Leaf Chlorophyll Content Research Articles

Plant growth-promoting microorganisms as natural stimulators of nitrogen uptake in citrus.

Improving nitrogen uptake efficiency by citrus in Mediterranean areas, where this crop predominates, is crucial for reducing ground-water pollution and enhancing environmental sustainability. This aligns with the Farm to Fork Strategy (European Green Deal) objectives, which aim to reduce the use of mineral fertilizers by up to 20% and to eliminate soil contamination from nitrogen entirely. In this context, exploring the potential of plant growth-promoting bacteria application to reduce nutrient inputs is a promising opportunity. The objective of the present study was to evaluate the effect of two Bacillus subtilis strains either individually inoculated or in combination with Saccharomyces cerevisiae on 15N-labeled fertilizer uptake efficiency and physiological parameters. Individual inoculations positively affected tree water potential, leaf chlorophyll concentrations (SPAD-values) and photosynthetic performance, enhancing tree growth. Fertilizer-15N use efficiency increased, as did phosphorus and potassium uptakes. Conversely, no response was observed in the trees co-inoculated with S cerevisiae. Therefore, PGPB can be considered an interesting means to reduce reliance on synthetic fertilizers in citrus orchards, minimizing the environmental impact and promoting sustainable production practices.

Assessing canopy temperature responses to nitrogen fertilisation in South Indian crops using UAV -based thermal sensing

ABSTRACT The heavily strained water resources in Bengaluru, India, as a result of rapid urban expansion are increasingly at risk of overexploitation and pollution due to intensified agriculture practices, such as increased nitrogen (N) use and irrigation. In recent years, thermal cameras mounted on Unmanned Aerial Vehicles (UAVs) have proven useful in detecting crop water stress and managing irrigation. However, the use of these cameras in managing N fertilization in the subtropics has been understudied. We employed this technology in two agricultural field experiments in Bengaluru to study the effects of N fertilization on canopy temperatures of maize, finger millet, and lablab, and their correlations with Leaf Chlorophyll Content (LCC), and soil temperature. The results showed that the effect of N was more pronounced at the rainfed experimental site, where the soil is highly acidic and porosity is low. At this site, N significantly affected the canopy temperature of maize and finger millet, particularly under sunny conditions (p = 0.000245), resulting in plots receiving higher nitrogen dosages showing canopies with 2.1°C and 1.3°C cooler temperatures, respectively. Lower temperatures with higher N application were also observed in the irrigated experiment (p value = 0.118), albeit only under sunny conditions. Additionally, canopy temperatures and LCC significantly correlated for maize (R = -0.68, p = 0.015) in the rainfed experiment and millet (R = -0.7, p = 0.011) in the irrigated experiment. However, the correlation of LCC with NDVI was stronger on both sites. Canopy and soil temperatures correlated significantly only when analysed without considering crop species. The use of thermal cameras, equipped with uncooled microbolometers, is accompanied by the dilemma of temperature drift, which affect measurement accuracy. We introduced a drift correction process, which effectively reduced drift by up to 45%, and decreased the drift standard deviation to less than 1°C, that resulted in homogeneous thermal maps suitable for robust statistical analysis. In my submission i added keywords, are they going to be included in the publication ??

Precision water recharge facilitates spikelet development and seed growth in Carex schmidtii: Implications for near-natural restoration of degraded semi-arid wetlands.

The expansion of irrigated agriculture in semi-arid regions exacerbates the degradation of wetland ecosystems. Precision water recharge can facilitate near-natural restoration of degraded wetlands by alleviating the conflict between wetlands and agricultural water use. However, although the ecological significance of precision water recharge as a nature-based solution for restoring wetland vegetation has been widely acknowledged, the mechanisms driving its role in spikelet development and seed growth in Carex schmidtii Meinsh. remain poorly understood despite their critical impact on reproduction and genetic information transfer. To address this knowledge gap, this study compared the characteristics of spikelet development and seed growth in C. schmidtii under four hydrological conditions (drought, moist, water depth of 5cm, and water depth of 10cm) and four re-watering treatments (maintaining constant water levels and re-watering to the initial hydrological regime on the 15th, 30th, and 45th days). We also investigated the ecological and photosynthetic characteristics of the leaves. The hydrological conditions and re-watering treatments significantly affected spikelet development, seed growth, leaf development, and photosynthetic pigment accumulation in C. schmidtii. Compared to other treatments, moist conditions and re-watering to the initial hydrological regime on the 15th day (IH2-RT2) significantly enhanced spikelet characteristics (length, diameter, and biomass) and seed growth traits (length, width, height, volume, thousand-seed weight, and seed test weight). Furthermore, leaf ecological characteristics (length, width, perimeter, and area) and chlorophyll content (chlorophyll a, b, and total chlorophyll) in C. schmidtii under IH2-RT2 exhibited higher values compared to other treatments. Spikelet development characteristics and seed growth traits exhibited significant correlations with leaf ecological characteristics and chlorophyll content. The interaction between leaf ecological characteristics and chlorophyll content explained 39.64% and 43.15% of the variation in spikelet development and seed growth, respectively. A structural equation model further demonstrated that hydrological regimes and re-watering treatments directly affected spikelet development and seed growth while indirectly influencing spikelet development and subsequent seed growth by altering leaf width and chlorophyll b content. Overall, hydrological regimes and re-watering treatments significantly influenced spikelet development and seed growth in C. schmidtii through multiple pathways. The utilization of flood and snowmelt water resources, along with the integrated management of agricultural and wetland water resources, can serve as key strategies for the efficient use of water resources in semi-arid regions. This study provides important insights for wetland vegetation restoration in semi-arid regions worldwide.

Effect of runoff water supply on vegetation and soil response to increasing aridity in Mediterranean drylands

Drylands are characterised by spatially discontinuous vegetation coverage. Consequently, during most rainfalls, runoff is generated in open areas and redistributed to vegetation. This transfer of water and nutrients from source to sink areas has been identified as a key ecohydrological process modulating drylands functioning. However, there are only a few experimental studies assessing the role of runoff redistribution on vegetation, and none of them evaluate its effect on determining the response of vegetation patches to aridification. In this study, we conducted a 3-year runoff exclusion experiment on 8 study sites consisting of Macrochloa tenacissima steppes distributed along two aridity gradients with contrasting lithologies in SE Spain. The aim was to assess the effect of runoff redistribution on vegetation and underlying soil communities as aridity increases, and to determine the influence of lithology on this response. For that, we compared a set of plants (photosynthetic activity, leaf chlorophyll content and green biomass production) and soil (microbial activity and composition) traits measured during different field campaigns on plants receiving run-on with the same variables measured on plants where run-on was excluded. Our findings demonstrate that run-on increases plant green biomass during wet periods with control plants showing a gain of the green biomass fraction higher than run-on excluded plants (difference between control and excluded plants is about ∼10 % of the total AGB in both gradients). By altering green biomass accumulation, run-on exclusion also shapes soil microbial communities (∼20 % of the aridity dependent ASVs are affected by run-on exclusion) and ameliorates the negative effects of drought on the activity and biomass of soil microorganisms (the decrease of SIR values between time 1 and 2 is 17 % lower in control than on run-on excluded plants), but it does not affect photosynthetic rate and chlorophyll concentration. This is due to the poikilohydric behaviour of M. tenacissima and the contrasting timing in the response of the measured variables to water pulses. Vegetation photosynthetic rates respond to short-term water availability, while green biomass and its indirect effect on the soil microbial communities results from a delayed response to the different rainfalls during the growing season. The effects of run-on were lower than expected and did not vary along aridity gradients, probably due to the unusual drought conditions and the atypical rainfalls during the studied period. During the last years, only a few large rainfalls were registered, causing soil moisture saturation under both excluded and control plants. Under these conditions, resources provided by runoff to control plants is diminished, thus lessening their competitive position compared to excluded plots. Long-term monitoring is necessary to evaluate the response of vegetation and the underlying soil to resource supply through runoff water with increasing aridity.

GhRAP2.4 enhances drought tolerance by positively regulating the strigolactone receptor GhD14 expression in cotton (Gossypium hirsutum L.).

Drought poses significant challenges to crop productivity, necessitating a deeper understanding of plant adaptive mechanisms. Strigolactones (SLs), a class of phytohormones, have been recognized as crucial regulators in plant responses to drought, yet the specific role of SL receptor in drought tolerance in cotton (Gossypium hirsutum L.) remains underexplored. In this study, we identified and characterized DWARF14 (GhD14), a SL receptor in cotton. Silencing GhD14 in cotton compromised drought tolerance by reducing leaf relative water content and chlorophyll content, slowing stomatal closure, increasing reactive oxygen species levels, and decreasing antioxidant enzyme activities. Conversely, overexpression of GhD14 in Arabidopsis d14 mutants rescued their drought-sensitive phenotype. Further, we identified a 197-bp fragment (-697 to -894 bp) in the GhD14 promoter that plays a crucial role in the drought stress response. RELATED TO APETALA 2.4 (GhRAP2.4), a dehydration responsive element binding protein (DREB) transcription factor, binds directly to the GhD14 promoter, enhancing its transcription under drought conditions. Silencing GhRAP2.4 in cotton resulted in reduced drought tolerance. This study not only elucidates the molecular interplay between GhRAP2.4 and GhD14 in cotton's drought response but also provides a potential target for genetic modification to improve drought resilience in crops.

Boosting photosynthesis opens new opportunities for agriculture sustainability and circular economy: TheBEST-CROP research and innovation action.

There is a need for ground-breaking technologies to boost crop yield, both grains and biomass, and their processing into economically competitive materials. Novel cereals with enhanced photosynthesis and assimilation of greenhouse gasses, such as carbon dioxide and ozone, and tailored straw suitable for industrial manufacturing, open a new perspective for the circular economy. Here we describe the vision, strategies, and objectives of BEST-CROP, a Horizon-Europe and United Kingdom Research and Innovation (UKRI) funded project that relies on an alliance of academic plant scientists teaming up with plant breeding companies and straw processing companies to use the major advances in photosynthetic knowledge to improve barley biomass and to exploit the variability of barley straw quality and composition. We adopt the most promising strategies to improve the photosynthetic properties and ozone assimilation capacity of barley: (i) tuning leaf chlorophyll content and modifying canopy architecture; (ii) increasing the kinetics of photosynthetic responses to changes in irradiance; (iii) introducing photorespiration bypasses; (iv) modulating stomatal opening, thus increasing the rate of carbon dioxide fixation and ozone assimilation. We expect that by improving our targeted traits we will achieve increases in aboveground total biomass production without modification of the harvest index, with added benefits in sustainability via better resource-use efficiency of water and nitrogen. In parallel, the resulting barley straw is tailored to: (i) increase straw protein content to make it suitable for the development of alternative biolubricants and feed sources; (ii) control cellulose/lignin contents and lignin properties to develop straw-based construction panels and polymer composites. Overall, by exploiting natural- and induced-genetic variability as well as gene editing and transgenic engineering, BEST-CROP will lead to multi-purpose next generation barley cultivars supporting sustainable agriculture and capable of straw-based applications.

Comparing Stacking Ensemble Learning and 1D-CNN Models for Predicting Leaf Chlorophyll Content in Stellera chamaejasme from Hyperspectral Reflectance Measurements

Stellera chamaejasme, a toxic invasive species widespread in degraded alpine grasslands, Qinghai Province, causes a significant threat to the local ecological balance. Accurate monitoring of the leaf chlorophyll content is essential for preventing its expansion over large areas. This study presents an optimal approach by integrating hierarchical dimensionality reduction, stacking ensemble learning, and 1D-CNN models to estimate leaf chlorophyll content in S. chamaejasme using hyperspectral reflectance data. Field spectrometry analysis demonstrates that the combination of Pearson correlation, first derivative, and SPA algorithms can efficiently select the most chlorophyll-sensitive wavelengths, red-edge parameters, and spectral indices related to S. chamaejasme leaves. The stacking ensemble model outperforms the 1D-CNN model in predicting leaf chlorophyll content of S. chamaejasme over the whole growth stage, while the 1D-CNN excels at prediction in each individual growth stage. Comparatively, the 1D-CNN model achieved higher accuracy (R2 > 0.5) in all five growth stages, with optimal performance during the flower bud stage (R2 = 0.787, RMSE = 2.476). This study underscores the potential of combining feature spectra selection with machine learning and deep learning models to monitor S. chamaejasme growth, offering valuable insights for invasive species control and ecological management.

Comparative Pathogenicity of Meloidogyne enterolobii and Meloidogyne incognita in Cotton Cultivars

Meloidogyne enterolobii (Me) is a nematode that has recently been observed in cotton. Initial observations indicate that cotton cultivars resistant to Meloidogyne incognita (Mi) are susceptible to Me, but the reproductive capacity and ability to cause damage by Me compared to Mi is unknown. The objective of this study was to assess the reproductive capacity and ability to cause damage by Mi and Me at different population densities in two cotton cultivars. The study included two greenhouse experiments in which two cotton cultivars, resistant and susceptible to Mi, were inoculated with six increasing population densities of Me and Mi. The genetic resistance of cotton to Mi given by quantitative trait loci of the q-Mi11 and q-Mi14 genes is ineffective against Me. The Mi-resistant cotton cultivar showed a similar gall index to the Mi-susceptible cultivar when inoculated with Me. The mean gall index with Me was significantly higher than that with Mi on the Mi-resistant cotton cultivar. Based on the number of nematodes per root mass and the reproductive factor, Me showed a higher reproductive capacity than Mi on cotton. Increasing Me population densities linearly reduced the height and dry matter production of aboveground biomass in the Mi-resistant cotton cultivar. However, neither Meloidogyne species affected leaf chlorophyll content and photosynthetic rate of the cotton plants.

The allelic mutation of NBS-LRR gene causes premature senescence in wheat.

Premature senescence has a significant impact on the yield and quality of wheat crops. The process is controlled by multiple and intricate genetic pathways and regulatory elements, whereby the discovery of additional mutants provides important insights into the molecular basis of this important trait. Here, we developed a premature senescence wheat mutant je0874, its leaves started to show yellow before heading stage; with plant growth and development, the degree of yellowing worsened rapidly, and chlorophyll content in flag leaf was reduced by 93.8% at 15 days after heading, all other leaves became dryness at the grain filling stage. In the mutant, the reactive oxygen species (ROS) and its metabolites increased up to 34.8%~47.3%, while activities of ROS scavenging enzymes were reduced by 62.7% to 96.7%. Premature senescence resulted in a reduction of thousand grain weight by over 50%. Genetic analysis showed the mutation of senescence was controlled by a single recessive gene, and target gene was finely mapped to a 338kb region of the long arm of chromosome 2D. This region contained a total of 6 annotated genes, while only gene TraesFLD2D01G513900 carried a SNP mutation. The gene contained an NBS-LRR domain, we named it Taps1. Allelic mutants of Taps1 exhibited a lesion mimic phenotype, and the mutant allele resulted in cell death in tobacco, which represent a novel gene controlling wheat senescence. Two haplotypes were identified in 180 accessions, which did not lead to cell death. These results contribute to increase our understanding of the regulation of premature plant senescence.

Prediction of Winter Wheat Parameters with Planet SuperDove Imagery and Explainable Artificial Intelligence

This study investigated the application of high-resolution satellite imagery from SuperDove satellites combined with machine learning algorithms to estimate the spatiotemporal variability of some winter wheat parameters, including the relative leaf chlorophyll content (RCC), relative water content (RWC), and aboveground dry matter (DM). The research was carried out within an experimental field in Southern Italy during the 2024 growing season. Different machine learning (ML) algorithms were trained and compared using spectral band data and calculated vegetation indices (VIs) as predictors. Model performance was assessed using R2 and RMSE. The ML models tested were random forest (RF), support vector regressor (SVR), and extreme gradient boosting (XGB). RF outperformed the other ML algorithms in the prediction of RCC when using VIs as predictors (R2 = 0.81) and in the prediction of the RWC and DM when using spectral bands data as predictors (R2 = 0.71 and 0.87, respectively). Model explainability was assessed with the SHAP method. A SHAP analysis highlighted that GNDVI, Cl1, and NDRE were the most important VIs for predicting RCC, while yellow and red bands were the most important for DM prediction, and yellow and nir bands for RWC prediction. The best model found for each target was used to model its seasonal trend and produce a variability map. This approach highlights the potential of integrating ML and high-resolution satellite imagery for the remote monitoring of wheat, which can support sustainable farming practices.

Bio-efficacy Studies of Unique in Relation to Growth, Yield and Shelf Life of Nanasaheb Purple Seedless Grape Variety Grown under Multilocation

Grape production, particularly seedless varieties like Nanasaheb Purple Seedless is highly valued for both domestic and export markets. However, environmental stresses such as drought and salinity often affect the quality and yield of grapes. This study explored the effectiveness of bio-stimulant (Unique) enhancing grape yield, quality and shelf life across two locations: ICAR-NRC for Grapes, Pune and Walwa, Sangli District of Maharashtra. While, bio-stimulants have shown potential in promoting vine growth and stress resilience, there is limited research on the optimal dosage and application timing for specific varieties like Nanasaheb Purple Seedless. The primary objective of this study was to identify the most effective dose and application schedule of Unique to maximize yield, berry quality and shelf life. A randomized block design (RBD) was employed with three treatment levels (20, 25 and 30 ml/L) of Unique applied through foliar spray at five key growth stages. Growth, yield, and quality parameters were measured and compared with control. Results revealed that Unique application of 30 ml/L at five critical growth stages significantly enhanced bunch weight, berry size and yield. Additionally, biochemical markers such as phenol, protein and reducing sugar levels also increased. Leaf area and chlorophyll content in leaf also improved facilitating better nutrient absorption and photosynthesis. Shelf life was extended with reduced weight loss during storage. The foliar application of 30 ml of Unique at specific growth stages is recommended to optimize the quality, yield and shelf life of Nanasaheb Purple Seedless grapes.

Construing the resilience to osmotic stress using endophytic fungus in maize (Zea mays L.).

In a wake of shifting climatic scenarios, plants are frequently forced to undergo a spectrum of abiotic and biotic stresses at various stages of growth, many of which have a detrimental effect on production and survival. Naturally, microbial consortia partner up to boost plant growth and constitute a diversified ecosystem against abiotic stresses. Despite this, little is known pertaining to the interplay between endophytic microbes which release phytohormones and stimulate plant development in stressed environments. In a lab study, we demonstrated that an endophyte isolated from the Kargil region of India, a Fusarium equiseti strain K23-FE, colonizes the maize hybrid MAH 14 - 5, promoting its growth and conferring polyethylene glycol (PEG)-induced osmotic stress tolerance. To unravel the molecular mechanism, maize seedlings inoculated with endophyte were subjected to comparative transcriptomic analysis. In response to osmotic stress, genes associated with metabolic, photosynthesis, secondary metabolites, and terpene biosynthesis pathways were highly upregulated in endophyte enriched maize seedlings. Further, in a greenhouse experiment, maize plants inoculated with fungal endophyte showed higher relative leaf water content, chlorophyll content, and antioxidant enzyme activity such as polyphenol oxidase (PPO) and catalase (CAT) under 50% field capacity conditions. Osmoprotectant like proline were higher and malondialdehyde content was reduced in colonized plants. This study set as proof of concept to demonstrate that endophytes adapted to adverse environments can efficiently tweak non-host plant responses to abiotic stresses such as water deficit stress via physiological and molecular pathways, offering a huge opportunity for their deployment in sustainable agriculture.

Enhancing Jamun cv. Goma Priyanka Growth and Stress Resilience through Foliar Humic Acid and Potassium Silicate Application

The present research focuses on an important knowledge deficit concerning the foliar reaction of Jamun cv. Goma Priyanka to the application of humic acid (HA) and potassium silicate (KS), emphasizing its growth and physiological functions. Humic acid promotes the production and equilibrium of phytohormones such as auxins and cytokinins, facilitating cell division, elongation, and differentiation, which in turn enhances plant development. The present investigation was carried out at the Fruit Instructional Farm of College of Horticulture and Forestry, Jhalawar, the study underscores the effectiveness of the T15 treatment, which combines potassium silicate and HA at elevated doses, in enhancing leaf relative humidity, chlorophyll content, stress tolerance, and overall plant vitality.

Mind the leaf anatomy while taking ground truth with portable chlorophyll meters

A wide range of portable chlorophyll meters are increasingly being used to measure leaf chlorophyll content as an indicator of plant performance, providing reference data for remote sensing studies. We tested the effect of leaf anatomy on the relationship between optical assessments of chlorophyll (Chl) against biochemically determined Chl content as a reference. Optical Chl assessments included measurements taken by four chlorophyll meters: three transmittance-based (SPAD-502, Dualex-4 Scientific, and MultispeQ 2.0), one fluorescence-based (CCM-300), and vegetation indices calculated from the 400–2500 nm leaf reflectance acquired using an ASD FieldSpec and a contact plant probe. Three leaf types with different anatomy were included: dorsiventral laminar leaves, grass leaves, and needles. On laminar leaves, all instruments performed well for chlorophyll content estimation (R2 > 0.80, nRMSE < 15%), regardless of the variation in their specific internal structure (mesomorphic, scleromorphic, or scleromorphic with hypodermis), similarly to the performance of four reflectance indices (R2 > 0.90, nRMSE < 16%). For grasses, the model to predict chlorophyll content across multiple species had low performance with CCM-300 (R2 = 0.45, nRMSE = 11%) and failed for SPAD. For Norway spruce needles, the relation of CCM-300 values to chlorophyll content was also weak (R2 = 0.45, nRMSE = 11%). To improve the accuracy of data used for remote sensing algorithm development, we recommend calibration of chlorophyll meter measurements with biochemical assessments, especially for species with anatomy other than laminar dicot leaves. The take-home message is that portable chlorophyll meters perform well for laminar leaves and grasses with wider leaves, however, their accuracy is limited for conifer needles and narrow grass leaves. Species-specific calibrations are necessary to account for anatomical variations, and adjustments in sampling protocols may be required to improve measurement reliability.

Radiation-assisted tailoring of swelling behavior and water retention of Na-CMC/PAAm hydrogels for enhancing Beta Vulgaris under drought stress

This study investigates the negative impact of climate change on water resources, specifically water for agricultural irrigation. It describes how to optimize swelling, gel properties and long-term water retention capacities of Na-CMC/PAAm hydrogels for managing drought stress of Sugar beet plants through techniques such as changing the composition, synthetic conditions and chemical modification. Gamma radiation-induced free radical copolymerization was used to synthesize superabsorbent hydrogels using sodium carboxymethyl cellulose (Na-CMC) and acrylamide (AAm). The study also explored how varying Na-CMC/AAm ratio and radiation dose influence their swelling behaviour, gel fraction, and water retention. FTIR showed that CMC and PAAm components are part of the hydrogel structure. The equilibrium swelling reached a maximum value of ~ 500 g/g at a Na-CMC/AAm ratio of 60/40. High content of AAm reduced swelling because it caused increased hydrophobicity while high radiation doses up to 50 kGy increased crosslinking resulting in improved but limited swelling from 65 to 85 (g/g). After the second cycle, KOH modification reached maximum swelling capacity by introducing anionic carboxylate groups up to 415 (g/g). SEM images revealed uniform pores in an unmodified scaffold while larger cavities were formed upon modification facilitating Water absorption. Surprisingly, the improved hydrogels retained more water: about 75% even after 16 days as opposed to a 50% drop within five days in the case of unmodified ones. This hydrogel significantly enhanced shoot length by 18%, root length by 32%, fresh weight shoot by 15%, and dry weight shoot by 15% under severe drought conditions. As a result, yield increased by 22%, proteins went up by 19%, and carbohydrates rose by 13%. Leaf chlorophyll content increased with a corresponding decline in stress enzymes indicating decreased oxidative damage. This eco-friendly Na-CMC/PAAm-based hydrogel seems to have potential use for addressing water scarcity and agricultural challenges.

Enrichment of Chlorophyll Content of Maize (Zea mays L.) Hybrid Through Biodegradable Polymer Coated Urea Fertilizers

Background: Nitrogen is essential for chlorophyll formation which significantly influencing the growth and yield of crops. This study aimed to enhance maize leaf chlorophyll content by ensuring a steady nitrogen supply throughout the growing period. A field experiment was conducted using biodegradable polymer coated urea as a slow release nitrogenous fertilizer to achieve chlorophyll enrichment in maize. Methods: There were nine treatments including uncoated urea, various biodegradable polymer-coated urea and commercially available coated urea fertilizer formulations were compared. Result: In enhancing the leaf area index and chlorophyll content of maize, pine oleoresin-coated urea (POCU) and humic acid-coated urea (HACU) showed superior performance over other urea fertilizers. Leaf area index (LAI), a key indicator of canopy development, average LAI was significantly higher in POCU (2.71) and HACU (2.70) treatments which was 32.8 and 32.4% higher than uncoated urea treatment respectively. This leading to higher photosynthetic efficiency and biomass accumulation resulted, higher chlorophyll content in maize by POCU and HACU treatments. In particular, POCU showed maximum chlorophyll ‘a’ (1.58 mg mL-1) and ‘b’ (0.49 mg mL-1) content as well as total chlorophyll content (2.07 mg mL-1) at various growth stages of maize. This indicates that these slow-release formulations provided a sustained supply of nitrogen, promoting chlorophyll synthesis and enhancing photosynthetic activity. Additionally, the positive correlation between LAI and chlorophyll content in maize plants, led to improved photosynthetic efficiency, biomass accumulation and ultimately higher yields.

Trade-Off Between Enzymatic Antioxidant Defense and Accumulation of Organic Metabolite Affects Salt Tolerance of White Clover Associated with Redox, Water, and Metabolic Homeostases.

White clover (Trifolium repens) is an excellent perennial cold-season ground-cover plant for municipal landscaping and urban greening. It is, therefore, widely distributed and utilized throughout the world. However, poor salt tolerance greatly limits its promotion and application. This study aims to investigate the difference in the mechanism of salt tolerance in relation to osmotic adjustment, enzymatic and nonenzymatic antioxidant defenses, and organic metabolites remodeling between salt-tolerant PI237292 (Trp004) and salt-sensitive Korla (KL). Results demonstrated that salt stress significantly induced chlorophyll loss, water imbalance, and accumulations of malondialdehyde (MDA), hydrogen peroxide (H2O2), and superoxide anion (O2.-), resulting in reduced cell membrane stability in two types of white clovers. However, Trp004 maintained significantly higher leaf relative water content and chlorophyll content as well as lower osmotic potential and oxidative damage, compared with KL under salt stress. Although Trp004 exhibited significantly lower activities of superoxide dismutase, peroxidase, catalase, ascorbate peroxidase, monodehydroasorbate reductase, dehydroascorbate reductase, and glutathione reductase than KL in response to salt stress, significantly higher ascorbic acid (ASA), dehydroascorbic acid (DHA), glutathione (GSH), glutathione disulfide (GSSG), ASA/DHA, and GSH/GSSG were detected in Trp004. These findings indicated a trade-off relationship between antioxidant enzymes and nonenzymatic antioxidants in different white clover genotypes adapting to salt stress. In addition, Trp004 accumulated more organic acids (glycolic acid, succinic acid, fumaric acid, malic acid, linolenic acid, and cis-sinapic acid), amino acids (serine, l-allothreonine, and 4-aminobutyric acid), sugars (tagatose, fructose, glucoheptose, cellobiose, and melezitose), and other metabolites (myo-inositol, arabitol, galactinol, cellobiotol, and stigmasterol) than KL when they suffered from the same salt concentration and duration of stress. These organic metabolites helped to maintain osmotic adjustment, energy supply, reactive oxygen species homeostasis, and cellular metabolic homeostasis with regard to salt stress. Trp004 can be used as a potential resource for cultivating in salinized soils.

Agronomic performance, genetic variability estimation and mutant selection in M3 generation of sorghum under optimum condition

Abstract The population resulting from mutations in the M3 generation generally has a diversity that can be selected to obtain mutants with the desired character. This study aimed to observe the agronomic performances of the M3 generation of sorghum and to estimate its genetic parameters as information for selection. The genetic materials used in this research were 242 sorghum mutant lines of the M3 generation, and six comparison genotypes, namely Numbu, Samurai-1, Kawali, Pahat, B-35, and Watar Hammu Putih (parent). This experiment used an augmented design. The result analysis revealed that the genotype treatments affected the differences in performance of panicle length, stem diameter, and chlorophyll content characters. Significant differences were also seen between the control genotypes on all the observed characters. The appearance of sorghum mutant lines and control genotypes showed substantial differences in panicle length, stem diameter, panicle weight, biomass weight, leaf chlorophyll content, and seed yield characters. The wide genetic diversity and high heritability values were indicated by plant height, panicle length, panicle weight, and chlorophyll content characters. Using panicle weight as a selection character in M3 populations has increased the differential selection of stem diameter, leaf chlorophyll content, biomass, and seed yield characters.

Identification of Salt Tolerance and Stress Response in US Department of Agriculture Tomato Germplasm at the Seedling Stage

Soil salinity is a significant abiotic factor that impedes sustainable crop production in key agricultural regions worldwide. Saline cultivation adversely affects soil quality, whereas the use of saline water for irrigation disrupts the physiological and biochemical processes of plants. Continuous irrigation with high salt concentrations leads to a gradual buildup of soil salinity, thus hindering optimal plant growth and development. Consequently, there is a growing emphasis on breeding salinity-tolerant cultivars of various crops. In this study, 71 tomato accessions sourced from 20 countries and provided by the US Department of Agriculture were evaluated under controlled greenhouse conditions and subjected to saline stress (200 mM NaCl). The experiment used a split-plot design, with the salt treatment serving as the main plot and the tomato accession as the subplot, which were arranged in a completely randomized design with three replications. Results identified nine accessions (PI 109837, PI 127820, PI 270256, PI 634828, PI 636205, PI 636255, PI 647143, PI 647528, and PI 647556) as salt-tolerant. Additionally, high broad-sense heritability was observed for the leaf injury score and leaf chlorophyll content. Furthermore, positive correlations were found among parameters related to the leaf injury score and leaf chlorophyll content (soil plant analysis development value). These findings offer valuable insights for tomato breeding programs, particularly those focused on enhancing salt tolerance of elite cultivars of this crucial crop.

Full cycle rice growth monitoring with dual-pol SAR data and interpretable deep learning

ABSTRACT Addressing challenges in crop growth monitoring, such as limited assessment dimensions, incomplete coverage of growth cycles, and limited deep learning (DL) interpretability, a novel dual-pol SAR rice growth monitoring method using a new crop growth index (CGI) and an interpretable DL architecture is proposed. Initially, radar vegetation indices, polarimetric decomposition parameters, and backscattering coefficients characterize rice growth in multiple dimensions. Subsequently, a CGI is designed, combining fractional vegetation cover and leaf chlorophyll content to accurately depict rice growth status, capturing both the structural and physiological activity of rice. Finally, an interpretable DL architecture incorporating a feature selection explainer and a feature-aware enhanced segmentation model is introduced. This architecture incorporates feature-wise variable learning networks, interprets the importance of individual features, and optimizes the feature composition, significantly enhancing the interpretability of the DL model. This architecture is also applicable to other neural networks. The method is applied in Suihua City, Heilongjiang Province, China, using Sentinel-1 dual-pol data from 2022 and 2023. Experiments indicate that the proposed method achieves an overall accuracy of 90.57% in the test set and a generalization accuracy of 90.43%. The integration of CGI and the interpretable DL architecture enhances the reliability of rice growth monitoring results.