Leaf Nitrogen Content Research Articles

Functional traits and performance of woody species on oil- affected soils of the Ecuadorian Amazon

Introduction: Plant functional traits are widely used to predict community productivity. However, they are rarely used to predict the performance (in terms of growth diameter, growth height, survival, and integral response index) of woody species planted in degraded soils. Objective: To evaluate the relationship between the functional traits and the performance of 25 woody species planted in disturbed soils affected by oil extraction activities in Ecuadorian Amazon. Methods: Eighteen permanent sampling plots were established and five 6-month-old seedlings of each 25 species were randomly planted in each plot (125 individuals per plot), at a distance of 4×4 m. Eight quantitative functional traits (leaf size, specific leaf area, leaf nitrogen concentration, leaf phosphorus concentration, leaf minimum unit, leaf dry matter content, stem specific density and leaf tensile strength) were determined for each species. Results: The woody species with high performance shows greater leaf size, specific leaf area and Stem Specific Density than those showing low performance. Leaf nitrogen concentration and stem specific density had a direct relationship with the integral response index. The leaf size, leaf phosphorus concentration, leaf dry matter content and leaf tensile strength sows a negative relationship with the integral response index. Conclusions: Our study showed that the performance of woody species o disturbed soils can be predicted satisfyingly by leaf and stem functional traits, presumably because these traits capture most of environmental and neighborhood conditions.

Performance evaluation of the ORYZA_V3 model for rice growth and organ nitrogen content

AbstractThe ORYZA version 3 (ORYZA_V3) model is commonly used for simulating paddy rice (Oryza sativa L.) growth. However, few studies have investigated the performance of the ORYZA_V3 model for predicting in‐season crop growth variables, especially for the nitrogen (N) translocation process among paddy rice organs in the whole growing season, that is, from sowing to harvest stages. This study examines the prediction accuracy of seven paddy rice growth variables based on one cropping season of field experiment. The results show that (1) the ORYZA_V3 model generates accurate prediction of paddy rice leaf area index, above‐ground biomass, and yield, where root mean square errors (RMSEs) are 0.98–1.11 ha/ha, 2360.5–3028.7 kg/ha, and 492.9–515.2 kg/ha, respectively, coefficient of determination (R2) ranges from 0.76 to 1.00, and index of agreement (D‐index) ranges from 0.50 to 0.98. (2) The prediction accuracy of paddy rice leaf and stem N contents is acceptable, where RMSE ranges from 0.0017 to 0.0041 kg/kg, R2 ranges from 0.82 to 0.96, and D‐index ranges from 0.93 to 0.98. (3) The ORYZA_V3 model cannot generate accurate prediction of rice root and panicle N contents, where RMSE ranges from 0.0007 to 0.0022 kg/kg, R2 ranges from 0.01 to 0.20, and D‐index ranges from 0.17 to 0.65. The structural uncertainty in the N translocation module may be a major reason for the unacceptable crop model prediction. This study demonstrated the substantial potential of the ORYZA_V3 model for simulating and understanding paddy rice growth and organ N translocation.

Influence of cultivation techniques on dry matter partitioning, nitrogen distribution pattern and yield of super hybrid rice Liangyoupeijiu

Liangyoupeijiu was grown under different crop cultivation techniques viz: conventional tillage and transplanting (CTTP), no tillage and transplanting (NTTP), conventional tillage and direct seeding (CTDS) and no- tillage and direct seeding (NTDS) during 2011 and 2012. Results showed that, CTTP had higher leaf dry weight than NTTP. Maximum leaf dry weight reduced in direct seeded than transplanted rice. Shoot dry weight reduced by 6% both in transplanted and direct seeded rice from heading to 12 days after heading (DAH) in both the years. No tillage and transplanting had higher export percentage of dry matter and transport percentage of dry matter among the cultivation techniques in both the years. At heading, leaf nitrogen concentration (%) and nitrogen uptake (g m-2) were higher in transplanted than direct seeded rice and significantly higher nitrogen uptake was observed under conventional tillage and transplanting in both the years. The physiological nitrogen use efficiency was higher in no-tillage than conventional tillage in both the years. Total nitrogen (kg ha-1) uptake was higher in conventional tillage than no tillage either in transplanted or in direct seeded rice and was higher under conventional tillage and transplanting among the cultivation techniques in both the years. Grain yield was closely associated with uptake of total nitrogen at heading. Although, direct seeded rice had more than 23% higher panicle number than transplanted rice but conventional tillage and transplanting produced higher grain yield due to higher uptake of nitrogen by grain at maturity and bigger sink size. Bangladesh Rice J. 26 (2): 51-62, 2022

Inter-Month Nutrients Dynamic and Plant Growth in Calamagrostis angustifolia Community and Soil after Different Burning Seasons

Presently, as human activity and climate warming gradually increase, straw burning leads to more accidental burning in neighbouring wetlands, which threatens wetland carbon stores. Plants are important carbon fixers in wetlands, converting carbon dioxide to biomass through photosynthesis and releasing carbon into the soil as plants die off. Nitrogen and phosphorus limitation in wetlands is a key factor affecting plant growth, and different burning seasons have different effects on mitigating this limitation. To further elucidate the effects of nitrogen and phosphorus distribution on wetland inter-month nutrient dynamics after different burning seasons, we selected a Calamagrostis angustifolia wetland in the Sanjiang Plain that was burned in spring and autumn, respectively, and conducted a monthly survey from May to September. We found that the leaf nitrogen content in September at spring burning sites was 3.59 ± 2.69 g/kg, which was significantly lower than that in July, while the difference at the unburned sites was only 0.60 ± 3.72 g/kg, and after the autumn burning, soil nitrogen and phosphorus contents remained higher than at the unburned sites in August, being 0.55 ± 1.74 g/kg and 0.06 ± 0.12 g/kg, respectively. Our results indicate that spring burning immediately increased the nitrogen and phosphorus contents in soil and plants but that these effects only lasted for a short time, until June. In comparison, autumn burning had a long-term effect on soil nitrogen and phosphorus levels and significantly increased the aboveground biomass. Thus, we recommend that conducting autumn burning before the commencement of agricultural burning not only reduces combustible accumulation to prevent fires but also promotes nitrogen and phosphorus cycling in wetlands, and the increase in plant biomass after autumn burning also enhances the carbon fixation capacity of the wetland.

Changes in Leaf Functional Traits Driven by Environmental Filtration in Different Monsoon Tropical Forest Types

Disturbances have created heterogeneous habitats for secondary and old-growth forests. Under the assumption that ecologically similar species have similar functional traits, numerous studies have attempted to use trait-based approaches to infer the abiotic and biotic factors that drive variations in community composition across different forests. However, the relative importance of these drivers in monsoon forests remains poorly understood. In this study, we randomly selected 86 plots and classified them into three forest types according to environmental factors: 1—secondary forests: secondary forest habitats at high elevation; 2—ecotone forests: general recovery and elevation; and 3—old growth forests: old growth at low elevations. We then compared the species and six leaf functional trait variations across the three forests and assessed their relationships with 15 environmental factors. The results showed that secondary and ecotone forests with a conservative strategy, exhibiting high dry matter content and leaf carbon content, tended to persist in stressful habitats, such as nutrient-poor soil, whereas old growth forests invested in trait values related to rapid resource acquisition with high specific leaf area, leaf nitrogen content, leaf phosphorous content, and leaf potassium content. Species with functional trait values between the secondary, ecotone, and old growth forests had clear signatures of their different strategies to persist in assemblages under distinct and opposite environmental filters. These plots were classified into three forest types according to environmental factors: (1) secondary forest at high elevation; (2) ecotone forests at general elevation; and (3) old growth forests at low elevation. Recovery time and elevation, followed by soil nutrients and light capture, were the most important factors shaping species and functional trait variations across forests. These results have demonstrated that environmental filters select plant species with distinct traits and ecological strategies. Acquisitive traits indicate higher competitive ability and faster resource acquisition for forest species that occur in areas with high soil fertility. Meanwhile, conservative traits promote the resistance of secondary species to environmental stressors in low soil fertility, suggesting that analyzing leaf functional-based trait variations to understand plant ecological strategies along an environmental gradient may improve understanding of forest dynamics in tropical monsoon forests.

Modifying the Growing Media and Bio Stimulants Supply for Healthy Gerbera (Gerbera jamesonii) Flowers

AbstractGerbera (Gerbera jamesonii) cv. Jaguar Yellow is an ornamental plant of the Asteraceae family. Ordinarily, farmers use expensive materials such as peat moss as a media substrate in gerbera production, in addition to application high nitrogen fertilizers. Therefore, the current study was designed to assess the yield and quality changes of gerbera flowers owing to utilizing environment-friendly inputs under unheated plastic greenhouse conditions for two seasons of 2017/18 and 2018/19. The experiments were laid out in a randomized complete block design with 3 replicates, each replicate involved 5 pots per treatment. For preparing the soil substrate mixtures, four substances were used which involved peat moss (P), sand (S), vermicompost (V), and compost (C). P + S, P + S + V and P + S + C were assembled whether with or without Azotobacter+Azospirillum as bio stimulant (Bio) addition to obtain six combinations. Results showed that P + S + V + Bio was the effective practice for enhancing gerbera plant height, leaf width, root weight plant plant-1 and leaves weight plant-1. Also, P + S + V + Bio produced the maximum values of leaf chlorophyll, nitrogen, phosphorus, and potassium contents. The differences in flowering initiation between P + S and each of P + S + V, P + S + V + Bio, P + S + C and P + S + C + Bio were not significant. P + S + V + Bio (for flowering duration and flower yield), in addition to P + S + V (for flowering duration) recorded the highest values in both seasons.

Respiration in light of evergreen and deciduous woody species and its links to the leaf economic spectrum.

Leaf respiration in the light (Rlight) is crucial for understanding the net CO2 exchange of individual plants and entire ecosystems. However, Rlight is poorly quantified and rarely discussed in the context of the leaf economic spectrum (LES), especially among woody species differing in plant functional types (PFTs) (e.g., evergreen vs. deciduous species). To address this gap in our knowledge, Rlight, respiration in the dark (Rdark), light-saturated photosynthetic rates (Asat), leaf dry mass per unit area (LMA), leaf nitrogen (N) and phosphorus (P) concentrations, and maximum carboxylation (Vcmax) and electron transport rates (Jmax) of 54 representative subtropical woody evergreen and deciduous species were measured. With the exception of LMA, the parameters quantified in this study were significantly higher in deciduous species than in evergreen species. The degree of light inhibition did not significantly differ between evergreen (52%) and deciduous (50%) species. Rlight was significantly correlated with LES traits such as Asat, Rdark, LMA, N and P. The Rlight vs. Rdark and N relationships shared common slopes between evergreen and deciduous species, but significantly differed in their y-intercepts, in which the rates of Rlight were slower or faster for any given Rdark or N in deciduous species, respectively. A model for Rlight based on three traits (i.e., Rdark, LMA and P) had an explanatory power of 84.9%. These results show that there is a link between Rlight and the LES, and highlight that PFTs is an important factor in affecting Rlight and the relationships of Rlight with Rdark and N. Thus, this study provides information that can improve the next generation of terrestrial biosphere models (TBMs).

Effect of shading and fertilization with iron and sulfur on some vegetative growth and leaves mineral content of Gardenia jasminoides Ellis.

This study was conducted in a glass house, Dept of Hort. and Landscape, College of Agriculture, Univ. Anbar, during the 2021-2022 growing season, to investigate the influence of shading and fertilization on the growth and leaf mineral content of gardenia plants. This study included two factors: two levels of shading at 0 (S0), shading 50 % (S1) and four treatments of fertilizations, control (F0), chelated iron spray at 2 ml.L-1 (F1), addition of magnesium sulfate to pots at 7 gm.plant-1 (F2) and chelated iron spray at 2 ml.L-1 + addition of magnesium sulfate to pots at 7 gm.plant-1 (F3) and their interaction. Treatments were replicated three times at Split plots design (Shading is the main plot) in an RCBD. The number of plants used was 36 plants. The results showed that interaction treatment (S1F3) significantly increased the plant height by 6.517 cm, the highest increase in shoot length of 11.267 cm, and the number of 94.107 leaves.plant-1 , highest leaf area of 9437.463 cm2 , highest leaf nitrogen content of 1.877 % and highest leaf potassium content of 0.561 %, while lower values of these traits were in interaction treatment (S0F0). Keywords: iron, sulfur, vegetative growth, Gardenia jasminoides Ellis

Response of photosynthetic 13C discrimination to vapour pressure deficit reflects changes in bundle-sheath leakiness in two C4 grasses

Combined measurements of photosynthetic 13C discrimination (Δ) and gas exchange can be used to estimate bundle-sheath leakiness (Φ), a key efficiency parameter for the CO2-concentrating mechanism of C4 species and their intrinsic water-use efficiency (iWUE). Yet, how vapour pressure deficit (VPD) influences the CO2-concentrating mechanism and Φ in low-leakiness species has been rarely explored. Here, we performed on-line 13C discrimination, CO2 and H2O gas exchange measurements and dry matter δ13C analysis to study the responses of Δ, Φ, and iWUE to VPD in two graminaceous C4 species (guinea grass and pearl millet). Growth at high VPD led to an average increase of photosynthetic 13C discrimination (∆A) by 1.4‰ and a concurrent increase of Φ by 0.08 for both species. ∆ of leaf dry matter (∆DM) showed similar responses to VPD, but was consistently higher than ∆A by 0.4‰. The increase of ∆A was associated with increased leaf nitrogen content at high VPD. ∆A was positively correlated with iWUE and leaf nitrogen content but was unrelated with specific leaf area. This study demonstrated that Φ is variable at different growth VPD, an effect that should be taken into account when using ∆ to estimate iWUE in C4 species.

Valorizing lignite waste into engineered nitro-humic fertilizer: Advancing resource efficiency in the era of a circular economy

This study investigates using lignite waste as a carrier matrix for creating engineered nitro-humic fertilizer (NHF). The NHF is synthesized through an innovative ozone oxidation method and nitrogen enrichment. Agronomic efficiency was evaluated through maize growth responses, soil incubation experiments, and fertilizer performance, comparing NHF to commercial urea and NPK fertilizers. Nitrogen release patterns and kinetic models were studied to understand the nitrogen release mechanism of NHF. The engineered structure of NHF displayed globular-like, microporous, and heterogeneous properties, with a negative charge density of 48.85 mV and lower thermal stability of aliphatic carbons. The NHF exhibited a remarkable capability to increase water-holding capacity by up to 48% and extend the water-retention period by 57% during 30 d of soil application. NHF significantly reduced soil urease enzyme activity by more than two-fold. It exhibited a longer nitrogen release period (77 d) with a slow-release pattern, releasing 71.75% of total nitrogen compared to 88.5% in 14 d for urea. The simple Elovich model accurately predicted NHF's nitrogen release kinetics (R2 = 0.9943), identifying Fickian diffusion-based controlled release. Applying NHF improved multiple aspects of maize growth: height, stem diameter, biomass, root weight, leaf area, SPAD value, and leaf nitrogen concentration. Total chlorophyll, carotenoid, and nitrogen uptake also greatly increased compared to the control sample. NHF exhibited superior nitrogen use efficiency (41.5%) and agronomic fertilizer efficiency (36.22%) compared to urea and even surpassed commercial NPK fertilizers. Generally, the produced NHF is an eco-friendly alternative to slow-release fertilizers, offering the advantages of humic substances and nitrogen fertilizers.

Untangling the impact of plantation type and functional traits on ecosystem nutrient stocks in an experimentally restored forest ecosystem

The primary objective of ecological restoration is recovering biodiversity and ecosystem functioning. While a functional trait-based approach can help understand community assembly and ecosystem function recovery during ecological restoration, there still exists a knowledge gap in assessing how functional traits indicate the mediating roles of the plant community in response to forest restoration effects on ecosystem functions. This study applied the “response-effect trait” framework to investigate experimentally whether the treatment of plantation type has an impact on community trait compositions, which in turn could affect forest ecosystem nutrient stocks – here, carbon (C) and nitrogen (N) and phosphorus (P) stocks in tree, understory, litter and soil pools at an experimental station in subtropical China. We used structural equation models (SEMs) to examine the relationships among plantation type, community weighted mean of traits, and nutrient stocks in each pool. Our results show that most of the tree and understory traits studied were response traits to plantation type. Moreover, certain traits played a significant role in mediating plantation-type effects on C, N and P stocks for understory pool (e.g., understory stem specific density and specific leaf area, tree leaf phosphorus content), and for litter and soil pools (e.g., tree leaf carbon or phosphorus content, understory specific leaf area, leaf nitrogen or phosphorus content), known as “response-effect traits”. For the tree pool, only effect traits, and no “response-effect” tree traits, were found for the N stock. Total effects of SEMs indicated that, understory or tree traits can have a greater impact than plantation type on understory or litter C, N or P stocks. After approximately 35 years of natural restoration, exotic plantations exhibited a different community trait characteristic from native plantations. The important roles of traits in mediating the effects of plantation type on non-tree pool C, N and P stocks were highlighted.

Method of Analysis of the Sample Matching of Diagnostic Ranges of Mineral Nutrients in Soil and Cacao Leaves

ABSTRACT Nutritional diagnostic ranges (NDRs) for soil mineral nutrients (SMNs) and leaf mineral nutrients (LMNs) were obtained from the response of the relative dry biomass of cacao beans (rDBCB) and the relative dry biomass of cacao pod husk (rDBCH). Using an exploratory approach, the sample matching levels of the NDRs were determined to discriminate the results of the soil and leaf nutritional diagnostics. These objectives have been achieved from two methodological processes: a new approach to the boundary line technique where the two-dimensional graph is divided into class intervals based on the predictor variables to then establish the NDR from second degree polynomial regressions, and the development of a classification system for soil and leaf samples by NDR to later verify the corresponding matching levels. This new graphical analysis approach has also allowed us to observe how the SMNs and LMNs present different diagnostic profiles for the prediction of rDBCB and rDBCH responses. The leaf nitrogen (N), potassium (K), magnesium (Mg), and manganese (Mn) concentrations showed an NDR matching level above 80% as predictors of rDBCB and rDBCH responses. Leaf calcium (Ca) concentration showed a level between 60% and 80%. Soil phosphorus (P) concentration showed more than 80% of the sample matching level classified by NDR, followed by the concentrations of K, Ca, and zinc (Zn) in the soil that showed a level of coincidence between 60% and 80%. The lack of uniformity in the genetic potential of cacao production and management has produced differences between predictions.

Agronomic performance of green corn at different sowing times and nitrogen doses

The present study aimed to identify the best sowing time and the best nitrogen dose in topdressing of the corn crop for "green ear" consumption. The experiment was conducted between October 2018 and June 2019 in a commercial crop, in Ipameri, Goiás, Brazil. The soil in the experimental area is classified as dystrophic Red-Yellow Latosol with clayey texture. The experimental design used was the randomized blocks, in a 5 x 5 factorial scheme, with five sowing times [1st (10/19/2018); 2nd (11/29/2018); 3rd (01/08/2019); 4th (02/18/2019) and 5th (03/28/2019)], implemented with 40 days intervals, after the first sowing, and five nitrogen doses (0, 50, 100, 150, and 200 kg ha-1), with four replicates. The following factors were evaluated for each sowing time: relative chlorophyll index, leaf dry mass, leaf nitrogen content, plant height, first ear insertion height, ears diameter and length, the total yield of ears with husks, the yield of commercial ears without husks and grain yield. The data were submitted to the analysis of variance (F-test). The sowing times and nitrogen doses in topdressing influenced the leaf nitrogen content, relative chlorophyll index, leaf dry mass, yield, and most of its components. Thus, it can be indicated that the best time for sowing corn for fresh consumption is in October (1st sowing time), and the estimated nitrogen dose in topdressing to obtain the maximum yield is 160 kg ha-1 of nitrogen.

Soil Chemical Attributes and Foliar Nutrient Contents of Native Species in Rehabilitation Chronosequence After Iron Ore Mining

ABSTRACT The mineland rehabilitation can be a challenge due to high soil density and low levels of organic matter and nutrients. This study assessed soil chemical attributes and leaf nutritional contents of two native species (Mimosa acutistipula var. ferrea and Vismia baccifera) grown in an iron waste pile under environmental rehabilitation in the Carajás Mineral Province, Eastern Amazon, Brazil. Soil samples were collected close to plant species in three different chronosequences of rehabilitation. Regardless of the rehabilitation stage, the soils have low levels of phosphorus, potassium, calcium, magnesium, and boron. A tendency of organic matter accumulation was observed at the advanced stage (5–8 years after the onset of rehabilitation process) and it was correlated with other soil nutrients. The leaf nutrient’ contents of M. acutistipula and V. baccifera tend to be distinct from each other, which could indicate that the studied species have different nutritional requirements. The V. baccifera presented higher leaf concentrations of sulfur, copper, and zinc, while M. acutistipula stood out for presenting a higher leaf nitrogen content, which is possibly related to its nitrogen-fixing capacity. In general, an improvement of soil chemical attributes was achieved with the advance of the rehabilitation stages, showing the efficiency of the procedures performed to rehabilitate the studied areas.

MITIGATION EFFECTS OF WATER-SOLUBLE CHITOSAN ON BORON TOXICITY IN PEPPER PLANTS

Excess boron in soil is often found in dry agricultural areas and is one of the factors limiting crop yields. Polysaccharide-based biostimulants can mitigate the harmful effects of environmental stresses on plants. I performed this study under controlled greenhouse conditions to understand the response of pepper plants under boron stress to treatment with water-soluble chitosan (WSC). I watered plants with 50 or 100 mg/l WSC and 1.5 mM boric acid solution. As a result of WSC application at both concentrations, plants were taller and had more leaves and greater leaf length, width, relative chlorophyll content, and fresh aboveground weight compared with the control. Plants exposed to boron stress had fewer leaves, a lower relative chlorophyll content, and leaf blade damage indicative of boron toxicity. At the same time, boron-exposed plants showed a marked increase in the leaf nitrogen, phosphorus, potassium, and boron contents. Applying WSC at both concentrations modulated boron stress in plants by improving plant growth; reducing boron accumulation in leaves; and increasing the available nitrate nitrogen, phosphorus, and potassium contents in the substrate.

Stoichiometric characteristics of woody plant leaves and responses to climate and soil factors in China.

The main research content of the field of ecological stoichiometry is the energy of various chemical elements and the interaction between organisms and the environment throughout ecological processes. Nitrogen and phosphorus are the main elements required for the growth and development of plants and these also form the constituent basis of biological organisms. Both elements interact and jointly regulate the growth and development of plants, and their element ratios are an indication of the nutrient utilization rate and nutrient limitation status of plants. Previous research developed a general biogeography model of the stoichiometric relationship between nitrogen and phosphorus in plant leaves on a global scale. Further, it was shown that the relative rate of nitrogen uptake by leaves was lower than that of phosphorus, and the scaling exponent of nitrogen and phosphorus was 2/3. However, it is not clear how the stoichiometric values of nitrogen and phosphorus, especially their scaling exponents, change in the leaves of Chinese woody plants in response to changing environmental conditions. Therefore, data sets of leaf nitrogen and phosphorus concentrations, and nitrogen to phosphorus ratios in Chinese woody plants were compiled and classified according to different life forms. The overall average concentrations of nitrogen and phosphorus in leaves were 20.77 ± 8.12 mg g-1 and 1.58 ± 1.00 mg g-1, respectively. The contents of nitrogen and phosphorus in leaves of deciduous plants were significantly higher than those of evergreen plants. In leaves, life form is the main driving factor of nitrogen content, and mean annual temperature is the main driving factor of phosphorus content; soil available nitrogen is the main driving factor of the nitrogen to phosphorus ratio. These values can be used for comparison with other studies. In addition, the scale index was found to be significantly different among different life forms. The scaling exponents of N-P of woody plants of different life forms, such as trees, shrubs, evergreen, deciduous, and coniferous plants are 0.67, 0.72, 0.63, 0.72, and 0.66, respectively. The N-P scaling exponent of shrubs was higher than that of trees, and that of deciduous plants was higher than that of evergreen plants. These results suggest that the internal attributes of different life forms, the growth rate related to phosphorus, and the relative nutrient availability of soil are the reasons for the unsteady relationship between nitrogen and phosphorus in leaves.

Multi-stage fertilizer recommendation for spring maize at the field scale based on narrowband vegetation indices

Crop fertilizer recommendations that are site-specific and can be adjusted in multiple growth stages can result in improved nutrient management, fertilizer use efficiency, and grain yield. There are considerable challenges to collecting a large number of soil and crop samples using the traditional methods, so a modern approach to developing fertilizer recommendations is urgently needed. In this study, we used the topdressing recommendation method based on unmanned aerial vehicle-based hyperspectral images and conducted a long-term nitrogen–phosphorus–potassium (NPK) combined fertilizer experiment in a spring maize cropping system. The hyperspectral imagery was acquired at multiple critical stages (jointing, silking, and maturity) in the experimental field containing 120 microplots during 2019–2020. The leaf nitrogen content (LNC) and yield measurement data for each microplot were also collected in multiple stages. Ten narrowband vegetation indices (VIs) were derived from the hyperspectral imagery as effective indicators for the estimation of the crop N status and grain yield. To develop topdressing recommendations for multiple stages, first, the optimal NPK fertilizer amounts, which were applied as the total fertilizer requirement to achieve the highest yield, were obtained. Second, the thresholds of the narrowband VIs, which justify if topdressing N fertilizer is needed, were calculated using the regression model established based on the relative yield and VIs. Finally, the N fertilizer amounts already applied in the jointing and silking stages were obtained based on the response of the narrowband VIs to the N fertilizer amounts. The results reveal that the optimal amount of N fertilizer is 180 kg ha−1, and the grain yield can be improved by using a combination of P and K fertilizers. Five VIs were significantly correlated with both the LNC and yield in the jointing and silking stages, and the thresholds of these VIs, below which topdressing fertilizer is needed, were identified at 95% of relative yield. The five VIs all presented high fitting accuracies with the amount of N fertilizer applied. However, there were noticeable differences in the sensitivities of the VIs in the jointing and silking stages. Therefore, we developed a cost-effective approach and provide multi-stage fertilizer recommendations at the field scale for the spring maize cropping system. This method can also benefit other precision agriculture applications if incorporated with remote sensing techniques.

A Method for Determining the Nitrogen Content of Wheat Leaves Using Multi-Source Spectral Data and a Convolution Neural Network

Accurate estimation of wheat leaf nitrogen concentration (LNC) is critical for characterizing ecosystem and plant physiological processes; it can further guide fertilization and other field management operations, and promote the sustainable development of agriculture. In this study, a wheat LNC test method based on multi-source spectral data and a convolutional neural network is proposed. First, interpolation reconstruction was performed on the wheat spectra data collected by different spectral instruments to ensure that the number of spectral channels and spectral range were consistent, and multi-source spectral data were constructed using interpolated, reconstructed imaging spectral data and non-imaging spectral data. Afterwards, the convolutional neural network DshNet and machine learning methods (PLSR, SVR, and RFR) were compared under various scenarios (non-imaging spectral data, imaging spectral data, and multi-source spectral data). Finally, the competitive adaptive reweighted sampling (CARS) and successive projections algorithm (SPA) were used to optimize the LNC detection model. The results show that the model based on DshNet has the highest test accuracy. The CARS method is more suitable for DshNet model optimization than SPA. In the modeling scenario with non-imaging spectral, imaging spectral, and multi-source spectral, the optimized R2 is 0.86, 0.82, and 0.82, and the RMSE is 0.29, 0.31, and 0.31, respectively. The LNC visualization results show that DshNet modeling using multi-source spectral data is conducive to the visualization expansion of non-imaging spectral data. Therefore, the method presented in this paper provides new considerations for spectral data from different sources and is helpful for related research on the chemometric task of multi-source spectral data.

Effect of Foliar Feeding of Plant Growth Regulators and Nutrients on Leaf Nutrient Status of Guava (Psidium guajava L.) cv. Gwalior-27

The investigation entitled “Effect of foliar feeding of plant growth regulators and nutrients on leaf nutrient status of Guava (Psidium guajava L.) cv. Gwalior-27” was carried out in the Fruit Orchard, Department of Horticulture, R.V.S.K.V.V, CoA, Gwalior district of Madhya Pradesh during mrig-bahar of 2021-22. The field experiment was laid under FRBD (Factorial randomized block design) which contain 20 treatments and were replicated thrice. The result indicated that the leaf nitrogen content (%) as well as leaf calcium content (%) was affected significantly. The highest N content (2.74%) and leaf calcium content (0.75%) were found with M3 (Ca(NO3)2 2%). However, the plant growth regulators and nutrient spray individually and their interactions both had non-significant effect on both leaf P as well as K content. Maximum leaf boron content (90.67 ppm) and leaf zinc content (60.58 ppm) was obtained with M1 (Borax 0.4%) and M2 (ZnSO4 0.5%) respectively. Therefore, based on the experimental findings it can be concluded that foliar feeding of PGR’s and nutrients was an effective way for enhancing the leaf nutrient status of guava. The effect of nutrients was found to be effective in maximising the leaf N content, leaf boron content, leaf zinc content and leaf calcium content significantly. Although, foliar feeding of various concentrations of PGR’s and nutrients independently as well as their interaction effect did not impact any change in the leaf P and K content of the leaf.

Estimation of leaf nitrogen content in winter wheat based on continuum removal and discrete wavelet transform

ABSTRACT Accurate and rapid estimation of leaf nitrogen content (LNC) in winter wheat using hyperspectral techniques is important for growth monitoring and accurate fertilization. Based on field experiments conducted over four years at three ecological sites with four different nitrogen (N) application treatments and four different N-efficient wheat varieties in Henan Province, the canopy spectra and LNC of winter wheat were obtained simultaneously in the main growth stages. The original spectrum was subjected to continuum removal (CR), the correlation between LNC and various vegetation indices was systematically analysed, and the optimal vegetation index estimation model for LNC was constructed. Simultaneously, discrete wavelet transform (DWT) was used to further compress and extract the CR spectrum. The model was combined with partial least squares regression (PLSR) and K-nearest neighbour (KNN) algorithms to estimate LNC in winter wheat. The results showed that the spectrum treated with CR was significantly improved in its correlation with LNC and that the model established based on normalized vegetation index NDVI (CR728, CR977) combined with the CR spectrum was better compared to existing vegetation indices. The calibration and validation coefficients of determination (R2) and root mean square error (RMSE) were 0.816 and 0.799, and 0.352% and 0.342%, respectively. DWT was used to transform the CR spectrum, and the results showed that a combination of the CR spectrum and a sym8 wavelet function with PLSR based on the approximation coefficients at decomposition level 2 predicted LNC most accurately. The coefficient of determination RC 2, root mean square error RMSEC, and relative percent deviation (RPDC) of the calibration set were 0.884, 0.279%, and 2.932, respectively, and RV 2, RMSEV, and RPDV of the validation set were 0.855, 0.291%, and 2.619, respectively, indicating that the model had good stability and predictive ability. Combination of CR and DWT improved the modelling accuracy of wheat LNC and showed better prediction results for multi-year and multi-point samples. The results of the study can provide a basis and reference for rapid monitoring of LNC in winter wheat.