On correlation between canopy vegetation and growth indexes of maize varieties with different nitrogen efficiencies.

Studying the canopy spectral reflection characteristics of different N-efficient maize varieties and analyzing the relationship between their growth indicators and spectral vegetation indices can help the breeding and application of N-efficient maize varieties. To achieve the optimal management of N fertilizer resources, developing N-efficient maize varieties is necessary. In this research, maize varieties, i.e., the low-N-efficient (Zhengdan 958, ZD958), the high-N efficient (Xianyu 335, XY335), the double-high varieties (Qiule 368, QL368), and the double inefficient-type varieties (Yudan 606 YD606), were used as materials. Results indicate that nitrogen fertilization significantly increased the vegetation indices NDVI, GNDVI, GOSAVI, and RVI of maize varieties with different nitrogen efficiencies. These findings were consistent with the performance of yield, dry matter mass, and leaf nitrogen content and were also found highest under both medium and high nitrogen conditions in the double-high variety QL368. The correlations of dry matter quality, leaf nitrogen content, yield, and vegetation indices (NDVI, GNDVI, RVI, and GOSAVI) at the filling stage of different N-efficient maize varieties were all highly significant and positive. In this relationship, the best effect was found at the filling stages, with correlation coefficients reaching 0.772-0.942, 0.774-0.970, 0754-0.960, and 0.800-0.960. The results showed that the yield, dry matter weight, and leaf nitrogen content of maize varieties with different nitrogen efficiencies increased first and then stabilized with the increase in the nitrogen application level in different periods, and the highest nitrogen application level of maize yield should be between 270 and 360 kg/hm2. At the filling stage, canopy vegetation index of maize varieties with different nitrogen efficiencies was positively correlated with yield, dry matter weight, and leaf nitrogen content, especially GNDVI and GOSAVI on the leaf nitrogen content. It can be used as a means to predict its growth index.

Study on nitrogen demand model in pakchoi (Brassica campestris ssp. Chinensis L.) based on nitrogen contents and phenotypic characteristics.

Introduction: In precision agriculture, the diagnosis of the nitrogen (N) nutrition status based on the plant phenotype, combined effects of soil types, various agricultural practices, and environmental factors which are essential for plant N accumulation. It helps to assess the N supply for plants at the right time and optimal amount to ensure high N use efficiency thereby reducing the N fertilizer applications to minimize environmental pollution. For this purpose, three different experiments were performed. Methods: A critical N content (Nc) model was constructed based on cumulative photothermal effect (LTF), Napplications, and cultivation systems on yield and N uptake in pakchoi. Results and discussion: According to the model, aboveground dry biomass (DW) accumulation was found equal or below to 1.5 t/ha, and the Nc value was observed at a constant of 4.78%. However, when DW accumulation exceeded 1.5 t/ha, Nc declined with the increase in DW accumulation, and the relationship between Nc and DW accumulation developed with the function Nc %=4.78 x DW-0.33. An N demand model was established based on the multi-information fusion method, which integrated multiple factors, including Nc, phenotypical indexes, temperature during the growth period, photosynthetically active radiation, and N applications. Furthermore, the model's accuracy was verified, and the predicted N contents were found consistent with the measured values (R2 = 0.948 and RMSE = 1.96 mg/plant). At the same time, an N demand model based on N use efficiency was proposed. Conclusions: This study can provide theoretical and technical support for precise N management in pakchoi production.

Ultrahigh Nitrogen Content Carbon Nanosheets for High Stable Sodium Metal Anodes.

Sodium metal, with a high theoretical specific capacity of 1165 mAh g-1 , is the ultimate anode for sodium batteries, yet how to deal with the inhomogeneous and dendritic sodium deposition and the infinite relative dimension change of sodium metal anodes during sodium depositing/stripping is still challenging. Here, a facile fabricated sodiuphilic 2D N-doped carbon nanosheets (N-CSs) are proposed as sodium host material for sodium metal batteries (SMBs) to prevent dendrite formation and eliminate volume change during cycling. Revealing from combined in situ characterization analyses and theoretical simulations, the high nitrogen content and porous nanoscale interlayer gaps of the 2D N-CSs can not only concede dendrite-free sodium stripping/depositing but also accommodate the infinite relative dimension change. Furthermore, N-CSs can be easily process into N-CSs/Cu electrode via traditional commercial battery electrode coating equipment that pave the way for large-scale industrial applications. On account of the abundant nucleation sites and sufficient deposition space, N-CSs/Cu electrodes demonstrate a superior cycle stability of more than 1500 h at a current density of 2 mA cm-2 with a high coulomb efficiency of more than 99.9% and ultralow nucleation overpotential, which enable reversible and dendrites-free SMBs and shed light on further development of SMBs with even higher performance.

Shedding Light on Degradation Gradients in Celluloid: An ATR-FTIR Study of Artificially and Naturally Aged Specimens.

Celluloid artifacts are known by conservation professionals to be prone to degradation, threatening their own integrity and that of nearby heritage collections. Celluloid alteration can have a heterogeneous nature, and this research topic is still in its infancy for heritage science. This article investigates degradation gradients, both along depth and width, of artificially aged celluloid sheets, and compares them to three-dimensional (3D) historical objects with the aim of gaining a better insight into the nature and evolution of their decay. ATR-FTIR was used to systematically study different sampling points of the artificially and naturally aged specimens and allowed us to recognize better-preserved surfaces and more deteriorated cores. ATR-FTIR was found suitable for assessing the molecular changes induced by degradation, particularly denitration and formation of carbonyl-containing degradation products in severely aged specimens. Even though the severely artificially aged sheets displayed unusual alteration phenomena, they present a degradation gradient similar to the one observed for the naturally aged 3D objects under study. This research underlines that sampling at different depths and/or widths is relevant for characterizing the heterogeneity of degraded celluloid, and further investigation with chromatographic techniques would greatly benefit the understanding of the complex degradation of celluloid artifacts.

Leaf functional traits have more contributions than climate to the variations of leaf stable carbon isotope of different plant functional types on the eastern Qinghai-Tibetan Plateau.

Elucidating the mechanisms that control the leaf stable carbon isotope values (δ13Cleaf) is the prerequisite for the widespread application of δ13Cleaf. However, the competing effects of physiological and environmental factors on δ13Cleaf variations of the different plant functional types (PFTs) have not been disentangled, and the corresponding mechanisms remain unclear. Based on large-scale δ13Cleaf measurements on the eastern Qinghai-Tibetan Plateau, the relative contributions and regulatory pathways of leaf functional traits (LFTs) and climatic factors to δ13Cleaf variations of the different PFTs were investigated. We found that δ13Cleaf of the different PFTs was correlated with annual mean precipitation negatively, but not a simple linear relationship with annual mean temperature and varied by PFTs. Leaf nitrogen content per unit area and leaf mass per area (correlated with δ13Cleaf positively) had more substantial effects on the δ13Cleaf variations of the different PFTs than other LFTs. The relative contributions of LFTs to the δ13Cleaf variations were greater than that of climatic factors, and the direct and indirect effects of climatic factors on δ13Cleaf variations varied by PFTs. Our findings provide new insights into understanding key drivers of δ13Cleaf variations at the PFT level on a regional scale.

Domestication provides durum wheat with protection from locust herbivory.

Lower plant resistance to herbivores following domestication has been suggested as the main cause for higher feeding damage in crops than in wild progenitors. While herbivore compensatory feeding has also been proposed as a possible mechanism for raised damage in crops with low nutritional quality, predictions regarding the effects of plant domestication on nutritional quality for herbivores remain unclear. In particular, data on primary metabolites, even major macronutrients, measured in the organs consumed by herbivores, are scarce. In this study, we used a collection of 10 accessions of wild ancestors and 10 accessions of modern progenies of Triticum turgidum to examine whether feeding damage and selectivity by nymphs of Locusta migratoria primarily depended on five leaf traits related to structural resistance or nutrient profiles. Our results unexpectedly showed that locusts favored wild ancestors over domesticated accessions and that leaf toughness and nitrogen and soluble protein contents increased with the domestication process. Furthermore, the quantitative relationship between soluble protein and digestible carbohydrates was found to poorly meet the specific requirements of the herbivore, in all wheat accessions, both wild and modern. The increase in leaf structural resistance to herbivores in domesticated tetraploid wheat accessions suggested that resource allocation trade-offs between growth and herbivory resistance may have been disrupted by domestication in the vegetative organs of this species. Since domestication did not result in a loss of nutritional quality in the leaves of the tetraploid wheat, our results rather provides evidence for a role of the content of plants in nonnutritive nitrogenous secondary compounds, possibly deterrent or toxic, at least for grasshopper herbivores.

Effects of Grazing, Extreme Drought, Extreme Rainfall and Nitrogen Addition on Vegetation Characteristics and Productivity of Semiarid Grassland.

Grassland use patterns, water and nutrients are the main determinants of ecosystem structure and function in semiarid grasslands. However, few studies have reported how the interactive effects of rainfall changes and nitrogen deposition influence the recovery of semiarid grasslands degraded by grazing. In this study, a simulated grazing, increasing and decreasing rainfall, nitrogen deposition test platform was constructed, and the regulation mechanism of vegetation characteristics and productivity were studied. We found that grazing decreased plant community height (CWMheight) and litter and increased plant density. Increasing rainfall by 60% from May to August (+60%) increased CWMheight; decreasing rainfall by 60% from May to August (-60%) and by 100% from May to June (-60 d) decreased CWMheight and coverage; -60 d, +60% and increasing rainfall by 100% from May to June (+60 d) increased plant density; -60% increased the Simpson dominance index (D index) but decreased the Shannon-Wiener diversity index (H index); -60 d decreased the aboveground biomass (ABG), and -60% increased the underground biomass (BGB) in the 10-60 cm layer. Nitrogen addition decreased species richness and the D index and increased the H index and AGB. Rainfall and soil nitrogen directly affect AGB; grazing and rainfall can also indirectly affect AGB by inducing changes in CWMheight; grazing indirectly affects BGB by affecting plant density and soil nitrogen. The results of this study showed that in the semiarid grassland of Inner Mongolia, grazing in the nongrowing season and grazing prohibition in the growing season can promote grassland recovery, continuous drought in the early growing season will have dramatic impacts on productivity, nitrogen addition has a certain impact on the species composition of vegetation, and the impact on productivity will not appear in the short term.

Visible and near-infrared spectroscopy and deep learning application for the qualitative and quantitative investigation of nitrogen status in cotton leaves.

Leaf nitrogen concentration (LNC) is a critical indicator of crop nutrient status. In this study, the feasibility of using visible and near-infrared spectroscopy combined with deep learning to estimate LNC in cotton leaves was explored. The samples were collected from cotton's whole growth cycle, and the spectra were from different measurement environments. The random frog (RF), weighted partial least squares regression (WPLS), and saliency map were used for characteristic wavelength selection. Qualitative models (partial least squares discriminant analysis (PLS-DA), support vector machine for classification (SVC), convolutional neural network classification (CNNC) and quantitative models (partial least squares regression (PLSR), support vector machine for regression (SVR), convolutional neural network regression (CNNR)) were established based on the full spectra and characteristic wavelengths. Satisfactory results were obtained by models based on CNN. The classification accuracy of leaves in three different LNC ranges was up to 83.34%, and the root mean square error of prediction (RMSEP) of quantitative prediction models of cotton leaves was as low as 3.36. In addition, the identification of cotton leaves based on the predicted LNC also achieved good results. These results indicated that the nitrogen content of cotton leaves could be effectively detected by deep learning and visible and near-infrared spectroscopy, which has great potential for real-world application.

Seasonal dynamics of photosynthetic nitrogen content and partitioning in deciduous forests.

Nitrogen allocated to the photosynthetic apparatus and its partitioning into different photosynthetic components is crucial for understanding plant carbon gain and plant productivity. It is known that photosynthetic nitrogen content and partitioning are controlled by both environmental and vegetation factors and have versatile and dynamic responses. However, such responses are greatly simplified in most current gas exchange models, in which only a prescribed relationship is commonly applied to describe the effect of nitrogen on photosynthesis and with limited model performance. While within-canopy variation at a specific time in leaf photosynthetic nitrogen content and partitioning has been studied previously, far less attention has been paid to the seasonal dynamics of photosynthetic nitrogen content and partitioning, which is especially critical to deciduous forests. In this study, we integrated long-term field observations in deciduous forests in Japan to determine seasonal patterns of photosynthetic nitrogen content and partitioning (rubisco, electron transport, and light capture) and to examine how photosynthetic nitrogen content and partitioning varied seasonally in deciduous forest canopies growing at different altitudes. The results demonstrated that there were remarkable seasonal variations in both photosynthetic nitrogen content and partitioning in deciduous forests along the altitudinal gradient. Moreover, photosynthetic nitrogen use efficiency was well explained by nitrogen partitioning rather than total leaf nitrogen. These results suggest that seasonal patterns of nitrogen partitioning should be integrated into ecosystem models to accurately project emergent properties of ecosystem productivity on local, regional, and global scales.

Environmental drivers of the leaf nitrogen and phosphorus stoichiometry characteristics of critically endangered Acer catalpifolium.

Acer catalpifolium is a perennial deciduous broad-leaved woody plant, listed in the second-class protection program in China mainly distributed on the northwest edge of Chengdu plain. However, extensive anthropogenic disturbances and pollutants emissions (such as SO2, NH3 and NOX) in this area have created a heterogeneous habitat for this species and its impacts have not been systematically studied. In this study, we investigated the leaf nitrogen (N) and phosphorus (P) content of A. catalpifolium in the natural distribution areas, and a series of simulation experiments (e.g., various water and light supply regimes, different acid and N deposition levels, reintroduction management) were conducted to analyze responses of N and P stoichiometric characteristics to environmental changes. The results showed that leaf nitrogen content (LNC) was 14.49 ~ 25.44 mg g-1, leaf phosphorus content (LPC) was 1.29~3.81 mg g-1 and the N/P ratio of the leaf (L-N/P) was 4.87~13.93. As per the simulation experiments, LNC of A. catalpifolium is found to be relatively high at strong light conditions (80% of full light), high N deposition (100 and 150 kg N ha-1), low acidity rainwater, reintroduction to understory area or N fertilizer applications. A high level of LPC was found when applied with 80% of full light and moderate N deposition (100 kg N ha-1). L-N/P was high under severe shade (8% of full light), severe N deposition (200 kg N ha-1), and reintroduction to gap and undergrowth habitat; however, low L-N/P was observed at low acidity rainwater or P fertilizer application. The nutrient supply facilitates corresponding elements uptake, shade tends to induce P limitation and soil acidification shows N limitation. Our results provide theoretical guidance for field management and nutrient supply regimes for future protection, population rejuvenation of this species and provide guidelines for conservation and nutrient management strategies for the endangered species.

Hydrothermal carbonization coupling with liquid dimethyl ether extraction pretreatment of sewage sludge: Hydrochar performance improvement and low-nitrogen biocrude production.

Hydrothermal carbonization of sewage sludge converts waste into hydrochar; however, the complex organic composition of feedstock limits the product value. A novel process that combines liquid dimethyl ether extraction and hydrothermal carbonization (DE-HTC) was proposed for improving the product value by simultaneously producing biocrude/hydrochar and improving feedstock suitability for thermochemical conversion. Biocrude and hydrochar with a product yield of 2.62% and 55.83% were produced via DE-HTC, respectively. The hydrochar yield increased by 12.65%-29.90% compared to traditional single-step hydrothermal carbonization. The hydrochar energy densification was decreased by 1.16%-10.28%, while hydrochar's energy yield increased by 47%-66%, and it had a more prominent porous structure. By avoiding the decomposition of proteins during thermochemical conversion, the nitrogen content of the biocrude obtained via DE-HTC was only 0.38%. The biocrude was also further qualitatively analyzed. This study provides insights into the efficacy of a novel hydrothermal method with distinct product value advantages over direct hydrothermal carbonization.

Physio-biochemical, agronomical, and gene expression analysis reveals different responsive approach to low nitrogen in contrasting rice cultivars for nitrogen use efficiency.

BACKGROUND: Nitrogen (N) is an essential macronutrient for plant growth and development as it is an essential constituent of biomolecules. Its availability directly impacts crop yield. Increased N application in crop fields has caused environmental and health problems, and decreasing nitrogen inputs are in demand to maintain crop production sustainability. Understanding the molecular mechanism of N utilization could play a crucial role in improving the nitrogen use efficiency (NUE) of crop plants. METHODS AND RESULTS: In the present study, the effect of low N supply on plant growth, physio-biochemical, chlorophyll fluorescence attributes, yield components, and gene expression analysis were measured at six developmental stages in rice cultivars. Two rice cultivars were grown with a supply of optimium (120 kg ha-1) and low N (60 kg ha-1). Cultivar Vikramarya excelled Aditya at low N supply, and exhibits enhanced plant growth, physiological efficiency, agronomic efficiency, and improved NUE due to higher N uptake and utilization at low N treatment. Moreover, plant biomass, leaf area, and photosynthetic rate were significantly higher in cv. Vikramarya than cv. Aditya at different growth stages, under low N treatment. In addition, enzymatic activities in cultivar Vikramarya were higher than cultivar Aditya under low nitrogen, indicating its greater potential for N metabolism. Gene expression analysis was carried out for the most important nitrogen assimilatory enzymes, such as nitrate reductase (NR), nitrite reductase (NiR), glutamine synthetase (GS), and glutamate synthase (GOGAT). Expression levels of these genes at different growth stages were significantly higher in cv. Vikramarya compared to cv. Aditya at low N supply. Our findings suggest that improving NUE needs specific revision in N metabolism and physiological assimilation. CONCLUSION: Overall differences in plant growth, physiological efficiency, biochemical activities, and expression levels of N metabolism genes in N-efficient and N-inefficient rice cultivars need a specific adaptation to N metabolism. Regulatory genes may separately or in conjunction, enhance the NUE. These results provide a platform for selecting crop cultivars for nitrogen utilization efficiency at low N treatment.

Multi-phase recovery of carabid assemblages during 19 years of secondary succession in forest stands disturbed by windstorm without salvage logging in northern Poland.

Windstorms impact the functioning and structure of forests and cause economic losses. For this reason, various potential methods of regenerating windthrown stands are investigated. Some of these studies use invertebrates, such as carabid beetles (Col., Carabidae). Salvage logging is used to recoup some of the economic ecosystem losses but increases the environmental impact of windthrow. I sampled ground beetles annually over 19 years (2003-2021y) in stands without salvage logging to test the effect of three varying levels of disturbance (severely, moderately and least disturbed stands with canopy cover of 10-30 %, 40-60 % and 70-90 %, respectively) on the regeneration of carabid assemblages and to determine its association with changes in the soil environment and in the recovering stands. Increased disturbance severity increased the abundance (up to 0.4 ind/trap/day) and species richness of ground beetles (up to 16.4) and proportion of beetles associated with early successional habitats (up to 53.5 %). Recovery of carabid assemblages and the environment was slowest in the severely disturbed stands, where at high soil pH nitrification initially increased the pool of nitrogen in the soil (up to 0.3), which was exploited by nitrophilous grasses taking over the space (up to 37,5 %), limiting the occurrence of forest species (decrease from 82.2 % to 51.4 %) and delaying the development of natural regeneration. Carabid recovery and ecosystem regeneration were associated with forest mosses surviving (84.1 % coverage) in patches with a high leaf area index (up to 1.9) and with the presence of Vaccinium vitis-idaea (up to 53.3 % coverage) in the moderately and least disturbed stands. The study indicated advanced successional development of carabid assemblages in less disturbed stands which can regenerate naturally. Natural recovery of carabids and regeneration of the most disturbed stands, rapidly taken over by nitrophilous grasses, was impeded; therefore, such stands should be regenerated traditionally.

Diversity and Differentiation of Duckweed Species from Israel.

Duckweeds (Lemnaceae) are tiny plants that float on aquatic surfaces and are typically isolated from temperate and equatorial regions. Yet, duckweed diversity in Mediterranean and arid regions has been seldom explored. To address this gap in knowledge, we surveyed duckweed diversity in Israel, an ecological junction between Mediterranean and arid climates. We searched for duckweeds in the north and center of Israel on the surface of streams, ponds and waterholes. We collected and isolated 27 duckweeds and characterized their morphology, molecular barcodes (atpF-atpH and psbK-psbI) and biochemical features (protein content and fatty acids composition). Six species were identified-Lemna minor, L. gibba and Wolffia arrhiza dominated the duckweed populations, and together with past sightings, are suggested to be native to Israel. The fatty acid profiles and protein content further suggest that diverged functions have attributed to different haplotypes among the identified species. Spirodela polyrhiza, W. globosa and L. minuta were also identified but were rarer. S. polyrhiza was previously reported in our region, thus, its current low abundance should be revisited. However, L. minuta and W. globosa are native to America and Far East Asia, respectively, and are invasive in Europe. We hypothesize that they may be invasive species to our region as well, carried by migratory birds that disperse them through their migration routes. This study indicates that the duckweed population in Israel's aquatic environments consists of both native and transient species.

The end-use quality of wheat can be enhanced by optimal water management without incurring yield loss.

In China, water-saving irrigation is playing important roles in ensuring food security, and improving wheat quality. A barrel experiment was conducted with three winter wheat (Triticum aestivum L.) genotypes and two irrigation pattens to examine the effects of regulated deficit irrigation (RDI) on wheat grain yield, water-use efficiency (WUE), and grain quality. In order to accurately control the soil water content, wheat was planted in the iron barrels set under a rainproof shelter, and the soil water content in the iron barrel was controlled by gravity method. The mechanisms whereby water management influences the end-use functional properties of wheat grain were also investigated. The results revealed that RDI improved the end-use functional properties of wheat and WUE, without significant yield loss (less than 3%). Moderate water deficit (60% to 65% field capacity) before jointing and during the late grain-filling stage combined with a slight water deficit (65% to 70% field capacity) from jointing to booting increased grain quality and WUE. The observed non-significant reduction in wheat yield associated with RDI may be attributed to higher rate of photosynthesis during the early stage of grain development and higher rate of transfer of carbohydrates from vegetative organs to grains during the later stage. By triggering an earlier rapid transfer of nitrogen deposited in vegetative organs, RDI enhances grain nitrogen content, which in turn could enhance dough elasticity, given the positive correlation between grain nitrogen content and dough midline peak value. Our results also indicate that the effects of RDI on grain quality are genotype dependent. Therefore, the grain end-use quality of some specific wheat genotypes may be enhanced without incurring yield loss by an optimal water management.

Nitrogen fertilization and CO2 concentration synergistically affect the growth and protein content of Agropyron mongolicum.

Background: The nitrogen (N) and protein concentrations in plant tissues exposed to elevated CO2 (eCO2) generally decline , such declines in forage grass composition are expected to have negative implications for the nutritional and economic value of grass. Plants require N for the production of a photosynthetically active canopy and storage proteins in the tissues, whose functionality will strongly influence productivity and quality. The objective of this study was to investigate whether eCO2 plus N-fertilization increases growth and N nutrition of Agropyron mongolicum, and the dependence of this improvement on the coordination between root and leaf development. Methods: We analyzed A. mongolicum from field-grown within the open-top chambers (OTCs) facility under two atmospheric CO2 (ambient, 400 ± 20 µmol mol-1, aCO2, and elevated, 800 ± 20 µmol mol-1, eCO2) and three N-fertigation treatments (control, low N-fertigation , and high N-fertigation) for two months. Results: Elevated CO2 plus N-fertigation strongly increased shoot and root biomass, and the nitrogen and protein concentrations of A. mongolicum compared to those plants at aCO2 levels. Increased N content in leaves and reduced specific leaf area (SLA) at a high N supply could alleviate photosynthetic acclimation to eCO2 and drive the production of greater shoot biomass with the potential for higher photosynthesis, productivity, and nutritional quality. The increased root length (RL), the ratio of total aboveground N taken up per RL (TN/RL), stomatal conductance (Gs), and transpiration rate (Tr) contribute to the transpiration-driven mass flow of N, consequently increasing N uptake by roots. In addition, a smaller percentage of N remained as unassimilated nitrate ( NO 3 - ) under eCO2, indicating that assimilation of NO 3 - into proteins was not inhibited by eCO2. These findings imply that grass productivity and quality will enhance under anticipated elevated CO2 concentration when effective management measures of N-fertilization are employed.

The potential for biochar application in "Shatangju" (Citrus reticulate cv.) orchard on acid red soil: Biochar prepared from its organic waste in an orchard.

Carbonization of agricultural and forestry wastes is the main use of biochar application in agriculture. In this study, the effects of biochar on the physical and chemical properties of soil and diversity in rhizosphere microorganisms, leaf nutrients and fruit quality of acid red soil in "Shatangju" (Citrus reticulate cv.) orchard were studied using organic wastes and small-scale carbonization furnaces from orchards were used to produce biochar. The results showed that the finished rate of biochar produced from the organic wastes in the orchard was approximately 37%, and the carbon content of the finished product was as high as 80%. The results suggested that the biochar produced in the orchard could meet the annual consumption of the orchard. Applying biochar can improve the physical and chemical properties of acid soil in the "Shatangju" orchard by enhancing the availability of various mineral nutrients such as nitrogen, phosphorus, potassium, calcium, magnesium and boron. The species and quantity of root and rhizosphere microbial communities (fungi, bacteria and archaea) increased, and the dominant bacterial group changed, manifested in the increase in microbial diversity. Biochar directly affected the soil pH value and increased the soil organic carbon content, which may be the main reason for the change in microbial diversity in the soil and rhizosphere of "Shatangju" in the orchard and pot tests. The fruit quality of each treatment group with biochar was also better than that of the control group and improved fruit coloring. In the pure soil test, whether or not chemical fertilizer was applied, 3% biochar amendments can provide a suitable pH value for "Shatangju" growth and are relatively stable. Regardless of whether or not fertilizer was applied, 1.5%-3% biochar improved the soil in the pot test. In the field, the biochar at a rate of 2.4 kg/plant to 3.6 kg/plant, respectively, was the best in improving soil physical and chemical properties, foliar nutrition and fruit quality. Therefore, the amount of biochar added in the open environment (if the garden) can be slightly adjusted according to the results of the closed environment test (pure soil test and pot test). In this experiment, we explored the self-recycling of organic carbon, mainly through the preparation of a simple small-scale biochar furnace suitable for the use by orchards, and selected the appropriate amount of biochar to improve the physical and chemical conditions of "Shatangju" orchard soil and increase fruit quality.

Estimation of the nitrogen content of potato plants based on morphological parameters and visible light vegetation indices.

Plant nitrogen content (PNC) is an important indicator to characterize the nitrogen nutrition status of crops, and quickly and efficiently obtaining the PNC information aids in fertilization management and decision-making in modern precision agriculture. This study aimed to explore the potential to improve the accuracy of estimating PNC during critical growth periods of potato by combining the visible light vegetation indices (VIs) and morphological parameters (MPs) obtained from an inexpensive UAV digital camera. First, the visible light VIs and three types of MPs, including the plant height (H), canopy coverage (CC) and canopy volume (CV), were extracted from digital images of the potato tuber formation stage (S1), tuber growth stage (S2), and starch accumulation stage (S3). Then, the correlations of VIs and MPs with the PNC were analyzed for each growth stage, and the performance of VIs and MPs in estimating PNC was explored. Finally, three methods, multiple linear regression (MLR), k-nearest neighbors, and random forest, were used to explore the effect of MPs on the estimation of potato PNC using VIs. The results showed that (i) the values of potato H and CC extracted based on UAV digital images were accurate, and the accuracy of the pre-growth stages was higher than that of the late growth stage. (ii) The estimation of potato PNC by visible light VIs was feasible, but the accuracy required further improvement. (iii) As the growing season progressed, the correlation between MPs and PNC gradually decreased, and it became more difficult to estimate the PNC. (iv) Compared with individual MP, multi-MPs can more accurately reflect the morphological structure of the crop and can further improve the accuracy of estimating PNC. (v) Visible light VIs combined with MPs improved the accuracy of estimating PNC, with the highest accuracy of the models constructed using the MLR method (S1: R 2 = 0.79, RMSE=0.27, NRMSE=8.19%; S2:R 2 = 0.80, RMSE=0.27, NRMSE=8.11%; S3: R 2 = 0.76, RMSE=0.26, NRMSE=8.63%). The results showed that the combination of visible light VIs and morphological information obtained by a UAV digital camera could provide a feasible method for monitoring crop growth and plant nitrogen status.

Soil Nitrogen Content Detection Based on Near-Infrared Spectroscopy.

Traditional soil nitrogen detection methods have the characteristics of being time-consuming and having an environmental pollution effect. We urgently need a rapid, easy-to-operate, and non-polluting soil nitrogen detection technology. In order to quickly measure the nitrogen content in soil, a new method for detecting the nitrogen content in soil is presented by using a near-infrared spectrum technique and random forest regression (RF). Firstly, the experiment took the soil by the Xunsi River in the area of Hubei University of Technology as the research object, and a total of 143 soil samples were collected. Secondly, NIR spectral data from 143 soil samples were acquired, and chemical and physical methods were used to determine the content of nitrogen in the soil. Thirdly, the raw spectral data of soil samples were denoised by preprocessing. Finally, a forecast model for the soil nitrogen content was developed by using the measured values of components and modeling algorithms. The model was optimized by adjusting the changes in the model parameters and Gini coefficient (∆Gini), and the model was compared with the back propagation (BP) and support vector machine (SVM) models. The results show that: the RF model modeling set prediction R2C is 0.921, the RMSEC is 0.115, the test set R2P is 0.83, and the RMSEP is 0.141; the detection of the soil nitrogen content can be realized by using a near-infrared spectrum technique and random forest algorithm, and its prediction accuracy is better than that of the BP and SVM models; using ∆ Gini to optimize the RF modeling data, the spectral information of the soil nitrogen content can be extracted, and the data redundancy can be reduced effectively.

Mapping landscape canopy nitrogen content from space using PRISMA data.

Satellite imaging spectroscopy for terrestrial applications is reaching maturity with recently launched and upcoming science-driven missions, e.g. PRecursore IperSpettrale della Missione Applicativa (PRISMA) and Environmental Mapping and Analysis Program (EnMAP), respectively. Moreover, the high-priority mission candidate Copernicus Hyperspectral Imaging Mission for the Environment (CHIME) is expected to globally provide routine hyperspectral observations to support new and enhanced services for, among others, sustainable agricultural and biodiversity management. Thanks to the provision of contiguous visible-to-shortwave infrared spectral data, hyperspectral missions open enhanced opportunities for the development of new-generation retrieval models of multiple vegetation traits. Among these, canopy nitrogen content (CNC) is one of the most promising variables given its importance for agricultural monitoring applications. This work presents the first hybrid CNC retrieval model for the operational delivery from spaceborne imaging spectroscopy data. To achieve this, physically-based models were combined with machine learning regression algorithms and active learning (AL). The key concepts involve: (1) coupling the radiative transfer models PROSPECT-PRO and SAIL for the generation of a wide range of vegetation states as training data, (2) using dimensionality reduction to deal with collinearity, (3) applying an AL technique in combination with Gaussian process regression (GPR) for fine-tuning the training dataset on in field collected data, and (4) adding non-vegetated spectra to enable the model to deal with spectral heterogeneity in the image. The final CNC model was successfully validated against field data achieving a low root mean square error (RMSE) of 3.4 g/m2 and coefficient of determination (R 2) of 0.7. The model was applied to a PRISMA image acquired over agricultural areas in the North of Munich, Germany. Mapping aboveground CNC yielded reliable estimates over the whole landscape and meaningful associated uncertainties. These promising results demonstrate the feasibility of routinely quantifying CNC from space, such as in an operational context as part of the future CHIME mission.