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The nitrogen content and solidification structure of the 1Mn18Cr18N ingots produced by the customized laboratory‐scale vacuum induction melting furnace and the pressure electroslag remelting furnace (PESR) with novel composite electrode under different pressure and the same power consumption are compared and studied. The results show that there are perfectly uniform radial chromium and nitrogen profiles during the PESR process. The nitrogen uptake reaction in the PESR process with composite electrode takes place on the liquid metal film on the electrode. Nitrogen uptake could be improved by increasing the nitrogen partial pressure. In addition, the basin depth at a pressure of 0.1 and 1.22 MPa is about 41 and 38 mm, the angle of the grains with respect to the vertical axis is 35° and 31°, respectively. The flat metal basin profile resulted from the thermal resistance at the slag–mold interface decreasing with increasing pressure. Primary and secondary dendritic arm spacing (PDAS and SDAS) variations exhibit an increasing and subsequently decreasing the trend as they move further away from the center in a horizontal direction. Both PDAS and SDAS decrease with increasing pressure from 0.1 to 1.22 MPa. [ABSTRACT FROM AUTHOR]

In the economically important red macroalga Pyropia, carbohydrates and proteins contents are usually used to evaluate the nutritional status and commercial value. As main component elements of carbohydrates and proteins, C, N and S contents can be the suitable indicators. However, efficient and nondestructive estimation of these elements have not been well established in macroalgae, which is definitely needed in high-throughput phenotyping and selective breeding. In the current study, hyperspectral imaging was used to estimate the C, N and S contents in thalli of Pyropia yesoensis. Based on spectral information acquired by two hyperspectral cameras with range of 400 nm to 1700 nm, two machine learning methods, partial least squares regression (PLSR) and support vector machine regression (SVR), were performed to establish prediction models following different preprocessing methods. The result showed that SVR model following Savitzky-Golay (S-G) smoothing preprocessing performed the best for N content with excellent accuracy (RTest2 = 0.94, RMSE = 0.331, MAPE = 5.47%, RPD = 3.44). Both of PLSR and SVR models could not yet meet satisfactory prediction for C and S content with RTest2 < 0.4 and RPD < 1.5. Further validation on field samples corroborated accuracy and robustness of the optimal estimation model for N. This study demonstrates that hyperspectral imaging is effective for estimating N contents of P.yesoensis thalli. It unveils the capability of hyperspectral imaging with machine learning models for estimating macroelement contents in macroalgae thalli, and offers a convenient, non-destructive, and effective method for the phenotyping and selective breeding of macroalgae. [ABSTRACT FROM AUTHOR]

The nitrogen content of apple leaves and jujube leaves is an important index to judge the growth and development of apple trees and jujube trees to a certain extent. The prediction performance of the two samples was compared between different models for leaf nitrogen content, respectively. The near-infrared absorption spectra of 287 apple leaf samples and 192 jujube leaf samples were collected. After eliminating the outliers by Mahalanobis distance method, the remaining spectral data were processed by six different preprocessing methods. BP neural network (BP), random forest regression (RF), least partial squares (PLS), K-Nearest Neighbor (KNN), and support vector regression (SVR) were compared to establish prediction models of nitrogen content in apple leaves and jujube leaves. The results showed that the determination coefficient (R2), root mean square error (RMSE) and residual prediction deviation (RPD) of the models established by different combined pretreatment methods were compared among the five methods. Compared with the performance of the other four models, the modeling method of SG + SD + CARS + RF was suitable for the prediction of nitrogen content in apple leaves, and its modeling set R2 was 0.85408, RMSE was 0.082188, and RPD was 2.5864. The validation set R2 is 0.75527, RMSE is 0.099028, RPD is 2.1956. The modeling method of FD + CARS + PLS was suitable for the prediction of nitrogen content in jujube leaves. The modeling set R2 was 0.7954, RMSE was 0.14558, and RPD was 2.4264; the validation set R2 is 0.81348, RMSE is 0.089217, and RPD is 2.4552.In the prediction modeling of apple leaf nitrogen content in the characteristic band, the model quality of RF was better than the other four prediction models. The model quality of PLS in predictive modeling of nitrogen content of jujube leaves in characteristic bands is superior to the other four predictive models, These results provide a reference for the use of near-infrared spectroscopy to determine whether apple trees and jujube trees are deficient in nutrients. [ABSTRACT FROM AUTHOR]

WC-Ti(C,N)-Cr3C2-Co ultrafine-grained cemented carbides with different contents of C, N and Co binder phases were fabricated. Their microstructures and mechanical properties were examined, and the relationship between the existing form of Ti(C,N) and various conditions was mainly discussed. The hardness of the samples increased and their fracture toughness decreased with decreasing C content. The average T.R.S. peaked at 4.8 GPa on the low-C side. Their microstructures significantly changed when the N2 partial pressure changed. At a N2 partial pressure of 2.6 kPa, the microstructure became finer and the average T.R.S. was the highest. Meanwhile, at N2 partial pressures of 0 and 11.7 kPa, the microstructure became coarser and the average T.R.S. decreased. As the content of Co binder phase decreased, the number of WC/WC interfaces increased. The average T.R.S. was maximum at 16.4 vol% Co, and decreases with the Co content, but was higher than those of conventional cemented carbides. The existing form of Ti(C,N) changed depending on the N content. Herein, a N2 partial pressure of 2.6 kPa and low C contents were deemed optimal. [ABSTRACT FROM AUTHOR]

Scots pine (Pinus sylvestris L.) has higher early growth rates than Norway spruce (Picea abies (L.) H. Karst.). To help efforts to understand possible reasons for this difference and identify appropriate regeneration methods, we labeled seedlings with 15N in the nursery to probe nitrogen (N) uptake and retranslocation in Scots pine and Norway spruce seedlings at both harsh and fertile sites in southern and northern Sweden. For this, 15N dilution was measured during the first two years after planting. We also examined the potential N2-fixation capacity in fine roots after 5–7 growing seasons. Use of 15N-labeled seedlings enabled clear discernment of contributions of uptake of new N and retranslocation of old N to new foliage. Scots pine seedlings had higher proportions of N derived from uptake (Ndfu) than Norway spruce seedlings, and higher growth. Scots pine seedlings were less responsive to site preparation treatments compared to Norway spruce that has a greater need for appropriate silvicultural measures to grow well. After the second growing season, the contribution of N derived from retranslocation (Ndfr) to N in new foliage had diminished to 10–20% at all except the harshest site, where both species were more dependent on Ndfr. The potential N2-fixation capacity in fine roots of the two species differed, but in both cases the contribution of N2-fixation to N-acquisition was negligible. [ABSTRACT FROM AUTHOR]

The paper presents the experimental study of the influence of a 50 Hz extremely-low-frequency (ELF) electromagnetic field (EMF) on the growth of microalgae Chlorella vulgaris in a BG11 culture medium. Comparative experimental determinations carried out under reference conditions (microalgae growth without exposure to EMF) and with exposure to a homogeneous 50 Hz EMF of various intensities highlighted the fact that EMF has a major impact on both the growth speed and the nitrogen and phosphorus content of the obtained algal mass. Through spectrophotometry and gravimetric determinations, it was found that the lag time was reduced from approximately 8 h (reference) to approximately 6 h for EMF of 2 V/m, 4.5 h for EMF of 5 V/m, 3.2 h for EMF of 10 V/m, and 2.5 h for EMF of 15 V/m. In the stimulation with 15 V/m EMF, the maximum biomass growth rate was 2.75 times higher than the reference, leading to a 2-fold increase in the rate of exhaustion of nutrients, especially phosphorus, in the culture medium. The specific chemical analyses for N-NO3, total nitrogen TNb, and total phosphorus Pt highlighted that the N-NO3 content of the culture medium decreased by 58 mg/L/day at 15 V/m EMF compared to 43 mg/L for the reference. The Pt content decreased to 90% depletion after approximately 80 h for the reference culture medium, versus only 48 h of growth with exposure to 15 V/m ELF. The TNb content of the algal suspension in BG11 under the influence of 15 V/m EMF for 96 h of growth increased 14 times compared to the reference. This shows that nitrogen metabolization in the dispersed air was significantly stimulated. It was also found that the 50 Hz EMF also influences the nitrogen and phosphorus content of the increased algal mass. The results show the potential of EMF stimulation of Chlorella vulgaris growth, leading to an increased efficiency of algae growth reactors. [ABSTRACT FROM AUTHOR]

Rabbits, which are commonly raised as livestock in many rural areas of Asian countries, produce liquid waste called urine that can have negative environmental impacts. In order to tackle this issue, the development of technology is necessary to effectively process this waste into a form that can be utilized without causing harm to the environment. Urine contains valuable organic compounds that can be used as raw materials for the production of liquid organic fertilizer (LOF). The quality of this fertilizer is dependent on the availability of microorganism substrates and the duration of fermentation. The objective of this study is to investigate the influence of different substrates and fermentation periods on the properties of liquid organic fertilizer. The raw material used in this research is locally sourced rabbit urine. The experiments were conducted in a laboratory at the Faculty of Animal Science, Hasanuddin University, Indonesia. Three types of substrates were employed: bioactivator animal substrate (BAsb), bioactivator plant substrate (BPsb), and commercial microorganism (C-mic) as the control. Two different fermentation periods were tested: 2 weeks and 4 weeks. The data were analyzed using a completely randomized design (CRD) with factorial patterns. The results revealed that the type of bioactivator substrate had a significant impact (p < 0.05) on the N-organic, C/N ratio, P2O5, and K2O content. However, pH and C-organic showed no significant effect (p > 0.05). Additionally, fermentation time had a significant effect (p < 0.05) on C-organic, N-organic, and the C/N ratio, but pH did not have a significant effect (p > 0.05). Moreover, there was a significant interaction (p < 0.05) between the substrate type and fermentation time in the LOF-RU process. The production of N-organic content from local rabbit urine yielded promising results. For the LOF-RU production process with BAsb or BPsb, fermentation periods of up to 4 weeks can be applied. [ABSTRACT FROM AUTHOR]

Abstract The nitrogen content of apple leaves and jujube leaves is an important index to judge the growth and development of apple trees and jujube trees to a certain extent. The prediction performance of the two samples was compared between different models for leaf nitrogen content, respectively. The near-infrared absorption spectra of 287 apple leaf samples and 192 jujube leaf samples were collected. After eliminating the outliers by Mahalanobis distance method, the remaining spectral data were processed by six different preprocessing methods. BP neural network (BP), random forest regression (RF), least partial squares (PLS), K-Nearest Neighbor (KNN), and support vector regression (SVR) were compared to establish prediction models of nitrogen content in apple leaves and jujube leaves. The results showed that the determination coefficient (R2), root mean square error (RMSE) and residual prediction deviation (RPD) of the models established by different combined pretreatment methods were compared among the five methods. Compared with the performance of the other four models, the modeling method of SG + SD + CARS + RF was suitable for the prediction of nitrogen content in apple leaves, and its modeling set R2 was 0.85408, RMSE was 0.082188, and RPD was 2.5864. The validation set R2 is 0.75527, RMSE is 0.099028, RPD is 2.1956. The modeling method of FD + CARS + PLS was suitable for the prediction of nitrogen content in jujube leaves. The modeling set R2 was 0.7954, RMSE was 0.14558, and RPD was 2.4264; the validation set R2 is 0.81348, RMSE is 0.089217, and RPD is 2.4552.In the prediction modeling of apple leaf nitrogen content in the characteristic band, the model quality of RF was better than the other four prediction models. The model quality of PLS in predictive modeling of nitrogen content of jujube leaves in characteristic bands is superior to the other four predictive models, These results provide a reference for the use of near-infrared spectroscopy to determine whether apple trees and jujube trees are deficient in nutrients.

Rabbits, which are commonly raised as livestock in many rural areas of Asian countries, produce liquid waste called urine that can have negative environmental impacts. In order to tackle this issue, the development of technology is necessary to effectively process this waste into a form that can be utilized without causing harm to the environment. Urine contains valuable organic compounds that can be used as raw materials for the production of liquid organic fertilizer (LOF). The quality of this fertilizer is dependent on the availability of microorganism substrates and the duration of fermentation. The objective of this study is to investigate the influence of different substrates and fermentation periods on the properties of liquid organic fertilizer. The raw material used in this research is locally sourced rabbit urine. The experiments were conducted in a laboratory at the Faculty of Animal Science, Hasanuddin University, Indonesia. Three types of substrates were employed: bioactivator animal substrate (BAsb), bioactivator plant substrate (BPsb), and commercial microorganism (C-mic) as the control. Two different fermentation periods were tested: 2 weeks and 4 weeks. The data were analyzed using a completely randomized design (CRD) with factorial patterns. The results revealed that the type of bioactivator substrate had a significant impact (p 0.05). Additionally, fermentation time had a significant effect (p 0.05). Moreover, there was a significant interaction (p

Refractory high-chromium alloy VZh159 (Haynes 282) obtained by the method of selective laser melting (SLM) is studied. C-curves of the precipitation of particles of a topologically closed-packed (tcp) phase are plotted for the temperature range of heat treatment and operation. It is shown that the content of the tcp-particles of unfavorable morphology increases and the ductility of the synthesized material during synthesis in a protective nitrogen environment decreases with increase in the chromium content in the alloy. The intensification of the precipitation of the particles of the tcp-phase is associated with decrease in the solubility of chromium in the solid solution at high temperatures due to elevation of the nitrogen content in the alloy. To stabilize the alloying system, the chromium content in alloy VZh159 is reduced by 1 wt.% with respect to the upper and lower alloying limits as compared to the deformable counterpart, which makes it possible to prevent marked lowering of the ductility of VZh159 fabricatedby SLM. [ABSTRACT FROM AUTHOR]

The soybean (Glycine max. L. Merr) can satisfy a large portion of its requirement for nitrogen (N) by living in symbiosis with symbiotic bacteria. However, this source of N may be inadequate in varieties with high yield potential. To fully exploit this potential, soybeans should additionally utilize mineral forms of nitrogen present in the soil. The aim of this study was to determine the effect of varied nitrogen fertilizer application rates on the dry weight of the separated parts of soybean plants and the whole plant, including the number and weight of root nodules, the potential to reduce atmospheric nitrogen (N2), and the content and uptake of nitrogen. Four levels of pre-sowing nitrogen fertilizer supply were tested: 0, 60, 120, and 180 kg N·ha−1. Measurements of the tested parameters were taken during the flowering stage and the fully ripe stage. During the flowering stage, a reduction in the number of root nodules was observed following the application of 120 and 180 kg N·ha−1. In the fully ripe stage, each increase in nitrogen application caused a systematic decrease in the number of nodules on the roots. Increasing the level of nitrogen application therefore reduced the N2 fixation potential of soybeans, regardless of the developmental stage. The use of high doses of nitrogen in soybean cultivation did not increase seed yield or the weight of the entire plant. With high doses of nitrogen, the content and accumulation of nitrogen in soybean seeds and total mass did not increase. Therefore, the content and yield of crude protein did not increase. The main organ of nitrogen accumulation in the soybean flowering stage was the leaves (58.6–64.8% of total N uptake), however, in the fully ripe stage, it was the seeds (66.8–74.2% of total N uptake). [ABSTRACT FROM AUTHOR]

Decreasing antenna size is considered a potential option for improving photosynthesis and increasing yield potential. Reducing chlorophyll content has been employed as a strategy to decrease antenna size. One of the commonly mentioned advantages of this approach is its ability to enhance crop nitrogen use efficiency (NUE); however, there is limited field evidence supporting this claim. In this study, we utilized a rice mutant called p35s‐Ami‐YGL1, which exhibits lower chlorophyll content and smaller antenna size, to investigate the effects of modifying leaf chlorophyll content on tissue nitrogen content and NUE. Our results demonstrate that the nitrogen contents in various tissues, including seed tissue, increased on a weight basis in p35s‐Ami‐YGL1 mutants while exhibiting a decrease in C:N ratio. Simultaneously, we observed a reduction in tissue carbon content along with an increase in the levels of chlorophyll precursors such as Proto IX. Specifically, we observed an upregulation in the expression of genes associated with photosynthetic light reactions and chlorophyll metabolism, while there was no increase in the expression of genes involved in the CBB cycle and nitrogen metabolism. In addition, p35s‐Ami‐YGL1 experienced increased photodamage. These findings suggest that the alterations in the C:N ratio and nitrogen content in plants may be attributed to Proto IX‐mediated photodamage and chloroplast reverse transduction signaling. Besides, these results suggest that the observed increase in tissue nitrogen content in p35s‐Ami‐YGL1 does not reflect an increase in plant nitrogen absorption or use efficiency, rather it is a result of stunted carbon fixation capacity. [ABSTRACT FROM AUTHOR]

Cellulose nitrates (CNs)-blended composites based on celluloses of bacterial origin (bacterial cellulose (BC)) and plant origin (oat-hull cellulose (OHC)) were synthesized in this study for the first time. Novel CNs-blended composites made of bacterial and plant-based celluloses with different BC-to-OHC mass ratios of 70/30, 50/50, and 30/70 were developed and fully characterized, and two methods were employed to nitrate the initial BC and OHC, and the three cellulose blends: the first method involved the use of sulfuric–nitric mixed acids (MAs), while the second method utilized concentrated nitric acid in the presence of methylene chloride (NA + MC). The CNs obtained using these two nitration methods were found to differ between each other, most notably, in viscosity: the samples nitrated with NA + MC had an extremely high viscosity of 927 mPa·s through to the formation of an immobile transparent acetonogel. Irrespective of the nitration method, the CN from BC (CN BC) was found to exhibit a higher nitrogen content than the CN from OHC (CN OHC), 12.20–12.32% vs. 11.58–11.60%, respectively. For the starting BC itself, all the cellulose blends of the starting celluloses and their CNs were detected using the SEM technique to have a reticulate fiber nanostructure. The cellulose samples and their CNs were detected using the IR spectroscopy to have basic functional groups. TGA/DTA analyses of the starting cellulose samples and the CNs therefrom demonstrated that the synthesized CN samples were of high purity and had high specific heats of decomposition at 6.14–7.13 kJ/g, corroborating their energy density. The CN BC is an excellent component with in-demand energetic performance; in particular, it has a higher nitrogen content while having a stable nanostructure. The CN BC was discovered to have a positive impact on the stability, structure, and energetic characteristics of the composites. The presence of CN OHC can make CNs-blended composites cheaper. These new CNs-blended composites made of bacterial and plant celluloses are much-needed in advanced, high-performance energetic materials. [ABSTRACT FROM AUTHOR]

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Common bean (Phaseolus vulgaris L.) ranks among the most produced and consumed legume crops and contains essential macro- and micronutrients. Grain yield of the food crop is markedly decreased by poor management, especially a lack of additional essential nutrient elements through the application of fertilizers. In addition to the application of fertilizers, scholarly research and crop farmers have shown that the use of biofertilizer inoculants improves the yield of legume crops. The objective of this research study was to assess the effectiveness of peat-based Rhizobium tropici sp. UD5 on the growth, yield, and nitrogen concentration of common bean. The peat inoculant contained 6.5 × 109 viable cells/g. The experiment was conducted in two climatic zones, as described by the Koppen–Gieger climatic classification system. Treatments involved the peat-based inoculant Rhizobium tropici (T0 = 0 g without inoculation, T1 = 250 g of peat inoculant of strain UD5 for 50 kg seeds, T2 = 500 g of inoculant of strain UD5, and T3 = 200 g of comparative peat inoculant). The results indicated that common-bean-inoculated formulation of R. tropici sp. strain UD5 increased the following parameters compared to the controls: plant height (T1 = 18.22%, T2 = 20.41%, and T3 = 19.93% for bioclimatic zone 1; T1 = 16.78%, T2 = 20.71%, and T3 = 19.93% for bioclimatic zone 2), root length (T1 = 13.26%, T2 = 21.28%, and T3 = 19.38% for zone 1; T1 = 15.06%, T2 = 23.70%, and T3 = 19.20% for zone 2), number of nodules (T1 = 1162.57%, T2 = 1166.36%, and T3 = 1180.30% for zone 1; T1 = 1575%, T2 = 1616.5%, and T3 = 1608.25% for zone 2), size of nodules (T1 = 224.07%, T2 = 224.07%, and T3 = 208.33% for zone 1; T1 = 166.4%, T2 = 180%, and T3 = 140% for zone 2), and yield (T1 = 40.49%, T2 = 47.10%, and T3 = 45.45% for zone 1; T1 = 62.16%, T2 = 54.05%, and T3 = 58.55% for zone 2). R. tropici sp. UD5 peat inoculant formulation also increased the nitrogen concentration in leaves compared to the control (T1 = 3.75%, T2 = 1.12%, and T3 = 8.72%) in both bioclimatic zones. The findings of this study provide significant information on the positive effect of R. tropic UD5 strain peat inoculant application in the improvement of plant growth, development, and yield through the formation of nodules.

The effects of large granular slow-controlled release fertiliser prepared by a double coating of sulfur and sodium alginate on peanut growth, nitrogen fertiliser utilisation, and soil microbial community were investigated through peanut pot experiments, with a view to providing a theoretical and practical basis for the development of large granular slow-controlled release fertiliser. The results showed that the homemade large granular fertiliser could promote the root development of peanuts, and the root volume increased by 45.10% compared with the uncoated fertiliser at the fruiting stage. At the same time, the soil NH4+-N and NO3--N content were reduced at the seedling stage and increased at the fruiting stage to achieve the fertiliser's slow and controlled release effect. A significant contribution to the net photosynthetic rate was made for growth development and yield in the middle and late stages. Pod dry weight was significantly higher at the blooming stage than uncoated fertiliser, 4.8% higher at the fruiting stage, and 22.9% higher in nitrogen use efficiency (NUE). In terms of microbial bacterial communities, the large granular slow-release fertiliser promoted the diversity of the treated bacterial communities to some extent, with little difference in the relative abundance of soil bacterial communities. These results showed that a one-time application of homemade large granular slow-release fertiliser positively affected peanuts in terms of yield increase, promotion of nitrogen uptake and improved nitrogen utilisation under nitrogen application with urea equivalent, but the overall effect on soil microbial community was small.

Crop homogenization in conventional agriculture has been pervasive while ecology has shown positive effects of biodiversity on ecosystem functioning, that arise from complementarity/facilitation and sampling/selection effects. These effects are well documented for interspecific diversity in both natural ecosystems and agroecosystems but remain less documented at an intraspecific level, particularly for the rates of nutrient uptake by plants and nutrient losses from ecosystems. We conducted a field experiment with 88 experimental plots cultivated with 1, 2, 4 or 8 wheat varieties and 1, 2, 3 or 4 functional groups to assess the effects of the number of varietal and functional diversity of winter wheat on plant biomass production, plant nutrient contents (N, Ca, Cu, Fe, Mg, Mn, P, K, Na and Zn) and fertilizer N recovery in the plant-soil system using a 15N labeling method. We found both negative and positive effects of the number of varieties or number of functional groups on shoot Cu, Fe, Zn, Na and P contents, but no significant effects of intraspecific diversity on biomass production, N content and 15N recovery in the plant-soil system. Our results show differential responses to an increase of intraspecific diversity of wheat on the contents of several essential nutrients in plants and highlight the need to jointly analyze multiple nutrients. Our study also suggests that increasing intraspecific diversity had no overall negative effects on biomass production or N content. Using knowledge on variety functional traits to target specific complementarity mechanisms when designing variety mixtures could thus lead to a positive effect on nutrient absorption and biomass production.

Tree branches from forest tree harvesting for the timber industry are an important energy feedstock. Solid biofuel in the form of wood chips, produced from branches, is an excellent renewable energy source for generating heat and electricity. However, the properties of wood chips as a solid biofuel produced from forest tree branches can vary greatly depending on the species from which they have been produced. Therefore, this study aimed to assess the thermophysical properties and elemental composition of fresh branches harvested from nine tree species (pedunculate oak, silver birch, European ash, common aspen, grey alder, Norway maple, Scots pine, European larch and Norway spruce) over three consecutive years (2020–2022). The branches of the tree species most commonly found in Polish forests (Scots pine) were characterized by the highest heating value (an average of 20.74 GJ Mg−1 DM), the highest carbon content (an average of 55.03% DM), the lowest ash (an average of 0.60% DM) and nitrogen contents (an average of 0.32% DM), and low sulfur (an average of 0.017% DM) and chlorine contents (an average of 0.014% DM). A cluster analysis showed that the branches of all three coniferous tree species (Scots pine, Norway spruce and European larch) formed one common cluster, indicating similar properties. The branches of the European ash were characterized by the lowest wood moisture content (an average of 37.19% DM) and thus the highest lower heating value (an average of 10.50 GJ Mg−1). During the three years of the study, the chlorine and ash contents of the branches of the tree species under study exhibited the highest variability. [ABSTRACT FROM AUTHOR]

In this paper, hyperspectral imaging technology, combined with chemometrics methods, was used to detect the nitrogen content of soybean leaves, and to achieve the rapid, non-destructive and in situ detection of the nitrogen content in soybean leaves. Soybean leaves under different fertilization treatments were used as the research object, and the hyperspectral imaging data and the corresponding nitrogen content data of soybean leaves at different growth stages were obtained. Seven spectral preprocessing methods, such as Savitzky–Golay smoothing (SG), first derivative (1-Der), and direct orthogonal signal correction (DOSC), were used to establish the quantitative prediction models for soybean leaf nitrogen content, and the quantitative prediction models of different spectral preprocessing methods for soybean leaf nitrogen content were analyzed and compared. On this basis, successive projections algorithm (SPA), genetic algorithm (GA) and random frog (RF) were employed to select the characteristic wavelengths and compress the spectral data. The results showed the following: (1) The full-spectrum prediction model of soybean leaf nitrogen content based on DOSC pretreatment was the best. (2) The PLS model of soybean leaf nitrogen content based on the five characteristic wavelengths had the best prediction performance. (3) The spatial distribution map of soybean leaf nitrogen content was generated in a pixel manner using the extracted five characteristic wavelengths and the DOSC-RF-PLS model. The nitrogen content level of soybean leaves can be quantified in a simple way; this provides a foundation for rapid in situ non-destructive detection and the spatial distribution difference detection of soybean leaf nitrogen. (4) The overall results illustrated that hyperspectral imaging technology was a powerful tool for the spatial prediction of the nitrogen content in soybean leaves, which provided a new method for the spatial distribution of the soybean nutrient status and the dynamic monitoring of the growth status. [ABSTRACT FROM AUTHOR]

Legumes contribute substantially to global crop production and soil nitrogen fertility and play a crucial role in agriculture, agroforestry and the ecosystem due to their ability to fix the atmospheric nitrogen. This study investigated the growth and nodulation behavior of three prevalent leguminous weeds viz., Crotolaria micans, Calopogonium mucunoides and Aeschynomene indica in Mizoram. Seeds of the legume species were collected and pretreated and sown in polybags of 13 X 13 cm in March 2020. Observations on the plant height and biomass; the number and biomass of the nodules on different categories of the roots were carried out three months after sowing. The total number of nodules/plants was in the order A. indica (488.30) > C. micans (21.00) > C. mucunoides (12.10). The shape of their nodules was globose, fan shaped and globose with white streak. Nodule biomass and nitrogen content varied across species, with C. micans demonstrating superior nitrogen content despite fewer numbers of nodules. These findings shed light on leguminous weed growth and nodulation behaviors, facilitating sustainable agricultural practices. [ABSTRACT FROM AUTHOR]

Peatland restoration usually aims at restarting the peatlands' function to store carbon within peat. The soil properties of the near-surface peat can give a first understanding of this process. Therefore, we sampled pH value, total organic carbon content (TOC), total nitrogen content (TN), C/N ratio as well as dry bulk density (BD), and describe the structure of near-surface peats in six restored fens in North-East Germany before (2002-2004) and after (2019-2021) restoration. Before restoration, the study sites showed peat degradation to various extents in their near-surface peats. pH values remained relatively stable over time. Comparing the degraded peat horizons, TOC increased significantly in four study sites, ranging from 35.7% to 47.8% in 2002-2004 and from 42.5% to 54.0% in 2019-2021. TN varied from 1.5% to 3.5% in 2002-2004 and from 1.8% to 3.2% in 2019-2021, but changes were only significant in one site, showing a slight decrease. In three sites, the increase in C/N ratio was significant, indicating lower nutrient availability. BD ranged from 0.08 to 0.48 g/cm3 in 2002-2004 and from 0.10 to 0.16 g/cm³ in 2019-2021, decreasing significantly in four sites. The structure of the degraded peat horizons changed after restoration to a more homogenous, sludge mass with larger re-aggregates. In three sites, new peat moss peat layers above the degraded soil horizon were present in 2019-2021, with a mean thickness of 6.8 to 36.1 cm. The structure was comparable to typical, slightly decomposed peat moss peat. Our findings suggest that within about 17 years after fen restoration, and thereby a water table rise close to surface, TOC of the near-surface peats increased to values that are typical for undisturbed peatlands. This indicates that restoration can lead to the re-establishment of peatlands as potential carbon sinks, with TOC within the near-surface peat as one key factor in this process. Further, we assume that the decrease in nutrient availability, decrease of BD, and new, undisturbed peat layers can favor the establishment of mire-specific biodiversity and support ecosystem services similar to near-natural mires. [ABSTRACT FROM AUTHOR]

Using swine manure biochar and biogas slurry in agriculture proves to be an effective strategy for soil improvement and fertilization. In this study, a pot trial on the growth of lotus root was conducted to investigate the persistent effects of applying 350°C swine manure biochar (1% and 2%) and biogas slurry (50% and 100%) on soil nitrogen nutrient and lotus root quality. The results showed that compared to chemical fertilizer alone (A0B0), swine manure biochar significantly increased soil nitrogen content after one year of application. The contents of total nitrogen (TN), alkali-hydrolyzed nitrogen (AHN), ammonium nitrogen (NH4 + −N) increased by 17.96% to 20.73%, 14.05% to 64.71%, 17.76% to 48.68% and 2.22% to 8.47%, respectively, during the rooting period. When swine manure biochar was present, the application of biogas slurry further elevated soil nitrogen content. The co-application of swine manure biochar and biogas slurry significantly increased soil nitrogen content, and the 100% nitrogen replacement with biogas slurry combined with 2% swine manure biochar (A2B2) treatment exhibited the most significant enhancement effect during whole plant growth periods. Soil enzyme activities, including soil protease (NPT), leucine aminopeptidase (LAP), b-glucosidase (β-GC) and dehydrogenase (DHA), showed a tendency to increase and then decrease with the prolongation of lotus root fertility period, reaching the maximum value during the rooting period. Compared to A0B0, the treatment with 2% swine manure biochar had the most significant effect on enzyme activities and increased the lotus root’s protein, soluble sugar, and starch contents. Nitrate content decreased with the application of 2% swine manure biochar as the amount of biogas slurry increased. In conclusion, swine manure biochar effectively improved soil nitrogen content, enzyme activity, and lotus root quality. Even after one year of application, 2% swine manure biochar had the best enhancement effect. [ABSTRACT FROM AUTHOR]3− −N) increased by 17.96% to 20.73%, 14.05% to 64.71%, 17.76% to 48.68% and 2.22% to 8.47%, respectively, during the rooting period. When swine manure biochar was present, the application of biogas slurry further elevated soil nitrogen content. The co-application of swine manure biochar and biogas slurry significantly increased soil nitrogen content, and the 100% nitrogen replacement with biogas slurry combined with 2% swine manure biochar (A2B2) treatment exhibited the most significant enhancement effect during whole plant growth periods. Soil enzyme activities, including soil protease (NPT), leucine aminopeptidase (LAP), b-glucosidase (β-GC) and dehydrogenase (DHA), showed a tendency to increase and then decrease with the prolongation of lotus root fertility period, reaching the maximum value during the rooting period. Compared to A0B0, the treatment with 2% swine manure biochar had the most significant effect on enzyme activities and increased the lotus root’s protein, soluble sugar, and starch contents. Nitrate content decreased with the application of 2% swine manure biochar as the amount of biogas slurry increased. In conclusion, swine manure biochar effectively improved soil nitrogen content, enzyme activity, and lotus root quality. Even after one year of application, 2% swine manure biochar had the best enhancement effect. [ABSTRACT FROM AUTHOR]

Solid biofuels, including straw as production residue, are still the largest energy feedstock in the structure of primary energy production from renewable energy sources. However, the properties of straw as a solid biofuel can vary depending on the species from which it was produced and the harvest period and year. Therefore, this study aimed to assess the thermophysical properties and elemental composition of six types of straw (rye, oat, triticale, wheat, corn, and rapeseed straw) obtained over three consecutive years (2020, 2021, 2022). Rye straw had the lowest moisture (mean: 10.55%), ash (mean: 2.71% DM), nitrogen (mean: 0.54% DM) and chlorine (mean: 0.046% DM) contents and the highest carbon content (mean: 47.93% DM), a higher heating value—HHV (mean: 19.03 GJ Mg−1 DM) and a lower heating value—LHV (mean: 15.71 GJ Mg−1). Triticale straw had similar properties, classifying it into the same cluster as rye straw. Corn straw had a remarkably high moisture content (mean: 48.91%), low LHV and high chlorine content. Rapeseed straw contained high levels of Cl, S, N and ash, and they were 643%, 481%, 104% and 169% higher, respectively, than those in rye straw. The sulfur, chlorine and moisture contents of the six straw types under study were highly variable during the three years of the study. Knowledge of the properties of different types of straw as energy feedstocks facilitates the logistics and organization of the supply of bioenergy installations. However, further research is needed, especially studies assessing the energy intensity and logistical costs of different types of straw used for energy purposes. [ABSTRACT FROM AUTHOR]

Nitrogen loss is an unavoidable problem during organic waste composting, while exogenous microbial inoculation is a promising strategy for reducing nitrogen loss and improving compost quality. This study was designed to probe available nitrogen levels, bacterial community composition, and the levels of nitrogen functional genes present when composting cattle manure with or without the addition of Bacillus coagulans X3. Bacterial supplementation was associated with the prolongation of the thermophilic stage and improved maturity of the resultant compost. At the maturity stage, samples to which B. coagulans X3 had been added exhibited significant increases in ammonium nitrogen, nitrate nitrogen, and total nitrogen levels. The dominant bacterial phyla observed in these composting samples were Firmicutes, Proteobacteria, Bacteroidetes, Actinobacteriota, and Chloroflexi. B. coagulans X3 addition resulted in significant increases in relative Firmicutes abundance during the thermophilic and cooling stages while also increasing amoA and nosZ gene abundance and reducing nirS gene levels over the course of composting. Together, these data suggest that B. coagulans X3 supplementation provides an effective means of enhancing nitrogen content in the context of cattle manure composting through the regulation of nitrification and denitrification activity. [ABSTRACT FROM AUTHOR]

Common bean (Phaseolus vulgaris L.) ranks among the most produced and consumed legume crops and contains essential macro- and micronutrients. Grain yield of the food crop is markedly decreased by poor management, especially a lack of additional essential nutrient elements through the application of fertilizers. In addition to the application of fertilizers, scholarly research and crop farmers have shown that the use of biofertilizer inoculants improves the yield of legume crops. The objective of this research study was to assess the effectiveness of peat-based Rhizobium tropici sp. UD5 on the growth, yield, and nitrogen concentration of common bean. The peat inoculant contained 6.5 × 109 viable cells/g. The experiment was conducted in two climatic zones, as described by the Koppen–Gieger climatic classification system. Treatments involved the peat-based inoculant Rhizobium tropici (T0 = 0 g without inoculation, T1 = 250 g of peat inoculant of strain UD5 for 50 kg seeds, T2 = 500 g of inoculant of strain UD5, and T3 = 200 g of comparative peat inoculant). The results indicated that common-bean-inoculated formulation of R. tropici sp. strain UD5 increased the following parameters compared to the controls: plant height (T1 = 18.22%, T2 = 20.41%, and T3 = 19.93% for bioclimatic zone 1; T1 = 16.78%, T2 = 20.71%, and T3 = 19.93% for bioclimatic zone 2), root length (T1 = 13.26%, T2 = 21.28%, and T3 = 19.38% for zone 1; T1 = 15.06%, T2 = 23.70%, and T3 = 19.20% for zone 2), number of nodules (T1 = 1162.57%, T2 = 1166.36%, and T3 = 1180.30% for zone 1; T1 = 1575%, T2 = 1616.5%, and T3 = 1608.25% for zone 2), size of nodules (T1 = 224.07%, T2 = 224.07%, and T3 = 208.33% for zone 1; T1 = 166.4%, T2 = 180%, and T3 = 140% for zone 2), and yield (T1 = 40.49%, T2 = 47.10%, and T3 = 45.45% for zone 1; T1 = 62.16%, T2 = 54.05%, and T3 = 58.55% for zone 2). R. tropici sp. UD5 peat inoculant formulation also increased the nitrogen concentration in leaves compared to the control (T1 = 3.75%, T2 = 1.12%, and T3 = 8.72%) in both bioclimatic zones. The findings of this study provide significant information on the positive effect of R. tropic UD5 strain peat inoculant application in the improvement of plant growth, development, and yield through the formation of nodules. [ABSTRACT FROM AUTHOR]

Despite advancements in using multi-temporal satellite data to assess long-term changes in Northeast India's tea plantations, a research gap exists in understanding the intricate interplay between biophysical and biochemical characteristics. Further exploration is crucial for precise, sustainable monitoring and management. In this study, satellite-derived vegetation indices and near-proximal sensor data were deployed to deduce various physico-chemical characteristics and to evaluate the health conditions of tea plantations in northeast India. The districts, such as Sonitpur, Jorhat, Sibsagar, Dibrugarh, and Tinsukia in Assam were selected, which are the major contributors to the tea industry in India. The Sentinel-2A (2022) data was processed in the Google Earth Engine (GEE) cloud platform and utilized for analyzing tea plantations biochemical and biophysical properties. Leaf chlorophyll (Cab) and nitrogen contents are determined using the Normalized Area Over Reflectance Curve (NAOC) index and flavanol contents, respectively. Biophysical and biochemical parameters of the tea assessed during the spring season (March–April) 2022 revealed that tea plantations located in Tinsukia and Dibrugarh were much healthier than the other districts in Assam which are evident from satellite-derived Enhanced Vegetation Index (EVI), Modified Soil Adjusted Vegetation Index (MSAVI), Leaf Area Index (LAI), and Fraction of Absorbed Photosynthetically Active Radiation (fPAR), including the Cab and nitrogen contents. The Cab of healthy tea plants varied from 25 to 35 µg/cm2. Pearson correlation among satellite-derived Cab and nitrogen with field measurements showed R2 of 0.61–0.62 (p-value < 0.001). This study offered vital information about land alternations and tea health conditions, which can be crucial for conservation, monitoring, and management practices. [ABSTRACT FROM AUTHOR]

• Wheat varietal and functional diversity were manipulated in the field. • Increasing intraspecific diversity of wheat did not influence biomass production. • Increasing intraspecific diversity did not alter 15N recovery by plants and soil. • Increasing intraspecific diversity affected plant Cu, Fe, Zn, Na and P contents. Crop homogenization in conventional agriculture has been pervasive while ecology has shown positive effects of biodiversity on ecosystem functioning, that arise from complementarity/facilitation and sampling/selection effects. These effects are well documented for interspecific diversity in both natural ecosystems and agroecosystems but remain less documented at an intraspecific level, particularly for the rates of nutrient uptake by plants and nutrient losses from ecosystems. We conducted a field experiment with 88 experimental plots cultivated with 1, 2, 4 or 8 wheat varieties and 1, 2, 3 or 4 functional groups to assess the effects of the number of varietal and functional diversity of winter wheat on plant biomass production, plant nutrient contents (N, Ca, Cu, Fe, Mg, Mn, P, K, Na and Zn) and fertilizer N recovery in the plant-soil system using a 15N labeling method. We found both negative and positive effects of the number of varieties or number of functional groups on shoot Cu, Fe, Zn, Na and P contents, but no significant effects of intraspecific diversity on biomass production, N content and 15N recovery in the plant-soil system. Our results show differential responses to an increase of intraspecific diversity of wheat on the contents of several essential nutrients in plants and highlight the need to jointly analyze multiple nutrients. Our study also suggests that increasing intraspecific diversity had no overall negative effects on biomass production or N content. Using knowledge on variety functional traits to target specific complementarity mechanisms when designing variety mixtures could thus lead to a positive effect on nutrient absorption and biomass production. [Display omitted] [ABSTRACT FROM AUTHOR]

The rapid and accurate estimation of the nitrogen content of fruit trees helps to achieve a precise management of orchards. Hyperspectral data were collected from leaves of apple tree canopies at different fertility stages through field experiments to investigate the relationship between the nitrogen content and spectral reflectance of apple canopy leaves. Two different preprocessing methods, Savitzky–Golay (SG) smoothing and multiple scattering correction (MSC), were used to extract the feature bands by combining the successive projection method (SPA) and the competitive adaptive weighting algorithm–partial least squares (CARS-PLS). The reflectance values of the feature bands screened via these two methods were used as inputs to construct the multi-factor inversion models of apple canopy leaf nitrogen content based on the long- and short-term memory (LSTM) network, the support vector regression (SVR) and the Least Squares Support Vector Machine Regression (RIME-LSSVM). The study compared the ability of three algorithmic models to estimate leaf nitrogen content, and the results showed that the model constructed with the reflectance values of the characteristic bands screened by the CARS-PLS algorithm as inputs was more effective in predicting the nitrogen content of leaves. Furthermore, the accuracy of the model constructed using RIME-LSSVM was significantly higher than that of the model constructed using the long- and short-term memory network and support vector regression, in which the coefficient of determination of the test set (R-squared) is 0.964 and the root-mean-squared error (RMSE) is 0.052. Finally, the CARS-PLS algorithm combined with the RIME-LSSVM model has a higher prediction accuracy. The study demonstrated the feasibility and reliability of hyperspectral techniques for the estimation of nitrogen content of apple leaves in the Aksu region. [ABSTRACT FROM AUTHOR]

Abstract Decreasing antenna size is considered a potential option for improving photosynthesis and increasing yield potential. Reducing chlorophyll content has been employed as a strategy to decrease antenna size. One of the commonly mentioned advantages of this approach is its ability to enhance crop nitrogen use efficiency (NUE); however, there is limited field evidence supporting this claim. In this study, we utilized a rice mutant called p35s‐Ami‐YGL1, which exhibits lower chlorophyll content and smaller antenna size, to investigate the effects of modifying leaf chlorophyll content on tissue nitrogen content and NUE. Our results demonstrate that the nitrogen contents in various tissues, including seed tissue, increased on a weight basis in p35s‐Ami‐YGL1 mutants while exhibiting a decrease in C:N ratio. Simultaneously, we observed a reduction in tissue carbon content along with an increase in the levels of chlorophyll precursors such as Proto IX. Specifically, we observed an upregulation in the expression of genes associated with photosynthetic light reactions and chlorophyll metabolism, while there was no increase in the expression of genes involved in the CBB cycle and nitrogen metabolism. In addition, p35s‐Ami‐YGL1 experienced increased photodamage. These findings suggest that the alterations in the C:N ratio and nitrogen content in plants may be attributed to Proto IX‐mediated photodamage and chloroplast reverse transduction signaling. Besides, these results suggest that the observed increase in tissue nitrogen content in p35s‐Ami‐YGL1 does not reflect an increase in plant nitrogen absorption or use efficiency, rather it is a result of stunted carbon fixation capacity.

Common broom Cytisus scoparius (L.) Link is a native shrub, common both in Europe and Poland and in many other areas of the world, it is considered an invasive plant. e size of the organs of generative reproduction and the factors determining it are still poorly understood. The study of the size of broom flowers, fruits, seeds and leaves was carried out on 16 plots in western Poland. Habitats were described using Ellenberg’s index values, which allowed us to divide the study into two types: warm, rich in nitrogen, and moister with higher pH. It has been shown that a significant part of the variability in the size of flowers and their elements is conditioned by inter-individual differences. Some features (wings and keel area, number of seeds, or nitrogen content in stems) are also dependent on the type of habitat. Probably the key factor influencing the size of generative organs and the number of seeds is the availability of water in the environment. In more moist habitats and with a higher pH, the organs of generative reproduction are larger, and the nitrogen content is lower. The size of individual elements of the perianth is significantly correlated with each other, and the number of seeds depends on the size of the keel. Depending on environmental factors, the size of the generative organs may affect the efficiency of pollination, which in turn determines the size and number of seeds. The ability of C. scoparius to adapt to various edaphic conditions, the ability to establish symbiosis with atmospheric nitrogen-fixing bacteria, and the production of size-diverse flowers that can be pollinated by insects of various sizes determine its invasive success.

Cotton is an economically valuable crop worldwide, and accurate and rapid leaf moisture content, nitrogen content, and soil plant analysis development (SPAD) value estimations are crucial for cotton growth. In this study, high-resolution spectral data were collected for the Tahe 2 cotton variety in Alar City, Xinjiang. The raw spectra were preprocessed using four methods: first derivative, standard normal variate transformation, second derivative, and multiplicative scatter correction. Wavelet coefficients at multiple scales were generated from the raw spectra using a continuous wavelet transform (CWT) and CWT with first derivative (CWT-FD). A quantitative detection model combining CWT and CWT-FD with successive projection algorithm – partial least squares (SPA-PLS) was developed to estimate the leaf moisture content, nitrogen content, and SPAD values. The performances of the different scales and methods for estimating these parameters were compared. Six stratification methods were employed to determine the optimal modelling results and decomposition scales for the parameters under various stratification schemes. The results demonstrated that the CWT and CWT-FD methods significantly improved the accuracy of estimating cotton canopy spectral characteristics related to the parameters, surpassing that of conventional spectral processing methods. The mexh, db5, and db5 wavelet basis functions, along with scale 3, were identified as the optimal modelling choices for moisture content, nitrogen content, and SPAD values throughout the cotton plant growth period. Among the six vertical stratification structures of cotton, the CWT and CWT-FD methods, along with the three wavelet basis functions, achieved the best results for the three parameters in the upper layer. The optimal relative percent deviation values for the three parameters of typical leaves ranged from 1.603 to 2.016, indicating satisfactory modelling performance. These findings provide a theoretical foundation for accurately estimating leaf moisture content, nitrogen content, and SPAD values using spectral technology, enabling the simultaneous extraction and monitoring of multiple physiological indicators. [ABSTRACT FROM AUTHOR]

Plant biomass is still the main raw material in the production of energy from renewable sources. Virginia fanpetals may be an alternative and complementary source of solid biomass to that obtained from forests and the wood industry. In this respect, it is important to assess the variability of the qualitative characteristics of Sida biomass as a solid biofuel over a long period of use of a plantation of this species. Three types of propagating material were used to establish the plantation: seeds, root cuttings (rhizomes), and seedlings, at two sowing/planting densities. The quality of the biomass, obtained during 14 consecutive years of harvest, was tested, including the moisture content, ash content, higher heating value (HHV), lower heating value (LHV), and the carbon, hydrogen, sulfur, and nitrogen content. It was found that both thermophysical properties and elemental composition were mostly determined by the years of vegetation. An important role in this respect was played by the juvenile period of the plants' development. The biomass obtained after 1 year of vegetation contained a larger concentration of ash, nitrogen, and sulfur and less carbon and hydrogen, which reduced its energy value. The results confirm the possibility of obtaining biomass with low moisture, which favorably places it from an energy point of view. [ABSTRACT FROM AUTHOR]

Different from the basic chemistry experiment course in the lower grades of the university, the higher grades offer self-designed experiments, focusing on independent thinking and active exploration. Taking the "determination of N content in TiCN-based alloys" as an example, this paper introduces the whole process of selfdesigned experiments, including the digestion of solid samples, the extraction of substances to be measured, analysis and testing, data processing and evaluation, and introduces theoretical knowledge into practical problems, and uses experimental methods to deeply integrate the two, improving students' ability to judge, solve problems and comprehensive quality. [ABSTRACT FROM AUTHOR]

The study aimed to compare the effect of urea fatty fraction (UFF) and Pulrea® (urea fertilizer) on plant yield and selected plant and soil parameters determined after the plants were harvested. UFF is a by-product of essential unsaturated fatty acids (UFAs) extraction from fish oil using urea, and Pulrea® is a commercial urea fertilizer. Both products were applied to the soil and the leaves (foliar application). The effect of Pulrea® on plant yield was generally stronger than that of UFF but depended on soil properties and plant species. Both fertilizers, but especially UFF, increased the total N content in the plant and effected nitrate accumulation. The plants used 45–90% of fertilizer nitrogen, with the plants generally using more N from Pulrea® than from UFF. Higher nitrogen production efficiency was achieved using Pulrea® than UFF and when plants were cultivated on medium soil than on light soil. Fertilizers increased the acidity and electrolytic conductivity of both soils but did not induce soil salinization. They increased the content of mineral nitrogen forms in soils, which was generally the case more in soil with Pulrea® application than with UFF application. As a rule, the soil dehydrogenases activity did not change significantly or even decrease after fertilizer application. It was visibly higher in medium soil and after foliar Pulrea® application than after foliar UFF application. This may be due to the content of accompanying substances in UFF that affect nitrogen absorption from this fertilizer. Based on the results, it cannot be clearly stated that one of the tested fertilizers had a better effect on the studied parameters. Generally, the less favorable effects of UFF compared to Pulrea® may indicate the necessity of removing from UFF the accompanying substances that may adversely affect plants and soil microorganisms. This aspect needs to be investigated under controlled conditions in field experiments. [ABSTRACT FROM AUTHOR]

Existing maize production is grappling with the hurdles of not applying nitrogen fertilizer accurately due to subpar detection accuracy and responsiveness. This situation presents a significant challenge, as it has the potential to impact the optimal yield of maize and ultimately, the profit margins associated with its cultivation. In this study, an automatic modeling prediction method for nitrogen content in maize leaves was proposed based on machine vision and convolutional neural network. We developed a program designed to streamline the image preprocessing workflow. This program can process multiple images in batches, automatically carrying out the necessary preprocessing steps. Additionally, it integrates an automated training and modeling system that correlates the images with nitrogen content values. The primary objective of this program is to enhance the accuracy of the models by leveraging a larger dataset of image samples. Secondly, the fully connected layer of the convolutional neural network was reconstructed to transform the optimization goal from classification based on 0–1 tags into regression prediction, so that the model can output numerical values of nitrogen content. Furthermore, the prediction model of nitrogen content in maize leaves was gained by training many samples, and samples were collected in three key additional fertilizing stages throughout the growth period of maize (i.e., jointing stage, bell mouth stage, and tasseling stage). In addition, the proposed method was compared with the spectral detection method under full-wave band and characteristic wavelengths. It was verified that our machine vision and CNN (Convolutional Neural Network)-based method offers a high prediction accuracy rate that is not only consistently better—by approximately 5% to 45%—than spectral detection approaches but also features the benefits of easy operation and low cost. This technology can significantly contribute to the implementation of more precise fertilization practices in maize production, leading to potential yield optimization and increased profitability. [ABSTRACT FROM AUTHOR]

Leaf nitrogen content is closely related to leaf photosynthesis and the nutritional status of winter wheat plants, which directly affects the plant growth and development. While the stem nitrogen content is closely related to the proportion and content of cellulose, hemicellulose and lignin in stems, which directly affects stem quality and plant lodging resistance. However, it is still lacking on the direct estimation of stem N content in winter wheat. It is very necessary to evaluate the stalk quality and predict lodging from the perspective of stem nitrogen content. In this study, a 2-year field experiment was conducted to accurately estimate the nitrogen content in different plant organs (leaves and stems) of winter wheat. Winter wheat canopy spectral reflectance, leaf and stem nitrogen content, and leaf SPAD (Soil and Plant Analyzer Development) values were obtained at four growth stages (jointing, heading, anthesis and filling) and three nitrogen application levels (N1, N2 and N3). A systematic analysis was made to determine the sensitivity of hyperspectral vegetation indices to leaf and stem nitrogen contents at different growth stages and nitrogen application levels. Five commonly-used machine learning algorithms were used to estimate the leaf and stem nitrogen contents of winter wheat, including random forest regression (RFR), support vector regression (SVR), partial least squares regression (SVR), partial least squares regression (PLSR), Gaussian process regression (GPR) and deep neural networks (DNN). The hyperspectral vegetation indices only or combined with SPAD were used as the inputs to construct the nitrogen estimation models for leaves and stems. The results showed that the sensitivity of hyperspectral vegetation indices to the nitrogen content in leaves and stems was influenced by the growth stage and nitrogen application level. In the filling stage, the best vegetation index DCNI (Double-peak canopy nitrogen index) shared the highest sensitivity to leaf nitrogen content, where the determination coefficient R² was 0.866. The sensitivity to stem nitrogen content was the highest at the heading stage, and the R² between the best vegetation index NPQI (Normalized phaeophytinization index) and nitrogen content was 0.677. The sensitivity of the spectral vegetation index to the stem nitrogen content increased with the increasing nitrogen application level. The machine learning combined with the SPAD value and vegetation indices was improved the estimation accuracy of the nitrogen content, compared with only the vegetation index. In leaf nitrogen content, the estimation accuracy increased by 1%-7% under different growth stages and nitrogen application levels. The normalized root mean square error (NRMSE) reduced from 0.254 to 0.214 during the whole growth stage. In a single growth period, the NRMSE reduced from 0.201 to 0.128 at the heading stage, indicating the most increase. In the stem nitrogen content, the NRMSE reduced from 0.443 to 0.400 during the whole growth stage. There was the most increase during the heading stage with the values ranging from 0.323 to 0.268. In the whole growth period, the DNN model combined with the SPAD value was achieved the best accuracy to estimate the nitrogen content of leaves (R² =0.782 and NRMSE=0.214) and stems (R² =0.802 and NRMSE=0.400). The combination of the SPAD value and spectral vegetation index can be expected to improve the accuracy of the nitrogen content in the leaves and stems of winter wheat at different growth stages and nitrogen application levels [ABSTRACT FROM AUTHOR]

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Forest dendromass is still the major raw material in the production of solid biofuels, which are still the most important feedstock in the structure of primary energy production from renewable energy sources. Because of the high species and type diversity of production residues generated at wood processing sites, as well as at logging sites, the quality of commercial solid biomass produced there has to be evaluated. The aim of this study was to assess the thermophysical characteristics and the elemental composition of ten types of commercial solid biofuels (pinewood sawdust; energy chips I, II, and III; veneer sheets; shavings; birch bark; pine bark; pulp chips; and veneer chips), depending on their acquisition time (August, October, December, February, April, and June). Pulp chips had the significantly lowest moisture content (mean 26.92%), ash content (mean 0.39% DM—dry matter), nitrogen (N) content (mean 0.11% DM), and sulfur (S) content (mean 0.011% DM) and the highest carbon (C) content (mean 56.09% DM), hydrogen (H) content (6.40% DM), and lower heating value (LHV) (mean 13.61 GJ Mg−1). The three types of energy chips (I, II, and III) had good energy parameters, especially regarding their satisfactory LHV and ash, S, and N content. On the other hand, pine and birch bark had the worst ash, S, and N contents, although they had beneficial higher heating values (HHVs) and C contents. Solid biofuels acquired in summer (June) had the lowest levels of moisture and ash and the highest LHV. The highest moisture content and the lowest LHV were found in winter (December). [ABSTRACT FROM AUTHOR]

Contents of C, N, and P and N : P and C : N ratios in plant leaves have been studied in four alpine phytocenoses of the northwestern Caucasus to find out whether the species encountered in these areas differ in chemical composition from random samples from the local flora or not and determine the significance of the values of these traits for dominance, as well as their phylogenetic conservation. The content of nitrogen is lower in the leaves of plants from alpine heaths and Festuca varia grasslands and higher in the leaves of species of Geranium–Hedysarum meadows and alpine snowbeds than in a random sample. Dominants of productive Geranium–Hedysarum meadows contain more nitrogen than nondominant species, while the opposite dependence has been recorded for the other communities. The leaves of the components of all communities except alpine snowbeds contain less phosphorus than a random sample. Dominants of alpine heaths have less phosphorus and Geranium–Hedysarum meadows have more phosphorus in the leaves than nondominant species. The C : N ratio in the leaves is higher than the random value in species of alpine heaths and Festuca varia grasslands and lower in other communities. The dominant species have higher C : N ratios than the other species in all communities except Geranium–Hedysarum meadows. The N : P ratio is higher than the random value in species of all communities except Festuca varia grasslands. All the traits except the C : N ratio have a significant phylogenetic signal. [ABSTRACT FROM AUTHOR]

Leaf photosynthetic capacity (light-saturated net assimilation rate, AA) increases from bottom to top of plant canopies as the most prominent acclimation response to the conspicuous within-canopy gradients in light availability. Light-dependent variation in AA through plant canopies is associated with changes in key leaf structural (leaf dry mass per unit leaf area), chemical (nitrogen (N) content per area and dry mass, N partitioning between components of photosynthetic machinery), and physiological (stomatal and mesophyll conductance) traits, whereas the contribution of different traits to within-canopy AA gradients varies across sites, species, and plant functional types. Optimality models maximizing canopy carbon gain for a given total canopy N content predict that AA should be proportionally related to canopy light availability. However, comparison of model expectations with experimental data of within-canopy photosynthetic trait variations in representative plant functional types indicates that such proportionality is not observed in real canopies, and AA vs. canopy light relationships are curvilinear. The factors responsible for deviations from full optimality include stronger stomatal and mesophyll diffusion limitations at higher light, reflecting greater water limitations and more robust foliage in higher light. In addition, limits on efficient packing of photosynthetic machinery within leaf structural scaffolding, high costs of N redistribution among leaves, and limited plasticity of N partitioning among components of photosynthesis machinery constrain AA plasticity. Overall, this review highlights that the variation of AA through plant canopies reflects a complex interplay between adjustments of leaf structure and function to multiple environmental drivers, and that AA plasticity is limited by inherent constraints on and trade-offs between structural, chemical, and physiological traits. I conclude that models trying to simulate photosynthesis gradients in plant canopies should consider co-variations among environmental drivers, and the limitation of functional trait variation by physical constraints and include the key trade-offs between structural, chemical, and physiological leaf characteristics. [ABSTRACT FROM AUTHOR]

Peatland restoration usually aims at restarting the peatlands’ function to store carbon within peat. The soil properties of the near-surface peat can give a first understanding of this process. Therefore, we sampled pH value, total organic carbon content (TOC), total nitrogen content (TN), C/N ratio as well as dry bulk density (BD), and describe the structure of near-surface peats in six restored fens in North-East Germany before (2002–2004) and after (2019–2021) restoration. Before restoration, the study sites showed peat degradation to various extents in their near-surface peats. pH values remained relatively stable over time. Comparing the degraded peat horizons, TOC increased significantly in four study sites, ranging from 35.7% to 47.8% in 2002–2004 and from 42.5% to 54.0% in 2019–2021. TN varied from 1.5% to 3.5% in 2002–2004 and from 1.8% to 3.2% in 2019–2021, but changes were only significant in one site, showing a slight decrease. In three sites, the increase in C/N ratio was significant, indicating lower nutrient availability. BD ranged from 0.08 to 0.48 g/cm3 in 2002–2004 and from 0.10 to 0.16 g/cm3 in 2019–2021, decreasing significantly in four sites. The structure of the degraded peat horizons changed after restoration to a more homogenous, sludge mass with larger re-aggregates. In three sites, new peat moss peat layers above the degraded soil horizon were present in 2019–2021, with a mean thickness of 6.8 to 36.1 cm. The structure was comparable to typical, slightly decomposed peat moss peat. Our findings suggest that within about 17 years after fen restoration, and thereby a water table rise close to surface, TOC of the near-surface peats increased to values that are typical for undisturbed peatlands. This indicates that restoration can lead to the re-establishment of peatlands as potential carbon sinks, with TOC within the near-surface peat as one key factor in this process. Further, we assume that the decrease in nutrient availability, decrease of BD, and new, undisturbed peat layers can favor the establishment of mire-specific biodiversity and support ecosystem services similar to near-natural mires.

The paper presents the experimental study of the influence of a 50 Hz extremely-low-frequency (ELF) electromagnetic field (EMF) on the growth of microalgae Chlorella vulgaris in a BG11 culture medium. Comparative experimental determinations carried out under reference conditions (microalgae growth without exposure to EMF) and with exposure to a homogeneous 50 Hz EMF of various intensities highlighted the fact that EMF has a major impact on both the growth speed and the nitrogen and phosphorus content of the obtained algal mass. Through spectrophotometry and gravimetric determinations, it was found that the lag time was reduced from approximately 8 h (reference) to approximately 6 h for EMF of 2 V/m, 4.5 h for EMF of 5 V/m, 3.2 h for EMF of 10 V/m, and 2.5 h for EMF of 15 V/m. In the stimulation with 15 V/m EMF, the maximum biomass growth rate was 2.75 times higher than the reference, leading to a 2-fold increase in the rate of exhaustion of nutrients, especially phosphorus, in the culture medium. The specific chemical analyses for N-NO3, total nitrogen TNb, and total phosphorus Pt highlighted that the N-NO3 content of the culture medium decreased by 58 mg/L/day at 15 V/m EMF compared to 43 mg/L for the reference. The Pt content decreased to 90% depletion after approximately 80 h for the reference culture medium, versus only 48 h of growth with exposure to 15 V/m ELF. The TNb content of the algal suspension in BG11 under the influence of 15 V/m EMF for 96 h of growth increased 14 times compared to the reference. This shows that nitrogen metabolization in the dispersed air was significantly stimulated. It was also found that the 50 Hz EMF also influences the nitrogen and phosphorus content of the increased algal mass. The results show the potential of EMF stimulation of Chlorella vulgaris growth, leading to an increased efficiency of algae growth reactors.

The soybean (Glycine max. L. Merr) can satisfy a large portion of its requirement for nitrogen (N) by living in symbiosis with symbiotic bacteria. However, this source of N may be inadequate in varieties with high yield potential. To fully exploit this potential, soybeans should additionally utilize mineral forms of nitrogen present in the soil. The aim of this study was to determine the effect of varied nitrogen fertilizer application rates on the dry weight of the separated parts of soybean plants and the whole plant, including the number and weight of root nodules, the potential to reduce atmospheric nitrogen (N2), and the content and uptake of nitrogen. Four levels of pre-sowing nitrogen fertilizer supply were tested: 0, 60, 120, and 180 kg N·ha−1. Measurements of the tested parameters were taken during the flowering stage and the fully ripe stage. During the flowering stage, a reduction in the number of root nodules was observed following the application of 120 and 180 kg N·ha−1. In the fully ripe stage, each increase in nitrogen application caused a systematic decrease in the number of nodules on the roots. Increasing the level of nitrogen application therefore reduced the N2 fixation potential of soybeans, regardless of the developmental stage. The use of high doses of nitrogen in soybean cultivation did not increase seed yield or the weight of the entire plant. With high doses of nitrogen, the content and accumulation of nitrogen in soybean seeds and total mass did not increase. Therefore, the content and yield of crude protein did not increase. The main organ of nitrogen accumulation in the soybean flowering stage was the leaves (58.6–64.8% of total N uptake), however, in the fully ripe stage, it was the seeds (66.8–74.2% of total N uptake).

Three peanut genotypes were cultivated under ambient and elevated CO2 conditions. Elevated CO2 treatment was associated with higher total phenolic content (TPC) values in the shoots and roots of all genotypes. Seeds showed lower levels of TPC compared to the other plant tissue, showing a decline in all three genotypes, and no differences between the CO2 treatments were observed. The Crude Protein (CP) content in seeds varied significantly among the genotypes, and elevated CO2 treatment was associated with mild increases (not significant) in CP of 4 and 6% in Holt and Alloway cultivars, respectively. It is worth mentioning that Kairi contained the highest CP content under elevated CO2 (29%). [ABSTRACT FROM AUTHOR]

Precision irrigation and fertilization in agriculture are vital for sustainable crop production, relying on accurate determination of the crop's nutritional status. However, there are challenges in optimizing traditional neural networks to achieve this accurately. This paper aims to propose a rapid identification method for crop water and nitrogen content using optimized neural networks. This method addresses the difficulty in optimizing the traditional backpropagation neural network (BPNN) structure. It uses 179 multi−spectral images of crops (such as maize) as samples for the neural network model. Particle swarm optimization (PSO) is applied to optimize the hidden layer nodes. Additionally, this paper proposes a double−hidden−layer network structure to improve the model's prediction accuracy. The proposed double−hidden−layer PSO−BPNN model showed a 9.87% improvement in prediction accuracy compared with the traditional BPNN model. The correlation coefficient R2 for predicted crop nitrogen and water content was 0.9045 and 0.8734, respectively. The experimental results demonstrate high training efficiency and accuracy. This method lays a strong foundation for developing precision irrigation and fertilization plans for modern agriculture and holds promising prospects. [ABSTRACT FROM AUTHOR]

Background and Objective: This experiment was performed to research the role of various tillage systems with application of nitrogen fertilizer and vermicompost on seed and oil yield of rapeseed (Brassica napus L.) and conjointly its result on nitrogen efficiency indices fully and low irrigation conditions. Materials and Methods:The experiment was performed as a split-split plot based on a randomized complete block design with three replications in the Alborz Research Station, Research Institute of Forests and Rangelands during two cropping seasons (2017-19). Tillage systems as the main plot at three levels including no-tillage, reduced tillage, and conventional tillage. The subplots included irrigation at two levels (normal irrigation and low irrigation) and fertilizer factor at four levels (no fertilizer, urea chemical fertilizer, vermicompost, urea fertilizer + vermicompost). Results: In the no-tillage system, oil yield decreased by 22% compared to reduced tillage and 21.5% compared to conventional tillage. Seed and oil yields in the conditions of combined application of vermicompost fertilizer were 18 and 17% higher than the control in normal irrigation conditions and 29 and 32% higher in low irrigation conditions, respectively. In all three tillage systems, the highest nitrogen use efficiency was observed, which in Compared to the application of vermicompost and urea, in non-tillage conditions 5 and 8.1%, in reduced tillage conditions 6.2 and 1.5%, and in conventional tillage conditions 5.5 and 1.7%, respectively, the nitrogen use efficiency was more. Conclusion: The results of this experiment showed that reduced tillage and replacement of urea fertilizer with vermicompost can increase canola seed and oil yields by reducing nitrogen wastage, increasing nitrogen content and also by modifying drought stress conditions. [ABSTRACT FROM AUTHOR]