasing with illumination. Both slope and intercept of the PRI-albedo relationship changed with season, but the pattern varied among species and functional types. SIF values decreased during autumnal senescence for all species, but evergreen species exhibited less seasonal decline in the slope of SIF-albedo relationship compared to deciduous species. The PRI and SIF light responses derived from the airborne imagery offer complementary information on dynamic photosynthesis responses presumably due to varying canopy structure, pigmentation and photoprotection among species and functional types. From airborne platforms, PRI- and SIF-light responses can be used to explore the contrasting physiological responses of individual tree crowns, providing a spatially and temporally explicit view of dynamic plant traits related to photoregulation and a novel view of functional diversity for entire landscapes. • PRI and SIF light responses of trees were fitted using airborne data. • Both PRI and SIF were strongly influenced by illumination. • PRI and SIF light responses varied among species, functional types and season. • PRI and SIF light responses revealed dynamic photosynthetic characteristics. [ABSTRACT FROM AUTHOR]

Edible halophyte Portulaca oleracea L., known as purslane, was grown in two percentages of artificial seawater (ASW) under two combined red (R) and blue (B) LED spectra. High salinity (40% ASW) negatively affected shoot productivity and leaf growth of purslane compared to those grown in 10% ASW. Photosynthetic pigment and total reduced nitrogen concentrations were significantly higher in purslane grown in 10% ASW than in 40% ASW. However, LED spectral quality did not markedly influence these parameters. Grown in 10% ASW under R/B 2.2, purslane had the highest maximum nitrate reductase activity, while those in 40% ASW under R/B 2.2 had the highest activation state. Under both light qualities, purslane had a sevenfold increase in proline concentration in 40% ASW than in 10% ASW. Total phenolic compounds’ concentration was the highest in 10% ASW under R/B 0.9, while there were no significant differences in the accumulation of total soluble sugars and ascorbic acids among all plants. Antioxidant enzymes activities were lower in 40% ASW under R/B 2.2 compared to the other conditions. In conclusion, salinity affected the yield, physiology and nutritional quality of purslane. The impacts of LED spectral quality on purslane were only reflected by certain physiological and nutritional parameters.

High-density planting is an effective technique to optimize yields of mulched cotton. On the other hand, deficit irrigation is an emerging water-saving strategy in cotton cultivation, especially suitable for arid and water-scarce areas. However, the relationships between deficit irrigation, high-density planting, and regulation mechanisms of canopy light radiation and light use efficiency (LUE) in cotton is not yet clear. To clarify the mechanism of light interception (LI) and the LUE of cotton canopies, three irrigation treatments [315 (50% Fc), 405 (75% Fc, farmers’ irrigation practice), and 495 mm (100% Fc), where Fc was the field capacity] with three plant densities [13.5, 18.0 (farmers’ planting practice), and 22.5 plants m2] were applied. The findings of this research revealed that, under deficit irrigation, the above-ground dry matter (ADM) was reduced by 5.05% compared to the farmers’ irrigation practice. Over both years and across all plant densities, LI and LUE under deficit irrigation decreased by 8.36% and 4.79%, respectively, relative to the farmers’ irrigation practices. In contrast, LI and LUE for the highest irrigation level increased by 10.59% and 5.23%, respectively. In the case of the interaction (plant density and irrigation level), the ADM under deficit irrigation and high-density combination increased by 7.69% compared to the control (farmers’ irrigation × sowing practices interaction effects). The LI and LUE also exhibited an increase in 1.63% and 6.34%, respectively. Notably, the LI effect of the middle and upper cotton canopy under film drip irrigation reached 70%. A lower irrigation level resulted in a higher percentage of LI in the lower canopy region. The leaf area index, light interception rate, and extinction coefficient escalated with the increase in plant density. Under deficit irrigation treatment, the LI of the 0–30 cm canopy in high plant density settings increased by 8.6% compared to the control (farmers’ irrigation × sowing practices interaction effects). In conclusion, deficit irrigation and increased plant density improved the interception of LI and LUE of cotton canopy. These findings may help the farmers to optimize their agricultural management strategies in water-deficient areas.

Zoigê wetland is located in the southeastern edge of the Qinghai–Tibet Plateau, in recent years, the wetland local area grassland productivity decline, land sanding, and other serious degradation phenomenon. Using remote sensing and hydrology data combined with the basic principles of vegetation ecology, we applied the Carnegie–Ames–Stanford Approach (CASA) model and Boreal Ecosystem Productivity Simulator (BEPS) model to invert the net primary productivity (NPP) of the Zoigê wetland ecosystem and then identified the deficiencies of the two models. In this article, we tested the factors that influence the light use efficiency of vegetation and considered the effects of livestock grazing on grassland ecosystems and wetland moisture content on vegetation growth. A new grazing coupled remote sensing process (GCRSP) model suitable for the productivity of the Zoigê wetland was proposed. Field survey data were combined with the CASA model, BEPS model, and Moderate Resolution Imaging Spectroradiometer (MODIS) NPP product, and the accuracy of the proposed GCRSP model was analyzed at regional level. The results show that after fitting the field measurements to the GCRSP model, the fitted variance between the model and the measured data is 0.84, which is larger than the variance between the other two methods and the measured data. In addition, the variance of the linear fit between the GCRSP model and the MODIS NPP product was 0.11, which was relatively small, indicating that the regional-scale GCRSP model was relatively accurate for the Zoigê wetland NPP. Therefore, this model was suitable for the inversion of regional-scale NPP. The results indicated that the average grassland NPP of the Zoigê wetland was 487.57 gC/m2, and larger NPP values were distributed near the rivers and wetland and smaller NPP values were distributed in the mountain glacier and desertified land areas. These results were consistent with the regional characteristics. This article provided technical and theoretical support for the desertification management of the Zoigê grassland and a new method for studying vegetation NPP, and the findings could help improve the accuracy of regional-scale vegetation NPP estimates.

Abstract Vertical farming is a relatively new fresh fruit and vegetable production system, where lamps (mostly light emitting diodes [LED]) are the sole light source. A high light use efficiency (LUEinc), defined as shoot dry weight per incident photosynthetic photon flux density (PPFD; g mol−1) integral, is crucial for the economic viability of vertical farming. Very different values for LUEinc have been reported in the literature and it is not clear whether LUEinc is higher in vertical farming than in greenhouse or open field cultivation. Values of LUEinc of lettuce grown in a vertical farm (53 studies), greenhouse (13 studies) and open field (8 studies) were collected from literature, as well as relevant cultivation aspects such as lettuce weight at harvest, cultivation period (plant age at harvest), daily light integral, cumulative daily light integral for the whole cultivation period, planting density and CO2 concentration. The average LUEinc for lettuce grown in a vertical farm was 0.55 g mol−1 which was higher than 0.39 g mol−1 for greenhouse‐grown lettuce. Both were substantially higher than for field‐grown lettuce (0.23 g mol−1). The maximum measured LUEinc for lettuce grown in a vertical farm (1.63 g mol−1) is close to the published maximum theoretical value, which ranges from 1.26 to 1.81 g mol−1. Since all environmental factors can be fully controlled, vertical farming has the capability to achieve the theoretical maximum LUEinc. Using the highest reported LUEinc based on shoot fresh weight (44 g mol−1 at 200 μmol m−2 s−1 PPFD and 16 h photoperiod), it is estimated that each layer of a vertical farm can potentially produce annually up to 700 kg of lettuce per m2 at 500 μmol m−2 s−1 of continuous light.

The gross primary production (GPP) in tropical terrestrial ecosystems plays a critical role in the global carbon cycle and climate change. The strong 2015–2016 El Niño event offers a unique opportunity to investigate how GPP in the tropical terrestrial ecosystems responds to climatic forcing. This study uses two GPP products and concurrent climate data to investigate the GPP anomalies and their underlying causes. We find that both GPP products show an enhanced GPP in 2015 for the tropical terrestrial ecosystem as a whole relative to the multiyear mean of 2001–2015, and this enhancement is the net result of GPP increase in tropical forests and decrease in nonforests. We show that the increased GPP in tropical forests during the El Nino event is consistent with increased photosynthesis active radiation as a result of a reduction in clouds, while the decreased GPP in nonforests is consistent with increased water stress as a result of a reduction of precipitation and an increase of temperature. These results reveal the strong coupling of ecosystem and climate that is different in forest and nonforest ecosystems and provide a test case for carbon cycle parameterization and carbon-climate feedback simulation in models.

Although gross primary productivity (GPP) is estimated with remote sensing over large regions of Earth, urban areas are usually excluded due to the lack of light use efficiency (LUE) parameters for urban vegetation and the spatial heterogeneity of urban land cover. Here, we estimated midsummer GPP, both within and among vegetation and land-use types, across the Minneapolis-Saint Paul, Minnesota metropolitan region. We derived LUE parameters for urban vegetation types using estimates of GPP from tree sap flow and eddy covariance CO2 flux observations, and from fraction of absorbed photosynthetically active radiation based on 2 m resolution WorldView-2 satellite imagery. Mean GPP per unit land area (including vegetation, impervious surfaces, and soil) was 2.64 g C m−2 d−1, and was 4.45 g C m−2 d−1 per unit vegetated area. Mapped GPP estimates were within 11.4% of estimates from independent tall tower eddy covariance measurements. Turf grass GPP had a larger coefficient of variation (0.18) than other vegetation classes (~0.10). Vegetation composition was largely consistent across the study area. Excluding golf courses, mean land-use GPP for the total study area varied more by percent vegetation cover (R2 = 0.98, p < 0.001) than by variability within vegetation classes (R2 = 0.21, p = 0.19). Urban GPP in general was less than half that of natural forests and grasslands in the same climate zone.

Terrestrial primary productivity and carbon cycle impacts of droughts are commonly quantified using vapour pressure deficit (VPD) data and remotely sensed greenness, without accounting for soil moisture. However, soil moisture limitation is known to strongly affect plant physiology. Here, we investigate light use efficiency, the ratio of gross primary productivity (GPP) to absorbed light. We derive its fractional reduction due to soil moisture (fLUE), separated from VPD and greenness changes, using artificial neural networks trained on eddy covariance data, multiple soil moisture datasets and remotely sensed greenness. This reveals substantial impacts of soil moisture alone that reduce GPP by up to 40% at sites located in sub-humid, semi-arid or arid regions. For sites in relatively moist climates, we find, paradoxically, a muted fLUE response to drying soil, but reduced fLUE under wet conditions. fLUE identifies substantial drought impacts that are not captured when relying solely on VPD and greenness changes and, when seasonally recurring, are missed by traditional, anomaly-based drought indices. Counter to common assumptions, fLUE reductions are largest in drought-deciduous vegetation, including grasslands. Our results highlight the necessity to account for soil moisture limitation in terrestrial primary productivity data products, especially for drought-related assessments.

Spatially and temporally continuous estimation of plant photosynthetic carbon fixation (or gross primary production, GPP) is crucial to our understanding of the global carbon cycle and the impact of climate change. Besides spatial, seasonal and interannual variations, GPP also exhibits strong diurnal variations. Satellite retrieved solar-induced chlorophyll fluorescence (SIF) provides a spatially continuous, but temporally discrete measurement of plant photosynthesis, and has the potential to be used to estimate GPP at global scale. However, it remains unclear whether the seasonal time series of SIF snapshots taken at a fixed time of the day can be used to infer daily total GPP variation at spatial and seasonal scales. In this study, we first used GPP estimates from 135 eddy covariance flux sites, covering a wide range of geographic locations and biome types, to investigate the relationship between the instantaneous GPP (GPPᵢₙₛₜ) and daily GPP (GPPdₐᵢₗy) on the seasonal course for different times of the day. Latitudinal and diurnal patterns were found to correspond to variations in photosynthetically active radiation (PAR) and light use efficiency (LUE), respectively. We then used the Soil-Canopy Observation Photosynthesis and Energy Balance (SCOPE) model and the FluxCom GPP product to investigate the instantaneous and daily SIF-GPP relationships at five flux tower sites along a latitudinal gradient and at a global scale for different biome types. The results showed that daily SIF had a stronger linear correlation with daily GPP than instantaneous SIF at the seasonal scale, with an instantaneous to daily SIF conversion factor following the latitudinal and seasonal pattern driven by PAR. Our study highlights the necessity to take the latitudinal and diurnal factors into consideration for SIF-GPP relationship analyses or for physiological phenology analyses based on SIF.

Clouds and aerosols increase the fraction of global solar irradiance that is diffuse light. This phenomenon is known to increase the photosynthetic light use efficiency (LUE) of closed-canopy vegetation by redistributing photosynthetic photon flux density (400–700nm) from saturated, sunlit leaves at the top of the canopy, to shaded leaves deeper in the canopy. We combined a process-based carbon cycle model with 10 years of eddy covariance carbon flux measurements and other ancillary data sets to assess 1) how this LUE enhancement influences interannual variation in carbon uptake, and 2) how errors in modeling diffuse fraction affect predictions of carbon uptake. Modeled annual gross primary productivity (GPP) increased by ≈0.94% when observed levels of diffuse fraction were increased by 0.01 (holding total irradiance constant). The sensitivity of GPP to increases in diffuse fraction was highest when the diffuse fraction was low to begin with, and lowest when the diffuse fraction was already high. Diffuse fraction also explained significantly more of the interannual variability of modeled net ecosystem exchange (NEE), than did total irradiance. Two tested radiation partitioning models yielded over- and underestimates of diffuse fraction at our site, which propagated to over- and underestimates of annual NEE, respectively. Our findings highlight the importance of incorporating LUE enhancement under diffuse light into models of global primary production, and improving models of diffuse fraction.

In Ghana, maize (Zea mays) is a crop crucial to achieving food and nutrition security. Maize consumption has increased exponentially over the past decades and contributes to 25% of the caloric consumption in the country. In order to assist in decision-making and guide investment in sustainable intensification of maize production, this study set out to identify the determinants of yield and to arrive at potential interventions for closing the maize yield gap. These were quantified using analytical approaches that combine a light use efficiency crop model (LINTUL-1) with statistical and geospatial analyses. Legacy data, auxiliary covariables, and maize fertilizer trials on eight experimental stations in Ghana were used in this study. Overall, the maize yield gap across the stations and trial treatments ranged from 17% to 98%. The variation in yield gap within a single station indicates a significant scope for closing the yield gap through site-specific nutrient management. Multiple linear regression models that explained 81% of the variability in maize yield gap identified soil organic matter, soil water-holding capacity, root zone depth, rainfall, sulfur fertilizer, and nitrogen fertilizer, in that order of importance, as the major determinants for closing the yield gap in the major agroecological zones of Ghana. The yield gap decreased by 1.4 t ha-1 with a 1% increase in soil organic matter. A 1 mm increase of the soil water-holding capacity reduced the yield gap by 1.06 t ha-1, while an increase in pH and in the application of potassium fertilizer widened the gap. These results suggest that both soil physical and chemical properties, together with weather data, should be taken into consideration to arrive at site-specific fertilizer recommendation and other agronomic practices.

Diffuse radiation (If) is one of important variables determining photosynthetic rate and carbon uptake of forest ecosystems. However, the responses of gross primary productivity (GPP) and light use efficiency (LUE) to diffuse fraction (DF) are still poorly understood. We used a 6-year dataset of carbon flux at a warmtemperate mixed plantation site in North China to explore the impacts of DF on GPP and LUE. During 2011-2017, ecosystem apparent quantum yield (α) and photosynthesis at photosynthetically active radiation (PAR) of 1800 µmol m-2 s -1 (P1800) on cloudy days were 63% and 17% higher than on clear days, respectively. Under lower vapor pressure deficit (VPD) and air temperature (Ta) conditions, canopy photosynthesis was significantly higher on cloudy skies than on clear skies. On half-hourly scale, increased DF enhanced α and P1800. Daily GPP peaked at a median DF (=0.5), while daily LUE significantly increased with DF (p<0.01). Both GPP and LUE were mainly controlled directly by DF and PAR. DF had an indirect effect on LUE and GPP mainly through PAR. At high DF levels (>0.5), the increase in LUE did not make GPP enhancement. The direct effect of DF on GPP and LUE under lower Ta and VPD was more sensitive than under higher Ta and VPD. When DF was incorporated into the MichaelisMenten model, it performed well in the GPP estimation, and the determination coefficient increased by 32.61% and the root mean square error decreased by 25.74%. These findings highlight the importance of incorporating DF into carbon sequestration estimation in North China. [ABSTRACT FROM AUTHOR]

Lighting strategies for morphological and physiological characteristics of horticultural crops often focus on the proper daily light integral (DLI); however, a suitable combination of photosynthetic photon flux density (PPFD) and photoperiod at the same DLI is conducive to optimize the light environment management in vegetable seedling production. In the present study, cucumber seedlings (Cucumis sativus L. cv. Tianjiao No. 5) were grown for 21 days under six different combinations of PPFD and photoperiod at a constant DLI of 11.5 mol⋅m−2⋅d−1, corresponding to a photoperiod of 7, 10, 13, 16, 19, and 22 h⋅d−1 provided by white light-emitting diodes (LEDs) under a controlled environment. Results showed that plant height, hypocotyl length, and specific leaf area of cucumber seedlings decreased quadratically with increasing photoperiod, and the opposite trend was observed in seedling quality index of cucumber seedlings. In general, pigment content and fresh and dry weight of cucumber seedlings increased as photoperiod increased from 7 to 16 h⋅d−1, and no significant differences were found in fresh and dry weight of shoot and root as photoperiod increased from 16 to 22 h⋅d−1. Sucrose and starch content of cucumber leaves increased by 50.6% and 32.3%, respectively, as photoperiod extended from 7 to 16 h⋅d−1. A longer photoperiod also led to higher cellulose content of cucumber seedlings, thus improving the mechanical strength of cucumber seedlings for transplanting. CsCesA1 relative expression level showed a trend similar to cellulose content. We propose that CsCesA1 is the key gene in the response to cellulose biosynthesis in cucumber seedlings grown under different combinations of PPFD and photoperiod. In summary, prolonging the photoperiod and lowering PPFD at the same DLI increased the quality of cucumber seedlings. An adaptive lighting strategy could be applied to increase seedling quality associated with the reduction of capital cost in cucumber seedling production.

• Intercropping intercepted more light than sole peanut but less than sole maize.• Maize light use efficiency (LUE) increased with plant density in the intercropping.• Intercropping did not affect LUE of maize but increased peanut LUE.Intercropping increases crop yields by optimizing light interception and/or use efficiency. Although intercropping combinations and metrics have been reported, the effects of plant density on light use are not well documented. Here, we examined the light interception and use efficiency in maize-peanut intercropping with different maize plant densities in two row configurations in semiarid dryland agriculture over a two-year period. The field experiment comprised four cropping systems, i.e. monocropped maize, monocropped peanut, maize-peanut intercropping with two rows of maize and four rows of peanut, intercropping with four rows of maize and four rows of peanut, and three maize plant densities (3.0, 4.5 and 6.0 plants m−1 row) in both monocropped and intercropping maize. The mean total light interception in intercropping across years and densities was 779 MJ·m−2, 5.5% higher than in monocropped peanut (737 MJ·m−2) and 7.6% lower than in monocropped maize (843 MJ·m−2). Increasing maize density increased light interception in monocropped maize but did not affect the total light interception in the intercrops. Across years the LUE of maize was 2.9 g·MJ−1 and was not affected by cropping system but increased with maize plant density. The LUE of peanut was enhanced in intercropping, especially in a wetter year. The yield advantage of maize-peanut intercropping resulted mainly from the LUE of peanut. These results will help to optimize agronomic management and system design and provide evidence for system level light use efficiency in intercropping.

Diffuse radiation (If) is one of important variables determining photosynthetic rate and carbon uptake of forest ecosystems. However, the responses of gross primary productivity (GPP) and light use efficiency (LUE) to diffuse fraction (DF) are still poorly understood. We used a 6-year dataset of carbon flux at a warm-temperate mixed plantation site in North China to explore the impacts of DF on GPP and LUE. During 2011-2017, ecosystem apparent quantum yield (α) and photosynthesis at photosynthetically active radiation (PAR) of 1800 µmol m-2 s-1 (P1800) on cloudy days were 63% and 17% higher than on clear days, respectively. Under lower vapor pressure deficit (VPD) and air temperature (Ta) conditions, canopy photosynthesis was significantly higher on cloudy skies than on clear skies. On half-hourly scale, increased DF enhanced α and P1800. Daily GPP peaked at a median DF (=0.5), while daily LUE significantly increased with DF (p0.5), the increase in LUE did not make GPP enhancement. The direct effect of DF on GPP and LUE under lower Ta and VPD was more sensitive than under higher Ta and VPD. When DF was incorporated into the Michaelis-Menten model, it performed well in the GPP estimation, and the determination coefficient increased by 32.61% and the root mean square error decreased by 25.74%. These findings highlight the importance of incorporating DF into carbon sequestration estimation in North China.

Low technological knowledge in production chains, global climate change, and misinformation are concrete threats to food security. In addition, these combined threats also trigger ecological instability in megadiverse areas of the world, especially in some cacao-producing countries in South America, where this crop plays an important socioeconomic role, even being used to replace illicit crops. Accordingly, the use of agroforestry systems approaches has emerged as a good alternative to maintain productivity, add high-value commodities to producers, and provide important ecosystem services for sustainable agriculture. However, limitations associated with the competition for resources between the species composing the system, and the higher incidence of some diseases, have led many producers to abandon this strategy, opting for monoculture. In this review, we seek to gather the main information available in the literature, aiming to answer the question: what is the real scientific evidence that supports the benefits and harms of adopting agroforestry systems in cacao production? We seek to make critical scrutiny of the possible negative effects of certain associations of the agroforestry system with biotic and abiotic stress in cacao. Here, we review the possible competition for light and nutrients and discuss the main characteristics to be sought in cacao genotypes to optimize these inter-specific relationships. In addition, we review the research advances that show the behavior of the main cacao diseases (Witch's broom disease, frosty pod rot, black pod rot) in models of agroforestry systems contrasted with monoculture, as well as the optimization of agronomic practices to reduce some of these stresses. This compendium, therefore, sheds light on a major gap in establishing truly sustainable agriculture, which has been treated much more from the perspective of negative stigma than from the real technological advantages that can be combined to the benefit of a balanced ecosystem with generating income for farmers. [ABSTRACT FROM AUTHOR]

The Photochemical Reflectance Index (PRI) has great potential for estimating Light Use Efficiency (LUE). Mixed canopy structure under different lighting and observation geometries can affect the remote sensing observations of the PRI, leading to some errors in estimating vegetation photosynthesis. Multi-angle observation is an effective method for resolving differences in observation geometry. Fitting multi-angle observations to a Bidirectional Reflectance Distribution Function (BRDF) can normalize PRI to a common solar-observation target position, resulting in a significant increase in the correlation between canopy PRI and LUE, and has been well used in forest ecosystems. However, studies on the standardization of multi-angle PRI by BRDF models on crop canopies are still not well developed. To investigate the ability of the improved PRI by BRDF model to estimate the LUE of rice canopies, this paper used multi-angle rice canopy reflection data and contemporaneous flux data from the National Meteorological Station in Shouxian, Anhui, a semi-empirical, kernel-driven BRDF model was used to standardize the multi-angle PRI for each half-hourly from 09:00 to 15:00 during the observation period. This paper explored the BRDF model simulated PRI values and the model parameter characteristics under different physiological and non-physiological conditions. The results showed that the BRDF model fitting was poorly at low Clearness Index (CI) and became better as the CI increased, with the best performance at CI = 0.9 (R² = 0.41). The parameters of the BRDF model are influenced by light conditions and vegetation status, where the isotropic weights (ki) correlated well with LUE for different CI ranges (linear regression coefficients R² > 0.3 for all CI ranges), with the best correlation at 0.6 ≤ CI < 0.7 (R² = 0.63); the daily variation of volume scattering weights (kv) showed a "U-shape" during the observation period, which was consistent with the daily variation of LUE. After correction by the BRDF model, the R² of the exponential regression between PRI and LUE increased from 0.46 (P<0.05) to 0.8 (P<0.01). Compared with the PRI from simple multi-angle remote sensing observations, the angular correction by the BRDF model improved the ability of PRI estimating LUE; this study also demonstrated the feasibility that multi-angle canopy spectral observations can use the BRDF model to improve vegetation indices tracking plant physiological activity. This study has reference value for processing multi-angle vegetation remote sensing observation data and for remote sensing estimation of physiological activities related to photosynthesis in regional vegetation. The BRDF model can be practiced in multi-angle satellite observations to achieve the monitoring of photosynthetic capacity in a large area of farming area. Subsequent experiments in different farming areas will be carried out to calibrate the wider band spectral observations available from satellite data to achieve a comprehensive understanding of the correlation between LUE variation and spectral reflectance in lutein and fluorescence-related absorption characteristics, and to provide some reference for the calibration of parameters in agricultural areas in the global productivity model. [ABSTRACT FROM AUTHOR]

Both light use efficiency (LUE) and water use efficiency (WUE) play essential roles in ecosystem production. The extent to which ecosystem production is affected by the coupling between LUE and WUE remains unclear. In this study, we used data from flux measurements and weather stations in the Heihe River Basin, China, along a strong climatic gradient to quantify the relationship between LUE and WUE. Variations of LUE explained up to 85% of the variations of WUE. The contribution of LUE to WUE increased with increasing water stress. Pearson's correlation coefficient between LUE and WUE increased from −0.12 to +0.63 with decreasing LUE. The coordination between LUE and WUE was essential to explaining the insensitive of WUE and GPP with increasing water stress. These results suggest that ecosystems enhance the coordination between light and water use when water stress is high. They enhance our understanding of the drought resilience of ecosystems and reduce uncertainties associated with the carbon cycle in drylands. [ABSTRACT FROM AUTHOR]

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We document the response of a 2 day wildfire smoke event on a moist temperate coniferous old‐growth forest in the western U.S. Wildfire smoke increased air temperature and suppressed relative humidity and total incoming radiation. Despite these conditions a ∼10% increase in ecosystem photosynthesis was observed. This was explained by a large increase (41%) in ecosystem‐scale stomatal conductance, inferred from measurements of carbonyl sulfide. Increased stomatal conductance contradicts expected stomatal closure at high vapor pressure deficit and was likely caused by an increase in diffuse light and thus shade leaf insolation. Higher ecosystem productivity and transpiration were linked to a greater drawdown of soil moisture. Ecosystem‐scale measurements across a diverse range of ecosystems are needed to better understand the canopy response to wildfire smoke, which is an increasingly common phenomenon across large parts of the world, including the forests of western North America. Plain Language Summary: Increases in wildfire intensity have been observed and projected for large parts of western North America, but the impact of smoke from these wildfires on carbon and water fluxes in different ecosystems is not well understood. In this study, we document the response of an old growth coniferous forest located in Pacific Northwestern U.S. to smoke from a nearby wildfire. During this event, the forest experienced warmer, drier and darker conditions. Using measurements of trace gases in the air we observe that the forest canopy increased photosynthesis and transpiration rates. This was due to an increase in scattering of light by smoke particles and facilitated by abundant soil moisture. Increased water‐use by trees also reduced the temperature of canopy leaves, potentially preventing them from damaging temperatures. We suggest continued measurements at the ecosystem scale to understand the response of diverse ecosystems to wildfire smoke, an increasingly common phenomenon for large parts of the world, including western North America. Key Points: Smoke from a nearby fire warmed and dried the air above an old‐growth forest and decreased incoming radiationSmoke led to higher canopy photosynthesis and transpiration rates, estimated from eddy covariance and carbonyl sulfide profile measurements, respectivelyThese increased fluxes are also facilitated by available deep soil moisture at the site [ABSTRACT FROM AUTHOR]

Carbon sinks in terrestrial ecosystems can be significantly increased by afforestation, which will slow global warming. However, it is still unclear how different plantations influence the carbon sink and how they respond to environmental factors, especially in drylands. In this study, eddy correlation method (EC) was used to measure carbon and water fluxes and environmental factors of two artificial forests (Larix principis-rupprechtii and Pinus tabulaeformis) in the dryland of Northwest China, and the responses of evapotranspiration (ET), net ecosystem exchange (NEE), gross primary productivity (GPP), and ecosystem respiration (RECO) to environmental factors were also assessed. Results showed that the L. principis-rupprechtii forest ecosystem had higher water use efficiency (WUE), light use efficiency (LUE), GPP, and RECO than the P. tabulaeformis forest ecosystem. However, the proportion of net ecosystem production (NEP) to GPP in the P. tabulaeformis forest ecosystem (62.89%) was higher than that in the L. principis-rupprechtii forest ecosystem (47.49%), indicating that the P. tabulaeformis forest ecosystem had the higher carbon sequestration efficiency. In addition, the CO2 and H2O fluxes in the L. principis-rupprechtii forest ecosystem were more sensitive to environmental factors, compared with the P. tabulaeformis forest ecosystem. Further, the RECO of the L. principis-rupprechtii forest ecosystem was more sensitive to temperature changes, which implies that the L. principis-rupprechtii forest ecosystem will release more CO2 than the P. tabulaeformis forest ecosystem with a warming climate. Therefore, the P. tabulaeformis forest ecosystem may have better carbon sequestration potential. These results are important for understanding the effects of climate change on the CO2 and H2O cycles in coniferous plantation ecosystems in drylands. [ABSTRACT FROM AUTHOR]

IntroductionIn recent decades, agricultural production systems have already explored many methods to increase the crops yield. Most of these methods involved increasing the efficiency of resources utilization such as nutrients, solar radiation, and atmospheric CO2. Crop growth and yield are considered as a function of photosynthetically active radiation (PAR) that is intercepted by plant as well its utilization efficiency to produce dry matter. Net primary production has often been found to be linearly related to the photosynthetically active radiation (PAR) intercepted by crops. The slope of this relationship is light use efficiency (LUE). Several authors have found close correlation between crop growth and yield with the radiation absorption and the LUE. Although, it was previously believed that the LUE is constant during the crop growing season and it is controlled more genetically, but environmental factors and management practices such as change in the sowing date, plant density, cultivars, climate, soil fertility, especially soil available nitrogen due to its specific role in photosynthesis, affect greatly the LUE. Therefore, the objectives of the present study were to evaluate light absorption and use efficiency in different sowing date for chickpea cultivars in Kermanshah regionlight absorption and use efficiency in different sowing date for chickpea cultivars in Kermanshah region climatic. Material and MethodsA split plot experiment was conducted based on Randomized Complete Block Design during 2016-2017 at the research farm of the faculty of agriculture and natural resources of Razi University, Kermanshah, Iran (34°, 19´ N, 47°, 50´ E and altitude 1317 m). The average annual rainfall was 455 mm, and the long-term average of maximum and minimum air temperature was 22.6 and 5.9°C, respectively. Main plots had three sowing dates (February 29, Match 10 and April 6) and sub plots were composed of chickpea cultivars (Bivanij, Adel, Arman and ILC482). The measured indexes were leaf area index (LAI), radiation absorption, total dry matter (TDM), light use efficiency (LUE) and grain yield of chickpea. The LUE was calculated based on g MJ-1 through the slope of linear regression between total dry matter accumulation (g m-2) and cumulative absorbed photosynthetically active radiation. Chickpea grain yield was measured at the physiological maturity stage. Results and DiscussionThe results showed that the maximum LAI of different chickpea cultivars decreased with the delay in sowing date. The greatest LAI (3.8) was related to Arman cultivar with the sowing date of March 1 and the lowest LAI (1.9) was related to ILC482 cultivar with the sowing date of April 6. The light absorption had the similar LAI trend that with the delay in sowing date decreased about 51%. The highest (15.9 MJ m-2) and the lowest (13.4 MJ m-2) light absorption were observed for Arman cultivar with the sowing date of March 1 and ILC482 cultivar with the sowing date of April 6, respectively. Combined analysis of variance of the results indicated that the effects of sowing date and cultivars were significant on TDM and grain yield, but the interactions of sowing date and cultivars were not significant for TDM and grain yield. The results indicated that the delay in sowing date led to reduce in the grain yield (45%) and TDM (33.5%). The highest (158 g m-2) and the lowest (102 g m-2) grain yield were related to Bivanij and Arman cultivars, respectively. The grain yield of Bivanij cultivar was higher (35%) compared to other cultivars. The highest LUE (1.6 g MJ-1) was observed for Adel cultivar with the sowing date of March 1 and the lowest LUE (0.7 g MJ-1) was related to Arman cultivar with the sowing date of April 6. Late sowing dates of March 11 and April 6 reduced LUE compared to early sowing date of February 29 about 4.2% and 2.7% in Bivanij cultivar, 9.4% and 27.3% in Adel cultivar, 43.4% and 40.3% in Arman cultivar and 19.1% and 16.8% in ILC482 cultivar, respectively. ConclusionIn general, the results of this study show that the delay in sowing date, which is unavoidable under some climatic conditions by the farmer, lead to reduce in measured traits such as grain yield and LUE of chickpea. However, it seems that late sowing could help with the selection of suitable chickpea cultivars that could offset the yield loss due to unsuitable environmental condition such as drought stress by end of the growing season.

Low technological knowledge in production chains, global climate change, and misinformation are concrete threats to food security. In addition, these combined threats also trigger ecological instability in megadiverse areas of the world, especially in some cacao-producing countries in South America, where this crop plays an important socio-economic role, even being used to replace illicit crops. Accordingly, the use of agroforestry systems approaches has emerged as a good alternative to maintain productivity, add high-value commodities to producers, and provide important ecosystem services for sustainable agriculture. However, limitations associated with the competition for resources between the species composing the system, and the higher incidence of some diseases, have led many producers to abandon this strategy, opting for monoculture. In this review, we seek to gather the main information available in the literature, aiming to answer the question: what is the real scientific evidence that supports the benefits and harms of adopting agroforestry systems in cacao production? We seek to make critical scrutiny of the possible negative effects of certain associations of the agroforestry system with biotic and abiotic stress in cacao. Here, we review the possible competition for light and nutrients and discuss the main characteristics to be sought in cacao genotypes to optimize these inter-specific relationships. In addition, we review the research advances that show the behavior of the main cacao diseases (Witch’s broom disease, frosty pod rot, black pod rot) in models of agroforestry systems contrasted with monoculture, as well as the optimization of agronomic practices to reduce some of these stresses. This compendium, therefore, sheds light on a major gap in establishing truly sustainable agriculture, which has been treated much more from the perspective of negative stigma than from the real technological advantages that can be combined to the benefit of a balanced ecosystem with generating income for farmers.

Vegetation gross primary production (GPP) in terrestrial ecosystems is a key element of the carbon cycle, and its estimation highly determines the accuracy of carbon budget assessments. Currently, several global datasets of vegetation production are available at coarse or moderate spatial resolutions, but globally they still have large uncertainties, which hindered the application of GPP, especially in strongly heterogeneous agriculture ecosystems and mountainous areas. Here, we used the Markov chain Monte Carlo (MCMC) approach with the footprints of FLUXNET data to optimize the parameters of the high resolution of Global LAnd Surface Satellite (Hi-GLASS) GPP algorithm (i.e., the revised EC-LUE model) using 30 m spatial resolution Landsat data as driving data. Then, we generated a new set of algorithm parameters for high resolution GPP estimates. We used the optimized parameters with integrating footprint to calculate Hi-GLASS GPP based on Landsat data and our results revealed that on average, Hi-GLASS GPP explained 76% of variance in tower GPP at the total of 78 sites across ten vegetation types. Moreover, compared with previous 500 m GPP product such as GLASS GPP and MODerate Resolution Imaging Spectroradiometer (MODIS) GPP, our optimized Hi-GLASS algorithm using Landsat data had large superiority in simulating GPP for wetlands, savannas, shrubland and C3, C4 cropland ecosystems, and had a slightly improvement for deciduous broadleaf forests and evergreen broadleaf forest ecosystem. Our study is an effort to optimize and quantify parameter uncertainty of Hi-GLASS algorithm using high spatial resolution (30 m) Landsat data and improve the high resolution GPP estimation for better understanding global ecosystem carbon dynamics and carbon-climate feedbacks.

Abstract Perennial crops have been the focus of bioenergy research and development for their sustainability benefits associated with high soil carbon (C) and reduced nitrogen (N) requirements. However, perennial crops mature over several years and their sustainability benefits can be negated through land reversion. A photoperiod‐sensitive energy sorghum (Sorghum bicolor) may provide an annual crop alternative more ecologically sustainable than maize (Zea mays) that can more easily integrate into crop rotations than perennials, such as miscanthus (Miscanthus × giganteus). This study presents an ecosystem‐scale comparison of C, N, water and energy fluxes from energy sorghum, maize and miscanthus during a typical growing season in the Midwest United States. Gross primary productivity (GPP) was highest for maize during the peak growing season at 21.83 g C m−2 day−1, followed by energy sorghum (17.04 g C m−2 day−1) and miscanthus (15.57 g C m−2 day−1). Maize also had the highest peak growing season evapotranspiration at 5.39 mm day−1, with energy sorghum and miscanthus at 3.81 and 3.61 mm day−1, respectively. Energy sorghum was the most efficient water user (WUE), while maize and miscanthus were comparatively similar (3.04, 1.75 and 1.89 g C mm−1 H2O, respectively). Maize albedo was lower than energy sorghum and miscanthus (0.19, 0.26 and 0.24, respectively), but energy sorghum had a Bowen ratio closer to maize than miscanthus (0.12, 0.13 and 0.21, respectively). Nitrous oxide (N2O) flux was higher from maize and energy sorghum (8.86 and 12.04 kg N ha−1, respectively) compared with miscanthus (0.51 kg N ha−1), indicative of their different agronomic management. These results are an important first look at how energy sorghum compares to maize and miscanthus grown in the Midwest United States. This quantitative assessment is a critical component for calibrating biogeochemical and ecological models used to forecast bioenergy crop growth, productivity and sustainability.

Estimating gross primary productivity (GPP) is important for simulating the subsequent carbon cycle elements and assessing the capacity of terrestrial ecosystems to support the sustainable development of human society. Light use efficiency (LUE) models were widely used to estimate GPP due to their concise model structures. However, quantifying LUEmax (maximum light use efficiency) and representing the responses of photosynthesis to environmental factors are still subject to large uncertainties, which lead to substantial errors in GPP simulations. In this study, we developed a hybrid model based on machine learning and a LUE model for GPP estimates. This hybrid model was built by targeting LUE with a machine learning approach, namely multi-layer perceptron (MLP), and then, estimating GPP within a LUE model framework with the MLP-based LUE and other required inputs. We trained the hybrid LUE (H-LUE) model and then, compared it against two conventional LUE models, the vegetation photosynthesis model (VPM) and vegetation photosynthesis and respiration model (VPRM), regarding GPP estimation, using tower-based daily-scale observations from 180 flux sites that cover nine different plant function types (PFTs). The results revealed better performance (R2 = 0.86 and RMSE = 1.79 gC m−2 d−1 on the test dataset) of the H-LUE model compared to the VPM and VPRM. Evaluations of the three models under four different extreme conditions consistently revealed better performance of the H-LUE model, indicating greater adaptability of the model to varied environments in the context of climate change. Furthermore, we also found that the H-LUE model can reasonably represent the responses of the LUE to meteorological variables. Our study revealed the reliable and robust performance of the developed hybrid LUE when simulating GPP across global biomes, providing references for developing better hybrid GPP models.

Supplemental artificial light in greenhouses is fundamental to achieving sustainable crop production with high yield and quality. This study's purpose was to investigate the efficacy of supplemental light (SL) sources on the vegetative and reproductive growth of cherry tomatoes. Four types of light sources were applied, including high-pressure sodium lamps (HPS), a narrow-spectrum LED light (NSL), and two specific full-spectrum LED lights (SFL1 and SFL2) with a shorter blue peak wavelength (436 nm) and/or green peak wavelength (526 nm). The control was the natural light condition. Shoot fresh and dry weight and leaf area in the SFL1 and SFL2 treatments were greater than those in the control. The HPS and NSL treatments also enhanced tomato growth, but they were less efficient compared to the SFL treatments. The SFL1 and SFL2 treatments showed higher fruit yields by 73.1% and 70.7%, respectively, than the control. The SL sources did not affect the effective photochemical quantum yield of photosystem II (Y (II)). However, they did trigger the increased electron transport rate (ETR) and non-photochemical quenching (NPQ). The SFL treatments enhanced tomato growth, fruit yield, and efficient use of light and energy, suggesting that the specific full spectrum based on the short-wavelength blue and/or green peak can be successfully applied for the cultivation of cherry tomato and other crops in greenhouses. [ABSTRACT FROM AUTHOR]

Copyright of Acta Prataculturae Sinica is the property of Acta Prataculturae Sinica Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Improving canopy photosynthetic light use efficiency and energy conversion efficiency (ε c ) is a major option to increase crop yield potential. However, so far, the diurnal and seasonal variations of canopy light use efficiency (LUE) and ε c are largely unknown due to the lack of an efficient method to estimate ε c in a high temporal resolution. Here we quantified the dynamic changes of crop canopy LUE and ε c during a day and a growing season with the canopy gas exchange method. A response curve of whole-plant carbon dioxide (CO2) flux to incident photosynthetically active radiation (PAR) was further used to calculate ε c and LUE at a high temporal resolution. Results show that the LUE of two wheat cultivars with different canopy architectures at five stages varies between 0.01 to about 0.05 mol CO2 mol–1 photon, with the LUE being higher under medium PAR. Throughout the growing season, the ε c varies from 0.5 to 3.7% (11–80% of the maximal ε c for C3 plants) with incident PAR identified as a major factor controlling variation of ε c . The estimated average ε c from tillering to grain filling stages was about 2.17%, i.e., 47.2% of the theoretical maximal. The estimated season-averaged radiation use efficiency (RUE) was 1.5–1.7 g MJ–1, which was similar to the estimated RUE based on biomass harvesting. The large variations of LUE and ε c imply a great opportunity to improve canopy photosynthesis for greater wheat biomass and yield potential. [ABSTRACT FROM AUTHOR]

Crop yield is dependent on crop biomass and harvest index. The increases in crop yield in the past benefit mainly from the increase in harvest index, the increase in biomass has been small. Light use efficiency is a bottleneck to further increase crop biomass and yield. Wheat (Triticum aestivum L.) is a widely cultivated cereal crop globally, providing energy to up to 20% of the world's population. It is necessary to reveal the intrinsic mechanism and extrinsic factors affecting the light use efficiency of wheat, which is important for improving the utilization efficiency of crop resources and productivity. Achieving high light efficient production of wheat under limited natural resources has become the focus of study at home and abroad. Here, the definition of light use efficiency, the main processes, the characteristics of light use efficiency in wheat were summarized from relevant references, showing a more significant potential to improve light use efficiency. The effects of external factors such as light, water, nutrient and tillage system on wheat light use efficiency were summarized. The results indicated that light use efficiency was regulated by internal factors such as photosynthesis at the individual plant scale, and by abiotic factors such as temperature, precipitation and tillage practices at the field scale. The current problems and the adaptation mechanism of wheat in the context of climate change were also analyzed, aiming to provide a theoretical reference for the practical research of the high light use efficiency of wheat. Future research on light use efficiency can use high-throughput phenotypic observation techniques combined with molecular markers to design ideotypes in the target environment, providing scientific evidence for crop breeding. [ABSTRACT FROM AUTHOR]

Background and Objective:Since improving the efficiency of environmental resources utilization in intercropping is one of the essential strategies for achieving sustainable agriculture, Therefore, in order to assess some ecophysiological properties of maize S.C 704 in additive intercropping with mungbean, an experiment was conducted. Materials and Methods: The experiment was based on randomized complete block design with six treatments and four replications in Dezful region during the summer of 2018. Experimental treatments consisted of different additive intercroppingof maize-mungbean intercropping (adding 10%, 20%, 30%, 40% and 50% of optimum density of mungbean to optimum maize density) and a pure stand of maize (control). Results: The results showed that the effect of different maize -mungbean additive intercropping treatments on leaf area index, leaf area duration, light absorption, crop growth rate, dry matter accumulation and light use efficiency was significant. But the relative growth rate was not significantly affected by the treatments. In this study, with increasing in mungbean density, the evaluated traits in all intercropping treatments were higher than that of pure maize. However, the additive intercropping treatment of maize+40% mungbean utilized higher leaf area index (5.28), leaf area duration (217 LAI-day), absorption of photosynthetically active radiation (18.12 MJ/m2), Crop growth rate (30.14 g/m2/day) and relative growth rate (0.0838 g/g/day) compared to the other treatments, resulting in the highest dry matter accumulation (1996.50 g/m2) and consequently the highest radiation use efficiency (2.91 g/mJ). Conclusion:In general, maize+40% mungbean treatment can be introduced as the best maize-mungbean additive intercropping system, regarding environmental resources consumption and dry matter production.

Improving canopy photosynthetic light use efficiency and energy conversion efficiency (εc) is a major option to increase crop yield potential. However, so far, the diurnal and seasonal variations of canopy light use efficiency (LUE) and εc are largely unknown due to the lack of an efficient method to estimate εc in a high temporal resolution. Here we quantified the dynamic changes of crop canopy LUE and εc during a day and a growing season with the canopy gas exchange method. A response curve of whole-plant carbon dioxide (CO2) flux to incident photosynthetically active radiation (PAR) was further used to calculate εc and LUE at a high temporal resolution. Results show that the LUE of two wheat cultivars with different canopy architectures at five stages varies between 0.01 to about 0.05 mol CO2 mol–1 photon, with the LUE being higher under medium PAR. Throughout the growing season, the εc varies from 0.5 to 3.7% (11–80% of the maximal εc for C3 plants) with incident PAR identified as a major factor controlling variation of εc. The estimated average εc from tillering to grain filling stages was about 2.17%, i.e., 47.2% of the theoretical maximal. The estimated season-averaged radiation use efficiency (RUE) was 1.5–1.7 g MJ–1, which was similar to the estimated RUE based on biomass harvesting. The large variations of LUE and εc imply a great opportunity to improve canopy photosynthesis for greater wheat biomass and yield potential.

Abstract Low natural daily light integrals (DLIs) are a major limiting factor for greenhouse production during darker months (e.g., October to February in Canada). Supplemental lighting (SL) is commonly used to maintain crop productivity and quality during these periods, particularly when the supply chain demands consistent production levels year-round. What remains to be determined are the optimum SL light intensities (LIs) for winter production of a myriad of different commodities. The present study investigated the growth and yield of sunflower (Helianthus annuus L., ‘Black oil’), kale (Brassica napus L., ‘Red Russian’), arugula (Eruca sativa L.), and mustard (Brassica juncea L., ‘Ruby Streaks’), grown as microgreens, in a greenhouse under SL light-emitting diode (LED) photosynthetic photon flux density (PPFD) levels ranging from 17.0 to 304 μmol·m−2·s−1 with a 16-hour photoperiod (i.e., supplemental DLIs from 1.0 to 17.5 mol·m−2·d−1). Crops were sown in a commercial greenhouse near Hamilton, ON, Canada (lat. 43°14′N, long. 80°07′W) on 1 Feb. 2018, and harvested after 8, 11, 12, and 12 days, resulting in average natural DLIs of 6.5, 5.9, 6.2, and 6.2 mol·m−2·d−1 for sunflower, kale, arugula, and mustard, respectively. Corresponding total light integrals (TLIs) ranged from 60 to 188 mol·m−2 for sunflower, 76 to 258 mol·m−2 for kale, 86 to 280 mol·m−2 for arugula, and 86 to 284 mol·m−2 for mustard. Fresh weight (i.e., marketable yield) increased asymptotically with increasing LI and leaf area increased linearly with increasing LI, in all genotypes. Hypocotyl length of mustard decreased and hypocotyl diameter of sunflower, arugula, and mustard increased with increasing LI. Dry weight, robust index, and relative chlorophyll content increased and specific leaf area decreased in kale, arugula, and mustard with increasing LI. Commercial microgreen greenhouse growers can use the light response models described herein to predict relevant production metrics according to the available (natural and supplemental) light levels to select the most appropriate SL LI to achieve the desired production goals as economically as possible.

It has been long established that the terrestrial vegetation in spring has stronger photosynthetic capability than in autumn. However, this study challenges this consensus by comparing photosynthetic capability of terrestrial vegetation between the spring and autumn seasons based on measurements of 100 in situ eddy covariance towers over global extratropical ecosystems. At the majority of these sites, photosynthetic capability, indicated by light use efficiency (LUE) and apparent quantum efficiency, is significantly higher in autumn than in spring, due to lower atmosphere vapor pressure deficit (VPD) at the same air temperature. Seasonal VPD differences also substantially explain the interannual variability of the differences in photosynthetic capability between spring and autumn. We further reveal that VPD in autumn is significantly lower than in spring over 74.14% of extratropical areas, based on a global climate dataset. In contrast, LUE derived from a data-driven vegetation production dataset is significantly higher in autumn in over 61.02% of extratropical vegetated areas. Six Earth system models consistently projected continuous larger VPD values in spring compared with autumn, which implies that the impacts on vegetation growth will long exist and should be adequately considered when assessing the seasonal responses of terrestrial ecosystems to future climate conditions. Public summary: • Autumn VPD is lower than spring VPD at the same air temperature over majority of the extratropical vegetated land • Photosynthetic capability is significantly higher in autumn than in spring due to lower VPD • Earth System Models projected continuous larger VPD values in spring as against autumn

Eddy-covariance (EC) measurements are widely used to optimize the terrestrial vegetation gross primary productivity (GPP) model because they provide standardized and high-quality flux data within their footprint areas. However, the extent of flux data taken from a tower site within the EC footprint, represented by the satellite-based grid cell between Landsat and Moderate Resolution Imaging Spectroradiometer (MODIS), and the performance of the model derived from the Normalized Difference Vegetation Index (NDVI) within the EC footprint at different spatial resolutions (e.g., Landsat and MODIS) remain unclear. Here, we first calculated the Landsat-footprint NDVI and MODIS-footprint NDVI and assessed their spatial representativeness at 78 FLUXNET sites at 30 m and 500 m scale, respectively. We then optimized the parameters of the revised Eddy Covariance-Light Use Efficiency (EC-LUE) model using NDVI within the EC-tower footprints that were calculated from the Landsat and MODIS sensor. Finally, we evaluated the performance of the optimized model at 30 m and 500 m scale. Our results showed that matching Landsat data with the flux tower footprint was able to improve the performance of the revised EC-LUE model by 18% for savannas, 14% for croplands, 9% for wetlands. The outperformance of the Landsat-footprint NDVI in driving model relied on the spatial heterogeneity of the flux sites. Our study assessed the advantages of remote sensing data with high spatial resolution in simulating GPP, especially for areas with high heterogeneity of landscapes. This could facilitate a more accurate estimation of global ecosystem carbon sink and a better understanding of plant productivity and carbon climate feedbacks.

Insufficient light in autumn–winter may prolong the production periods and reduce the quality of plug seedlings grown in greenhouses. Additionally, there is no optimal protocol for supplementary light strategies when providing the same amount of light for plug seedling production. This study was conducted to determine the influences of combinations of supplementary light intensity and light duration with the same daily light integral (DLI) on the morphological and physiological properties of cucumber seedlings (Cucumis sativus L. cv. Tianjiao No. 5) grown in a greenhouse. A supplementary light with the same DLI of 6.0 mol m−2 d −1 was applied with the light duration set to 6, 8, 10, or 12 h d−1 provided by light-emitting diodes (LEDs), and cucumber seedlings grown with sunlight only were set as the control. The results indicated that increasing DLI using supplementary light promoted the growth and development of cucumber seedlings over those grown without supplementary light; however, opposite trends were observed in the superoxide dismutase (SOD) and catalase (CAT) activities. Under equal DLI, increasing the supplementary light duration from 6 to 10 h d−1 increased the root surface area (66.8%), shoot dry weight (24.0%), seedling quality index (237.0%), root activity (60.0%), and stem firmness (27.2%) of the cucumber seedlings. The specific leaf area of the cucumber seedlings decreased quadratically with an increase in supplementary light duration, and an opposite trend was exhibited for the stem diameter of the cucumber seedlings. In summary, increased DLI or longer light duration combined with lower light intensity with equal DLI provided by supplementary light in insufficient sunlight seasons improved the quality of the cucumber seedlings through the modification of the root architecture and stem firmness, increasing the mechanical strength of the cucumber seedlings for transplanting. [ABSTRACT FROM AUTHOR]

Waterlogging is a severe stress that constrains crop production. We studied ecophysiological traits related to waterlogging tolerance in wheat, barley oilseed rape and field pea. Outdoor experiments using canopies of wheat (Triticum aestivum L.), barley (Hordeum vulgare L.), oilseed rape (Brassica napus L.) and field pea (Pisum sativum L.) were subjected to a 14‐day‐waterlogging at early (vegetative) or late (reproductive) stages and a non‐waterlogged treatment (as control). Leaf area index (LAI), radiation interception, radiation use efficiency (RUE) and aerial dry matter were monitored along the life‐cycle; quantifying yield and its components at maturity. Wheat was able to withstand waterlogging, with similar yields than controls. Barley showed no differences in yield at early stage, but late‐waterlogging resulted in 64%–66% lower yield owing to fewer spikes/m2 and poor recovery of radiation interception and RUE. Oilseed rape showed yield penalization due to waterlogging, but responses differed from 17%–30% to 42%–69% for early and late stages, respectively; due to the limited ability to restore radiation interception and RUE in late stage; and the additional losses in seed number and weight. Field pea was unable to restore LAI, radiation interception, or RUE and suffered substantial yield reductions (85%–100%). Wheat could be cultivated in areas prone to transient waterlogging (i.e., early or late stages) of up to 2 weeks; barley and rapeseed are recommended only with waterlogging occurring in early stages and field pea is not suitable for areas facing waterlogging. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Remote Sensing is the property of Editorial Office of Journal of Remote Sensing & Science Publishing Co. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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• The absorbed photosynthetically active radiation (APAR) is important in P model. • The intrinsic quantum yield efficiency (φ 0) is vital in P model. • Modifying the calculation of APAR and φ 0 is effective in developing P model. • An improved P model (IP model) was further generated. • The IP model provided a more accurate and reasonable estimate of terrestrial GPP. Terrestrial gross primary productivity (GPP) plays a crucial role in global carbon cycle and budget. A range of light use efficiency (LUE) models have been developed to estimate GPP at different spatial scales. However, large uncertainties still remain in GPP output from such models, mainly owing to the difficulty in the proper determination of maximum light use efficiency (LUE max). The recently developed P model directly quantifies actual LUE based on environmental and physiological factors, reducing the uncertainty in GPP estimation caused by the ambiguous LUE max. However, the existing P models still suffer from a potential underestimation in global validation, which might be related to the calculation of absorbed photosynthetically active radiation (APAR) and intrinsic quantum yield efficiency (φ 0) in the P model. In this study, we improved the P model by differentiating sunlit and shaded leaves for APAR calculation and by considering the spatial variability of the optimal temperature for φ 0 (T opt_phi0). The roles of modified APAR and φ 0 calculations in reducing the uncertainty of simulated GPP were assessed through model simulation experiments with monthly tower-based GPP from 120 flux sites globally distributed as the benchmark. The validation indicates that simultaneous improvements on APAR and φ 0 algorithms are able to better the performance of the P model. Monthly GPP simulated with this improved P model (i.e., IP model) is in good agreement with tower-based values, with a linear R2, root mean squared error, mean error, mean absolute error, and DISO of 0.76, 1.88 g C m −2 d −1, -0.14 g C m −2 d −1, 1.77 g C m −2 d −1 and 0.60. The total global terrestrial GPP output from the IP model (IPGPP) averaged 134.3 Pg C yr−1 during 1981—2021, in the upper range of existing GPP products. [ABSTRACT FROM AUTHOR]

The spectral properties of plant leaves relate to the state of their photosynthetic apparatus and the surrounding environment. An example is the well known photosynthetic downregulation, active on the time scale from minutes to hours, caused by reversible changes in the xanthophyll cycle pigments. These changes affect leaf spectral absorption and are frequently quantified using the photochemical reflectance index (PRI). This index can be used to remotely monitor the photosynthetic status of vegetation, and allows for a global satellite-based measurement of photosynthesis. Such earth observation satellites in near-polar orbits usually cover the same geographical location at the same local solar time at regular intervals. To facilitate the interpretation of these instantaneous remote PRI measurements and upscale them temporally, we measured the daily course of leaf PRI in two evergreen biomes—a European boreal forest and an Amazon rainforest. The daily course of PRI was different for the two locations: At the Amazonian forest, the PRI of Manilkara elata leaves was correlated with the average photosynthetic photon flux density (PPFD) ($R^{2}=0.59$, $p< 0.01$) of the 40 minutes preceding the leaf measurement. In the boreal location, the variations in Pinus sylvestris needle PRI were only weakly ($R^{2}=0.27$, $p< 0.05$) correlated with mean PPFD of the preceding two hours; for Betula pendula, the correlation was insignificant ($p>0.5)$ regardless of the averaging period. The measured daily PRI curves were specific to species and/or environmental conditions. Hence, for a proper interpretation of satellite-measured instantaneous photosynthesis, the scaling of PRI measurements should be supported with information on its correlation with PPFD.

Carbon sinks in terrestrial ecosystems can be significantly increased by afforestation, which will slow global warming. However, it is still unclear how different plantations influence the carbon sink and how they respond to environmental factors, especially in drylands. In this study, eddy correlation method (EC) was used to measure carbon and water fluxes and environmental factors of two artificial forests (Larix principis-rupprechtii and Pinus tabulaeformis) in the dryland of Northwest China, and the responses of evapotranspiration (ET), net ecosystem exchange (NEE), gross primary productivity (GPP), and ecosystem respiration (RECO) to environmental factors were also assessed. Results showed that the L. principis-rupprechtii forest ecosystem had higher water use efficiency (WUE), light use efficiency (LUE), GPP, and RECO than the P. tabulaeformis forest ecosystem. However, the proportion of net ecosystem production (NEP) to GPP in the P. tabulaeformis forest ecosystem (62.89%) was higher than that in the L. principis-rupprechtii forest ecosystem (47.49%), indicating that the P. tabulaeformis forest ecosystem had the higher carbon sequestration efficiency. In addition, the CO2 and H2O fluxes in the L. principis-rupprechtii forest ecosystem were more sensitive to environmental factors, compared with the P. tabulaeformis forest ecosystem. Further, the RECO of the L. principis-rupprechtii forest ecosystem was more sensitive to temperature changes, which implies that the L. principis-rupprechtii forest ecosystem will release more CO2 than the P. tabulaeformis forest ecosystem with a warming climate. Therefore, the P. tabulaeformis forest ecosystem may have better carbon sequestration potential. These results are important for understanding the effects of climate change on the CO2 and H2O cycles in coniferous plantation ecosystems in drylands.

Vegetation gross primary production (GPP) is an important variable for the carbon cycle on the Qinghai-Tibetan Plateau (QTP). Based on the measurements from 12 eddy covariance flux sites, we validated a light use efficiency model (i.e. EC-LUE) to evaluate the spatial-temporal patterns of GPP and the effect of environmental variables on QTP. In general, EC-LUE model performed well in predicting GPP at different time scale over QTP. Annual GPP over the entire QTP ranged from 575 to 703 Tg C, and showed a significantly increasing trend from 1982 to 2013. However, there were large spatial heterogeneities in long-term trends of GPP. Throughout the entire QTP, air temperature increase had a greater influence than solar radiation and precipitation (PREC) changes on productivity. Moreover, our results highlight the large uncertainties of previous GPP estimates due to insufficient parameterization and validations. When compared with GPP estimates of the EC-LUE model, most Coupled Model Intercomparison Project (CMIP5) GPP products overestimate the magnitude and increasing trends of regional GPP, which potentially impact the feedback of ecosystems to regional climate changes.

For decisions on supplemental lighting a quantitative knowledge of the plants' responses to light under varying conditions is fundamental. In this study, we developed light dose-response curves of growth and morphological traits for Ocimum basilicum L. and examined the effects of light color (blue, red, and white plus far-red) and natural environment (season) on these curves. Four greenhouse experiments were conducted throughout the year to determine the efficiencies of the light regimes on growth and their effects on plant morphology. A special aspect was the photosynthetic efficiency of far-red light. Linear and monomolecular relationships were found for the relationships between plant traits and supplemental light dose. Traits related to biomass productivity increased linearly with light dose whereas some morphological characters showed a saturation behavior. Red light and white plus far-red light were more efficient in plant dry weight production than blue light, and the plants adapted differently to the light qualities: higher biomass under red light was related to a plant architecture more favorable for light capture, i.e., taller plants and bigger leaves. White plus far-red light, on the other hand, increased leaf mass per area (LMA) and light use efficiency (LUE). Blue light resulted in lowest plant light interception and LUE. Considering photosynthetic effects of near-infrared light (PPFD800, 400–800 nm) instead of photosynthetic photon flux density (PPFD700, 400–700 nm) led to strongly reduced efficiencies. Traits related to photosynthesis such as dry weight, LMA and LUE were particularly affected by PPFD800. There were no interactions between the efficiencies of the different light colors and the seasons. Efficiencies of all light regimes were significantly lower during summer compared to spring and winter. Higher dry weight production during summer compared to winter and spring were a consequence of increased light interception rather than changes in LUE. The observed differences in seasonal efficiencies were directly linked to the amount of natural light present as indicated by changes in the ratio of supplemental to natural light.

For decisions on supplemental lighting a quantitative knowledge of the plants' responses to light under varying conditions is fundamental. In this study, we developed light dose-response curves of growth and morphological traits for Ocimum basilicum L. and examined the effects of light color (blue, red, and white plus far-red) and natural environment (season) on these curves. Four greenhouse experiments were conducted throughout the year to determine the efficiencies of the light regimes on growth and their effects on plant morphology. A special aspect was the photosynthetic efficiency of far-red light. Linear and monomolecular relationships were found for the relationships between plant traits and supplemental light dose. Traits related to biomass productivity increased linearly with light dose whereas some morphological characters showed a saturation behavior. Red light and white plus far-red light were more efficient in plant dry weight production than blue light, and the plants adapted differently to the light qualities: higher biomass under red light was related to a plant architecture more favorable for light capture, i.e., taller plants and bigger leaves. White plus far-red light, on the other hand, increased leaf mass per area (LMA) and light use efficiency (LUE). Blue light resulted in lowest plant light interception and LUE. Considering photosynthetic effects of near-infrared light (PPFD800, 400–800 nm) instead of photosynthetic photon flux density (PPFD700, 400–700 nm) led to strongly reduced efficiencies. Traits related to photosynthesis such as dry weight, LMA and LUE were particularly affected by PPFD800. There were no interactions between the efficiencies of the different light colors and the seasons. Efficiencies of all light regimes were significantly lower during summer compared to spring and winter. Higher dry weight production during summer compared to winter and spring were a consequence of increased light interception rather than changes in LUE. The observed differences in seasonal efficiencies were directly linked to the amount of natural light present as indicated by changes in the ratio of supplemental to natural light. [ABSTRACT FROM AUTHOR]

Many studies have reported intraspecific variations in leaf functional traits, but their contribution to plant performance and ecosystem function are poorly understood. We studied altitudinal gradients of intraspecific variations in leaf traits, productivity and resource use efficiency in the dominant species of subalpine evergreen coniferous and deciduous broad‐leaved forests in Japan.We addressed three hypotheses, which are exclusive to each other. (1) Leaf traits vary along the leaf economics spectrum (LES). Plants that grow at lower and higher altitudes have fast‐ and slow‐return strategies, respectively, which improve productivity or resource use efficiency in the respective habitat. (2) Leaf trait variations are not consistent with the LES, but they contribute to improving productivity or resource use efficiency in the respective habitat. (3) Leaf trait variations do not contribute to improving productivity or resource use efficiency at higher altitudes.On the studied mountain range, Fagus crenata, a deciduous broad‐leaved tree, and Abies mariesii, an evergreen conifer, are the dominant species at lower and higher altitudes respectively. In F. crenata, leaf mass per area (LMA) and nitrogen concentrations were higher at higher altitudes. The net assimilation rate and light use efficiency during the growing season were greater at higher altitudes, which compensated for the shorter growing season in terms of annual productivity. In A. mariesii, the LMA was lower and the leaf life span was unchanged at higher altitudes. Productivity and resource use efficiency decreased with altitude.Synthesis. We conclude that F. crenata improves its productivity and resource use efficiency at higher altitudes by altering its leaf functional traits (Hypothesis 2), whereas alterations to leaf traits in A. mariesii are not associated with any improvement at higher altitudes (Hypothesis 3), which may result from the negative impact of environmental stress. Hence, the ecological significance of altitudinal variations in leaf traits depends on species and environment. [ABSTRACT FROM AUTHOR]