Chlorophyll Density Research Articles

Comparison of linear and nonlinear modeling approaches to develop an abundance index based on voyage and market data for a data-limited fishery

IntroductionWorldwide coastal fish resources face severe threats from fisheries overexploitation. However, the evaluation of abundance trends in most coastal fisheries is constrained by limited data. This study took blackmouth croaker (Atrobucca nibe), a stock depleted by coastal trawl fishery in southwestern Taiwan, as an example to showcase the development of a relative abundance index from data-limited fishery (only landing data were available).MethodsThis study employed unique data sourcing from voyage data recorders (VDRs) to estimate fishing effort (in combination with landing data to estimate the catch per unit effort, CPUE) that demonstrated the potential application in global data-limited fisheries and assessed alternative approaches for predictors of fishery-targeting practices to condition effort for producing more accurate metrics of relative abundance. The nominal CPUE was standardized using three statistical models: generalized linear model, generalized additive model (GAM), and vector-autoregressive spatiotemporal models (VASTs) with two treatments of each of the four effects: environmental (sea temperature, salinity, density of mixing layer, seafloor temperature, and chlorophyll), vessel, spatial, and targeting effects. A total of 15 models were designed and compared for these effects, and their explanatory power (EP) was evaluated using cross-validation R2 and other metrics.Results and discussionResults indicated that the targeting effect exerted the most significant influence on standardization and was suggested to be addressed through the principal component analysis (PCA) approach. Both vessel and spatial effects demonstrated considerable influence, whereas the environmental effect exhibited a limited impact, possibly due to the small fishing area in this study. Regarding models’ EP, given the nonlinear nature of the PCA algorithm and environmental data, the study highlighted the superiority of the GAM over linear-based models. However, incorporating nonlinear features in VAST (M15) makes it the most effective model in terms of predictive power in this study. Concerning the stock status, despite variations in relative CPUE trends among major models, a general declining trend since 2015 signals the potential decline of the blackmouth stock and urges fishery managers to consider further design of management measures.

Analysis of Spectral Characteristics of Cotton Leaves at Bud Stage under Different Nitrogen Application Rates

Soil salinity affects nutrient uptake by cotton. The cotton bud stage is a very important period in the process of cotton planting and directly affects the yield of cotton. The nutritional status of the bud stage directly affects the reflectance spectra of cotton canopy leaves. Therefore, it is of great significance to nondestructively monitor the nutritional status of the cotton bud stage on salinized soil via spectroscopic techniques and perform corresponding management measures to improve cotton yield. In this study, potted plants with different nitrogen application rates were set up to obtain the reflection spectral curves of cotton bud stage leaves, analyze their spectral characteristics under different nitrogen application rates, and establish spectral estimation models of chlorophyll density. The results are as follows: in the continuum removal spectrum of the cotton bud stage, the lowest point of the absorption valley near 500 nm shifted to the shortwave direction with an increasing nitrogen application rate. The mean reflectance between 765 and 880 nm was significantly different between nitrogen-stressed and nitrogen-unstressed cotton. The average reflectance of the near-infrared band, the absorption valley depths near 500 nm and 675 nm, the first derivative of the 710 nm reflectance, and the second derivatives of the 690 nm and 730 nm reflectance increased with increasing nitrogen application and chlorophyll density, and significant correlations were observed with the chlorophyll density. These parameters were modeled using support vector regression (SVR) and artificial neural network (ANN) methods, two commonly used algorithms in the field of machine learning. The determination coefficients of the three chlorophyll samples via the ANN models were 0.92, 0.77, and 0.94 for the modeling set and 0.77, 0.69, and 0.77 for the verification set. The ratio of quartile to root-mean-square error (RPIQ) of the ANN model was greater than 2.2, and the ratio of the standard error of the measured value to the standard error of the predicted (SEL/SEP) was close to 1, indicating that the chlorophyll density estimation models built based on the ANN algorithm had robust prediction ability. Our model could accurately estimate the leaf chlorophyll density in the cotton bud stage.

Effects of dense planting patterns on photosynthetic traits of different vertical layers and yield of wheat under different nitrogen rates

A two-year field experiment was conducted to measure the effects of densification methods on photosynthesis and yield of densely planted wheat. Inter-plant and inter-row distances were used to define rate-fixed pattern (RR) and row-fixed pattern (RS) density treatments. Meanwhile, four nitrogen (N) rates (0, 144, 192, and 240 kg N ha−1, termed N0, N144, N192, and N240) were applied with three densities (225, 292.5, and 360 × 104 plants ha−1, termed D225, D292.5, and D360). The wheat canopy was clipped into three equal vertical layers (top, middle, and bottom layers), and their chlorophyll density (ChD) and photosynthetically active radiation interception (FIPAR) were measured. Results showed that the response of ChD and FIPAR to N rate, density, and pattern varied with different layers. N rate, density, and pattern had significant interaction effects on ChD. The maximum values of whole-canopy ChD in the two seasons appeared in N240 combined with D292.5 and D360 under RR, respectively. Across two growing seasons, FIPAR values of RR were higher than those of RS by 29.37% for the top layer and 5.68% for the middle layer, while lower than those of RS by 20.62% for the bottom layer on average. With a low N supply (N0), grain yield was not significantly affected by density for both patterns. At N240, increasing density significantly increased yield under RR, but D360 of RS significantly decreased yield by 3.72% and 9.00% versus D225 in two seasons, respectively. With an appropriate and sufficient N application, RR increased the yield of densely planted wheat more than RS. Additionally, the maximum yield in two seasons appeared in the combination of D360 with N144 or N192 rather than of D225 with N240 under both patterns, suggesting that dense planting combined with an appropriate N-reduction application is feasible to increase photosynthesis capacity and yield.

Seasonal patterns of phytoplankton photoacclimation in a dimictic oligotrophic lake over 5 yr: Implications for chlorophyll as an estimate of biomass

AbstractChlorophyll a is commonly used as a surrogate for algal biomass in lakes and oceans even though phytoplankton can readily adjust intracellular chlorophyll concentration to changes in the environment through a cellular process termed photoacclimation. Marine studies have documented fluctuations in cellular chlorophyll to year‐round changes in light intensity and nutrients using the chlorophyll : carbon ratio to estimate cellular pigment density. However, similar freshwater studies are almost exclusively limited to chlorophyll : carbon ratios at the summertime deep chlorophyll maximum (DCM) depth in less productive water. This study expands direct estimates of freshwater photoacclimation to all seasons of the year utilizing optically derived estimates of algal carbon and chlorophyll fluorescence from high‐frequency (daily) data. We describe patterns of photoacclimation at daily, seasonal, and interannual time scales over a 5‐yr period. We show that increases in chlorophyll density at the cellular level not only occurred at the DCM depth during summer stratification but were a dominant and recurring feature when the lake was vertically mixing in fall, winter, and spring. Pigment density within the mixed layer was negatively correlated with light level, indicating a photoacclimation driven response to reduced light intensity. Predicting how cellular pigment density is affected by the surrounding environment in a replicated range of lake systems is needed if chlorophyll is to be accurately used as an estimate of algal biomass in freshwaters.

The Leaf Properties, Stomatal Index and Chlorophyll Content of Turkish Hazelnut (Corylus avellana L.) Cultivars

In the present study, leaf micromorphlogical properties, stoma indexs and chlorophll contents of 20 Turkish hazelnut (Corylus avellana) cultivars were studied. Investigated cultivars were “Acı, Allahverdi, Cavcava, Çakıldak, Foşa, Giresun melezi, Incekara, Kalınkara, Kan, Karafındık, Kargalak, Kuş, Mincane, Okay 28, Palaz, Sivri, Uzunmusa, Tombul, Yassı Badem, Yuvarlak Badem”. Three wax ornamentation types are recognized; crust, smooth and granules. Epidermal features, stomatal index and chlorophyll amounts showed some differences between C. avellana cultivars. Stoma width and stoma length were determined to be important for Palaz, Kuş, Yuvarlak Badem ve Yassı Badem cultivars. Stoma index, upper epidermis and lower epidermis width, upper epidermis and lower epidermis length values were determined to be distinctive for Allahverdi, Kargalak, Kara and Mincane. Chlorophyll density was found to be distinctive for Sivri, Çakıldak, İncekara and Acı cultivars The highest similarity was found between Okay 28 and Tombul cultivars with a rate of 0.98. The lowest similarity was found between Sivri-Karafındık, Sivri-Foşa and Sivri-Kargalak with 0.87.

A new spectral index for estimation of wheat canopy chlorophyll density: considering background interference and view zenith angle effect

A new spectral index for estimation of wheat canopy chlorophyll density: considering background interference and view zenith angle effect

Evaluating the Canopy Chlorophyll Density of Maize at the Whole Growth Stage Based on Multi-Scale UAV Image Feature Fusion and Machine Learning Methods

Maize is one of the main grain reserve crops, which directly affects the food security of the country. It is extremely important to evaluate the growth status of maize in a timely and accurate manner. Canopy Chlorophyll Density (CCD) is closely related to crop health status. A timely and accurate estimation of CCD is helpful for managers to take measures to avoid yield loss. Thus, many methods have been developed to estimate CCD with remote sensing data. However, the relationship between the CCD and the features used in these CCD estimation methods at different growth stages is unclear. In addition, the CCD was directly estimated from remote sensing data in most previous studies. If the CCD can be accurately estimated from the estimation results of Leaf Chlorophyll Density (LCD) and Leaf Area Index (LAI) remains to be explored. In this study, Random Forest (RF), Support Vector Machines (SVM), and Multivariable Linear Regression (MLR) were used to develop CCD, LCD, and LAI estimation models by integrating multiple features derived from unmanned aerial vehicle (UAV) multispectral images. Firstly, the performances of the RF, SVM, and MLR trained over spectral features (including vegetation indices and band reflectance; dataset I), texture features (dataset II), wavelet coefficient features (dataset III), and multiple features (dataset IV, including all the above datasets) were analyzed, respectively. Secondly, the CCDP was calculated from the estimated LCD and estimated LAI, and then the CCD was estimated based on multiple features and the CCDP was compared. The results show that the correlation between CCD and different features is significantly different at every growth stage. The RF model trained over dataset IV yielded the best performance for the estimation of LCD, LAI, and CCD (R2 values were 0.91, 0.97, and 0.97, and RMSE values were 6.59 μg/cm2, 0.35, and 24.85 μg/cm2). The CCD directly estimated from dataset IV is slightly closer to the ground truth CCD than the CCDP (R2 = 0.96, RMSE = 26.85 μg/cm2) calculated from LCD and LAI. The results indicated that the CCD of maize can be accurately estimated from multiple multispectral image features at the whole growth stage, and both CCD estimation strategies can be used to estimate the CCD accurately. This study provides a new reference for accurate CCD evaluation in precision agriculture.

The Effects of Two Organic Soil Amendments, Biochar and Insect Frass Fertilizer, on Shoot Growth of Cereal Seedlings

To mitigate the environmental harm associated with high-input agriculture, arable farmers are increasingly required to maintain productivity while reducing inputs of synthetic fertilizers. Thus, a diverse range of organic products are now being investigated in terms of their value as alternative fertilizers and soil amendments. This study used a series of glasshouse trials to investigate the effects of an insect frass-based fertilizer derived from black soldier fly waste [HexaFrass™, Meath, Ireland] and biochar on four cereals grown in Ireland (barley, oats, triticale, spelt) as animal feed and for human consumption. In general, the application of low quantities of HexaFrass™ resulted in significant increases in shoot growth in all four cereal species, along with increased foliage concentrations of NPK and SPAD levels (a measure of chlorophyll density). These positive effects of HexaFrass™ on shoot growth were observed, however, only when a potting mix with low basal nutrients was used. Additionally, excessive application of HexaFrass™ resulted in reduced shoot growth and, in some cases, seedling mortality. The application of finely ground or crushed biochar produced from four different feedstocks (Ulex, Juncus, woodchip, olive stone) had no consistent positive or negative effects on cereal shoot growth. Overall, our results indicate that insect frass-based fertilizers have good potential in low-input, organic, or regenerative cereal production systems. Based on our results, biochar appears to have less potential as a plant growth promoting product, but could be used as a tool for lowering whole-farm carbon budgets by providing a simplistic means of storing carbon in farm soils.

Nitrogen addition alters soil fungal communities, but root fungal communities are resistant to change.

Plants are colonized by numerous microorganisms serving important symbiotic functions that are vital to plant growth and success. Understanding and harnessing these interactions will be useful in both managed and natural ecosystems faced with global change, but it is still unclear how variation in environmental conditions and soils influence the trajectory of these interactions. In this study, we examine how nitrogen addition alters plant-fungal interactions within two species of Populus - Populus deltoides and P. trichocarpa. In this experiment, we manipulated plant host, starting soil (native vs. away for each tree species), and nitrogen addition in a fully factorial replicated design. After ~10 weeks of growth, we destructively harvested the plants and characterized plant growth factors and the soil and root endosphere fungal communities using targeted amplicon sequencing of the ITS2 gene region. Overall, we found nitrogen addition altered plant growth factors, e.g., plant height, chlorophyll density, and plant N content. Interestingly, nitrogen addition resulted in a lower fungal alpha diversity in soils but not plant roots. Further, there was an interactive effect of tree species, soil origin, and nitrogen addition on soil fungal community composition. Starting soils collected from Oregon and West Virginia were dominated by the ectomycorrhizal fungi Inocybe (55.8% relative abundance), but interestingly when P. deltoides was grown in its native West Virginia soil, the roots selected for a high abundance of the arbuscular mycorrhizal fungi, Rhizophagus. These results highlight the importance of soil origin and plant species on establishing plant-fungal interactions.

Photosynthesis in rice is increased by CRISPR/Cas9-mediated transformation of two truncated light-harvesting antenna.

Plants compete for light partly by over-producing chlorophyll in leaves. The resulting high light absorption is an effective strategy for out competing neighbors in mixed communities, but it prevents light transmission to lower leaves and limits photosynthesis in dense agricultural canopies. We used a CRISPR/Cas9-mediated approach to engineer rice plants with truncated light-harvesting antenna (TLA) via knockout mutations to individual antenna assembly component genes CpSRP43, CpSRP54a, and its paralog, CpSRP54b. We compared the photosynthetic contributions of these components in rice by studying the growth rates of whole plants, quantum yield of photosynthesis, chlorophyll density and distribution, and phenotypic abnormalities. Additionally, we investigated a Poales-specific duplication of CpSRP54. The Poales are an important family that includes staple crops such as rice, wheat, corn, millet, and sorghum. Mutations in any of these three genes involved in antenna assembly decreased chlorophyll content and light absorption and increased photosynthesis per photon absorbed (quantum yield). These results have significant implications for the improvement of high leaf-area-index crop monocultures.

Morphometric parameters and photosynthetic performance of in vitro propagated pineapple

Pineapple (Ananas comosus) is a horticultural species of the Bromeliaceae family of high socioeconomic interest, widely cultivated around the world. The multiplication of pineapple seedlings in the field can be time-consuming, requiring a significant labor investment. The objective of this study was to evaluate the performance of continuous and temporary immersion systems in the micropropagation scale-up of the species. Shoots were obtained from explants subcultured in flasks with gelled culture medium and without gas exchange. The shoots were transferred to liquid MS medium supplemented with 2mM NAA, and 4mM BAP, and cultivated in four different devices: sealed flasks, flasks with semipermeable gas membranes, RITA®, and twin-flasks. After 45 days of cultivation, plant growth, fresh mass increment, the stomatal density of the abaxial surface of the leaves, the maximum quantum yield of the photosystem II, and contents of chlorophyll and carotenoids were analyzed. Significant differences were observed in plant growth, stomatal density, and contents of chlorophyll and carotenoids. The twin-flasks and RITA® devices revealed better results in morphological parameters, such as plant growth and stomatal density, while the treatments in sealed flasks and with membrane stood out in the chlorophyll content.

Variation in leaf characters and agronomical traits of Yard-long bean genotypes between Dimocarpus longan and Psidium guajava stand

Abstract. Putra FP, Kusmiyati F, Anwar S, Widaryati, Sas MGA. 2022. Variation in leaf characters and agronomical traits of Yard-long bean genotypes between Dimocarpus longan and Psidium guajava stand. Biodiversitas 23: 5752-5758. Yard-long bean (Vigna unguiculata subs. sesquipedalis) is one of the most familiar horticulture crops. Leaf characteristics such as trichomes, stomata, and chlorophyll content correlated to other traits that influenced tolerance under sub-optimum conditions and component production traits. This study aimed to evaluate the leaf characters and agronomical traits variations of the Yard-long bean genotypes. The study was conducted by Split-plot design, with the primary factor were shading between Psidium guajava and Dimocarpus longan Lour. stand. The sub-plot was seven genotypes of Yard-long beans. Analyses were performed of multiple components, including the density of trichome, density of stomata, chlorophylls, carotenoids, nitrate reductase activity, flowering times, harvesting times, and production components under shading conditions between D. longan and P. guajava stands. The density of trichome, density of stomata, total chlorophyll, carotenoid, and Nitrate reductase activity showed the variability responses for each genotype in different shading conditions. One genotype showed early flowering in shaded conditions between D. longan than in shaded conditions between P. guajava. Two genotypes have the potential to adapt under shade conditions between D. longan. The morpho-agronomic characters that have been characterized may be used as potential donors for future hybridization programs to develop superior yard-long bean varieties.

Monitoring maize canopy chlorophyll density under lodging stress based on UAV hyperspectral imagery

Lodging causes severe decreases in crop yield, reduces grain quality, and increases the difficulty of mechanical harvesting. Obtaining the spatial distribution information of maize lodging grades in a timely and accurate manner is essential for yield loss assessment, post-stress management, and insurance claims settlements. The purpose of this study is to explore the ability of unmanned aerial vehicle (UAV) imaging technology to monitor maize lodging stress. With the support of maize lodging control experiments, the canopy chlorophyll density (CCD) of maize populations under stress from different lodging grades was used as the characterization index. The responses between hyperspectral characteristic parameters and CCD with different lodging grade stresses were analyzed. The monitoring model of the maize CCD under lodging stress was constructed using the sensitive characteristic parameters of original canopy spectra (OCS), first-order differential (FOD), wavelet coefficient (WC), and vegetation index (VI). The results showed that the reflectance of the stalk was significantly higher than that of the leaf in hyperspectral imagery, which was the main reason for the change in the original canopy spectra under lodging stress. The original canopy spectral reflectance increased with the severity of lodging stress. The accuracy of the CCD model was VI > WC > FOD > OCS (R2 = 0.63, 0.61, 0.59, 0.57, respectively), in which the accuracy of VI was the highest (R2 = 0.63, RMSE = 0.36 g/m3). This is because CCD considers not only the change in canopy spatial structure after maize lodging, but also the change in physiological activity of maize plants under lodging stress. The maize lodging grades were evaluated according to the CCD model based on the UAV hyperspectral imagery.

Morphological and Anatomical Variations of Vicia faba L. Seedlings in Response to Static Magnetic Force

Static magnetic force (SMF) is the most important factors affecting all living creatures. This force investigated for its effect on human physiology, animal behavior and migration and plant germination and horticulture. Vicia faba seeds subjected to static magnetic forces arising from iron magnetic (4.0X2.5X1.0 cm, Y30H) in two regimes. The first one (A) post soaked seeds exposed to five magnetic cycles for 30 minutes and 30 minutes in between the two cycles. Then these seeds (A) soaked in tap water for six hours before starting the germination. The second portion (B), first soaked in tap water (Presoaked) for six hours, then exposed to the five cycles beside the Blank seeds. Germination %, seedlings morphology and anatomical structure recorded throughout the experiment which last for about 26 days. The germination % increased in the first regime (A) than the control, while the second regime (B) delayed the germination till the first two weeks and then respond to be as the blank ones. The most effective seedlings portions are the root system, the leaf color and area, leaf ptyxis , number of cortex layers, chlorophyll density beside the type of vascular bundles as well as xylem/phloem ratio.
 SMF has great effect on seed germination, seedling morphology andanatomicalstructure of the stem.

Simultaneous and nondestructive diagnostics of nitrogen/magnesium/potassium-deficient cucumber leaf based on chlorophyll density distribution features

Nitrogen (N), magnesium (Mg), and potassium (K) deficiency all result in the decrease of chlorophyll density (CH.D) in cucumber leaf, but it is difficult to differentiate N/Mg/K-deficient leaves using CH.D. New nutrient indicators based on CH.D distribution features of the whole cucumber leaf were proposed to simultaneously diagnose N/Mg/K-deficient cucumber plants. CH.D distribution map in N/Mg/K-deficient and control leaves were determined non-destructively using hyperspectral imaging with the wavelength range of 430–960 nm. Compared with the CH.D distribution map of control group leaves, a decrease in CH.D could be observed on the whole area of N-deficient leaves, Mg-deficient leaves presented pixels with low CH.D between main leaf vein, and pixels with low CH.D at the border of K-deficient leaves. Distribution features were extracted from the CH.D distribution map and were employed to diagnose N/Mg/K-deficient leaves simultaneously, with the diagnostics rates of 96.67%. The results indicated that CH.D distribution features can realize the simultaneous diagnosing in the early stage of N/Mg/K deficiency and timely guidance of top dressing is of great significance to increase yield.

Interactions of melatonin with the micro-morphological structures and physiological characteristics of lemon balm

Melatonin (MEL) is defined as a plant master regulator. It regulates plant growth and development in various stress environments by increasing in amount. Effects of external MEL application on the content of the secretion products in micro-morphological structures of leaf trichomes of Melissa officinalis L. (lemon balm) without the presence of external stress factors were characterized. The relationships between different MEL concentrations and changes in type, density and size of trichomes, total chlorophyll and proline amounts, and secretion products were defined. Furthermore, monoterpenoids, which are the main products of trichomes that determine the quality of essential oils in lemon balm, varied under the effects of MEL. Especially 100 mM MEL concentration had the most dramatic impact. The highest number of glandular trichomes (GT) were observed at this concentration. 150 mM concentration of MEL had the opposite effect. At this concentration, significant decreases in secondary metabolite content and glandular structures were observed. Thus, it was concluded that MEL had a positive effect on these parameters up to a certain concentration. Changes in the size and number of GT due to MEL application is greatly reflected by the quality and content of secondary metabolites. Total chlorophyll, proline and monoterpene numbers were highest at 100 mM MEL concentration. The effects of MEL application without the presence of any stress conditions were supported by total chlorophyll and proline content. Important information was obtained about the relationship of these effects with the density of peltate trichomes and the chemical compounds and quality of essential oils.

Joint Retrieval of Winter Wheat Leaf Area Index and Canopy Chlorophyll Density Using Hyperspectral Vegetation Indices

Leaf area index (LAI) and canopy chlorophyll density (CCD) are key biophysical and biochemical parameters utilized in winter wheat growth monitoring. In this study, we would like to exploit the advantages of three canonical types of spectral vegetation indices: indices sensitive to LAI, indices sensitive to chlorophyll content, and indices suitable for both parameters. In addition, two methods for joint retrieval were proposed. The first method is to develop integration-based indices incorporating LAI-sensitive and CCD-sensitive indices. The second method is to create a transformed triangular vegetation index (TTVI2) based on the spectral and physiological characteristics of the parameters. PROSAIL, as a typical radiative transfer model embedded with physical laws, was used to build estimation models between the indices and the relevant parameters. Validation was conducted against a field-measured hyperspectral dataset for four distinct growth stages and pooled data. The results indicate that: (1) the performance of the integrated indices from the first method are various because of the component indices; (2) TTVI2 is an excellent predictor for joint retrieval, with the highest R2 values of 0.76 and 0.59, the RMSE of 0.93 m2/m2 and 104.66 μg/cm2, and the RRMSE (Relative RMSE) of 12.76% and 16.96% for LAI and CCD, respectively.

Remote sensing retrieval of winter wheat leaf area index and canopy chlorophyll density at different growth stages

ABSTRACT Leaf area index (LAI) and canopy chlorophyll density (CCD) are key indicators of crop growth status. In this study, we compared several vegetation indices and their red-edge modified counterparts to evaluate the optimal red-edge bands and the best vegetation index at different growth stages. The indices were calculated with Sentinel-2 MSI data and hyperspectral data. Their performances were validated against ground measurements using R2, RMSE, and bias. The results suggest that indices computed with hyperspectral data exhibited higher R2 than multispectral data at the late jointing stage, head emergence stage, and filling stage. Furthermore, red-edge modified indices outperformed the traditional indices for both data genres. Inversion models indicated that the indices with short red-edge wavelengths showed better estimation at the early jointing and milk development stage, while indices with long red-edge wavelength estimate the sought variables better at the middle three stages. The results were consistent with the red-edge inflection point shift at different growth stages. The best indices for Sentinel-2 LAI retrieval, Sentinel-2 CCD retrieval, hyperspectral LAI retrieval, and hyperspectral CCD retrieval at five growth stages were determined in the research. These results are beneficial to crop trait monitoring by providing references for crop biophysical and biochemical parameters retrieval.

Determination of Effective Mutation Dose on Walnut (Juglans regia L. cv. Chandler) Budwoods

Walnut (Juglans regia L., 2n=2x=32, Juglandaceae) is a deciduous temperate fruit species with an increasing economic importance and health benefits. The effective mutation dose (EMD) was not determined for ‘Chandler’ budwoods. The objective of this study was to determine the radiosensitivity of walnut budwoods to cobalt-60 gamma ray. One-year-old budwoods of ‘Chandler’ walnut cultivar carrying 4-5 buds in 20 cm in length were irradiated with cobalt-60. The gamma irradiation and chip budding were performed three different times. The budwoods were irradiated (1) with 0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100 Gy gamma doses on Apr 2017, (2) with 0, 20, 25, 30, 35, 40 Gy gamma doses on Sep 2017, and (3) with only 42 Gy gamma dose on Apr 2018. Then, gamma irradiated budwoods were chip budded on seedling rootstocks. Mutation 1 Vegetation 1 (M1V1) plants were obtained. The humidity content of the budwoods was determined after gamma irradiation. The bud take ratio, shoot length, and chlorophyll density of M1V1 plants were measured. From the shoot length of the plants, EMD was calculated as 42.1 Gy after the first irradiation on Apr, 2017, and that was calculated as 20.9 Gy in the second irradiation on Sep, 2017. The main plant population was obtained by previously calculated 42.1 Gy dose in the third irradiation on Apr, 2018. The survival rates of budded plants in three irradiation experiments were 21.6%, 54.8%, and 32.0%, respectively. According to the results, the most suitable gamma ray dose is 42.1 Gy.

Latitude and chlorophyll a density drive the distribution of carbohydrate-active enzymes in the planktonic microbial fraction of the epipelagic zone.

Microbes drive the majority of the global carbon cycle. The effect of environmental conditions on selecting microbial functional diversity is well established, and recent studies have revealed the effects of geographic distances on selecting the functional components of marine microbial communities. Our study is the first attempt at establishing the effects of environmental factors on driving the marine carbohydrate-active enzyme (CAZyme) distribution. We characterized the diversity of CAZyme genes and investigated the correlations between their distributions and biogeographic parameters (latitude, longitude, distance from the equator, site depth, water depth, chlorophyll density, salinity and temperature). Therefore, we accessed a subset of surface water samples (38 metagenomes) from the Global Ocean Sampling project. Only chlorophyll and latitude altered the distribution patterns of CAZymes, revealing the existence of two latitudinal gradients (positive and negative) of marine CAZyme abundance. Considering the importance of carbohydrates in microbial life, characterization of the spatial patterns of the genetic repertoire involved in carbohydrate metabolism represents an important step in improving our understanding of the metabolic strategies associated with the microbial marine carbon cycle and their effects on the productivity of marine ecosystems.