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Introduction: Flesh color is an essential trait in chieh-qua (Benincasa hispida Cogn. var. Chieh-qua How); however, the inheritance and molecular basis of green flesh trait remain unclear. Methods: In the present study, two F2 populations, derived from 1742 (white flesh) × FJ3211 (green flesh) and J16 (white flesh) × FJ5 (green flesh), were used to identify the green flesh (Cqgf) locus. Results: Genetic analysis revealed that the presence of green flesh was a quantitative trait that closely followed a normal distribution. Combining the results from QTL mapping and BSA-seq analysis, the Cqgf locus was preliminarily determined to be located on chromosome 05 and was narrowed down to a 2.55-Mb interval by linkage analysis. A large J16 × FJ5 F2 population comprising 3,180 individuals was subsequently used to screen the recombinants, and the Cqgf locus was fine-mapped to a region of 329.70 kb that harbors six genes. One of the candidate genes, Bch05G003700 , the zinc-finger transcription factor LOL1 (lsd one like 1 protein; CqLOL1), was the strongest candidate gene for the Cqgf locus according to sequence variation and expression analysis. Additionally, a point mutation (A > C) in CqLOL1 resulted in the substitution of threonine (T) with proline (P) in the amino acid sequence, showing a complete relationship linked with flesh color in a panel of 45 germplasms. Discussion: The study suggests that CqLOL1 promotes the accumulation of chlorophyll content in chieh-qua and lead to green flesh. Our findings establish a theoretical and technical foundation for breeding different flesh color lines and elucidating the underlying mechanisms of flesh color in chieh-qua. [ABSTRACT FROM AUTHOR]

Most oak savannas in the Midwestern United States have been lost to agriculture and habitat degradation. Because of their rarity and high plant and animal diversity, savannas are often a target for restoration, which frequently relies on the direct planting of oak seedlings to establish the necessary canopy. Returning fire to the system is critical to the herbaceous component, but with planted seedlings, managers risk damaging or killing trees if burning is introduced too soon. We studied the growth and physiological responses of three oak species (Quercus alba, Quercus macrocarpa, and Quercus velutina) to prescribed fire to determine impacts on planted trees. This study utilized two restored oak savanna units that were planted in 1995 and 1998, each with burned and unburned areas. We tracked trees ranging from 0.9 to 29.8 cm in diameter at breast height (DBH) to determine the size threshold above which top kill is unlikely and documented differences in leaf structure and extension growth between the burned and unburned areas. There was no mortality observed. Moreover, no trees larger than 4 cm DBH were top killed by the fire. Fire responses in leaf mass per unit area and chlorophyll content were small and inconsistent across species. However, all oak species grew more in burned areas than trees in adjacent unburned areas. Therefore, the addition of low‐intensity prescribed fire to an oak savanna planting may increase the growth rate of planted trees with minimal risk of mortality once trees have reached sufficient size. [ABSTRACT FROM AUTHOR]

• Drought stress adversely affected the soybean seed yield, oil content and protein content. • Activity of antioxidant enzymes promoted in soybean plant under drought stress. • Chitosan improved growth and yield of soybean genotypes under both irrigation regimes. • Soybean genotypes used different defense mechanisms under chitosan application to cope with drought stress. The current study investigated the responses of physiological, biochemical, and agronomic of four soybean genotypes to foliar application of chitosan under optimal water supply and drought stress conditions. A factorial split-plot experiment was set up in a randomized complete block design with three replications for two years (2022 and 2023). The enzymes activity of catalase (CAT), superoxide dismutase (SOD), peroxidase (POD), ascorbate peroxidase (APX) as well as chlorophyll content (a, b, and total), ß -carotene content, seed yield, protein yield, and oil yield were measured. Drought stress enhanced the ß -carotene content and the activity of SOD, POD, APX, and CAT compared with the full irrigation regime. By contrast, the chlorophyll content (a, b, and total) was reduced when soybean plants were grown under water-limited condition as compared with the water-limited condition. The drought stress regime led to decreases of 60 %, 12.5 %, and 23.3 % (on average across years, genotype, and chitosan treatments) in soybean seed yield, oil content, and protein content, respectively. The soybean genotypes differently responded to the foliar application of chitosan under both irrigation regimes in terms of the activity of SOD, POD, APX, and CAT enzymes. The chlorophyll a, b, and total contents roughly enhanced when the soybean plants were treated with chitosan compared with the control treatment. A slight reduction was observed for the ß -carotene content when the chitosan was applied under optimal water supply condition while the ß -carotene content was depleted for all studied genotypes under drought stress condition. On average across genotypes and chitosan treatments, applying chitosan boosted the soybean seed yield, oil content, and protein content by 6.9 %, 8.1 %, and 6.7 %, respectively. Overall, foliar application of chitosan and Williams genotype would be recommended under both irrigation regimes (drought and well-watered) to achieve the highest soybean seed yield, oil content, and protein content. [ABSTRACT FROM AUTHOR]

The influences of airborne trace elements in urban dust on element concentrations and functional traits of Tilia cordata were examined. For the present study, the unwashed and washed leaves of T. cordata were collected to assess the concentration of metals in Katowice City, Poland, from sites of different traffic intensity and industry activity. The content of Al, Cd, Cr, Cu, Fe, Mn, Pb, Zn, C, and N was measured. Additionally, a number of functional traits such as photosynthetic pigment content, specific leaf area (SLA), leaf dry matter content (LDMC), and diseased areas of the leaves were determined to assess the impact of the polluters on the physiology of the trees and their resources acquisition strategy. We hypothesized that the photosynthetic pigments of T. cordata will decrease with the traffic and industry intensity, and the traits related to the resources acquisition and stress resistance will shift into a more conservative strategy. The Principal Component Analysis and the Inverse Distance Weighting (IDW) interpolation method helped to identify that the Fe, Zn, Al, and Cr were related mainly to traffic intensification and Pb to industrial activities. The results indicate that Katowice is considerably polluted by Zn (up to 189.6 and 260.2 mg kg−1 in washed and unwashed leaves, respectively), Pb (up to 51.7 and 133.6 mg kg−1), and Cd (up to 2.27 and 2.43 mg kg−1) compared to other cities worldwide. Also, a reduction of approximately 27% in the photosynthetic pigments was observed at the high-traffic and industrial sites. The trees from the mainly affected areas with heavy traffic and industry tend to apply a conservative resources strategy with a decrement in SLA and an increment in LDMC. In contrast, the opposite trend was observed at the less affected sites (high SLA, low LDMC). The study showed that unfavourable urban conditions can trigger a plastic response on multiple levels. Knowledge of the possible paths of adaptation to urban conditions of different plant species is nowadays crucial to appropriate urban greenery planning. [ABSTRACT FROM AUTHOR]

Fusing three-dimensional (3D) and multispectral (MS) imaging data holds promise for high-throughput and comprehensive plant phenotyping to decipher genome-to-phenome knowledge. Acquiring high-quality 3D MS point clouds (3DMPCs) of plants remains challenging because of poor 3D data quality and limited radiometric calibration methods for plants with a complex canopy structure. Here, we present a novel 3D spatial–spectral data fusion approach to collect high-quality 3DMPCs of plants by integrating the next-best-view planning for adaptive data acquisition and neural reference field (NeREF) for radiometric calibration. This approach was used to acquire 3DMPCs of perilla, tomato, and rapeseed plants with diverse plant architecture and leaf morphological features evaluated by the accuracy of chlorophyll content and equivalent water thickness (EWT) estimation. The results showed that the completeness of plant point clouds collected by this approach was improved by an average of 23.6% compared with the fixed viewpoints alone. The NeREF-based radiometric calibration with the hemispherical reference outperformed the conventional calibration method by reducing the root mean square error (RMSE) of 58.93% for extracted reflectance spectra. The RMSE for chlorophyll content and EWT predictions decreased by 21.25% and 14.13% using partial least squares regression with the generated 3DMPCs. Collectively, our study provides an effective and efficient way to collect high-quality 3DMPCs of plants under natural light conditions, which improves the accuracy and comprehensiveness of phenotyping plant morphological and physiological traits, and thus will facilitate plant biology and genetic studies as well as crop breeding. This study reports an unmanned ground vehicle phenotyping-based method for generating high-quality 3D multispectral point clouds to analyze spatial heterogeneity in plant traits. Combining next-best-view planning for adaptive data acquisition and neural reference field for radiometric calibration, the approach significantly improves estimation accuracies for key plant traits, such as chlorophyll content and equivalent water thickness. [ABSTRACT FROM AUTHOR]

The concentration of nitrogen fertilizer is matched with the nutrient requirements in different growth stages of plants, which coordinates their vegetative and reproductive growth. In this study, the influences of nitrogen concentration before and after initiation of flower bud differentiation (first and second stage, respectively) on pepper seedling quality were studied. The chlorophyll a content, sucrose synthase activity, and sucrose phosphate synthase activity of pepper seedlings grown under moderate nitrogen (15 mmol L−1) in the first stage combined with high nitrogen (25.61 mmol L−1) in the second stage were 15.7%, 39.3%, and 34.6% higher than those of the same nitrogen concentration (15 mmol L−1) in the first and second stages treatment, respectively. The regression model also showed that the values of flower bud diameter, shoot fresh weight, root fresh weight, and glutamine synthetase activity of pepper were high under the condition of moderate nitrogen in the first stage and higher nitrogen in the second stage. In addition, the results of comprehensive evaluation showed that moderate nitrogen (15 mmol L−1) in the first stage and high nitrogen (25.61 mmol L−1) in the second stage treatment ranked first, which improved carbon and nitrogen metabolism, increased biomass accumulation, and promoted the flower bud differentiation and flowering of pepper seedlings. [ABSTRACT FROM AUTHOR]

To investigate the effects of pulse electric field stimulation on the photosynthetic electron transport chain and negative air ion (NAI) release capacity of snake plants, the chlorophyll content, fluorescence induction kinetics curve (OJIP curve), chlorophyll fluorescence parameters, and NAI release concentration of snake plants kept under identical greenhouse conditions under different pulse electric field stimulations were compared and analyzed. The experimental results show that (1) after pulse electric field stimulation, the chlorophyll content in treatment group T1 (5 kv) and T2 (7 kv) of snake plants increased by 6.30% and 6.70%, respectively, with significant differences observed between the two treatment groups and the control group (CK). (2) In both treatment groups, the OJIP curve exhibited higher values for the inflection point (I) and peak (P) compared to the origin (O) and inflection point (J) values, with the rising trend in the I–P segment being more gentle than that of the O–J segment. Additionally, the J band was above 0, with the peak value in the T2 group being higher than that in the T1 group. (3) The chlorophyll fluorescence parameters showed fluctuating variations. Specifically, Fm, TRo/CSo, ETo/CSo, and DIo/CSo showed ascending trends in the treatment groups. Fv/Fo, Sm, and ABS/RC exhibited descending trends; Fv/Fm, Vj, ETo/RC, and φEo showed relatively minor changes. The PIabs displayed a decreasing trend. The PItotal in the CK was greater than that in the T1 and T2 groups. (4) After 4 h of pulse electric field stimulation, the NAI concentration increased by 87.60% in the T1 group and by 62.09% in the T2 group, compared to the same measurement taken at 3 h. Pulse electric field impacts the photosynthetic electron transport chain of snake plants, thereby influencing their NAI release capacity. This study aims to elucidate the physiological responses of the chloroplasts in snake plants to pulsed electric field stimulation and to lay the foundation for enhancing the plant's release of negative air ion concentrations through physical and technological means. [ABSTRACT FROM AUTHOR]

This study explored the quantitative inversion of the chlorophyll content in Paulownia seedling leaves under drought stress and analyzed the factors influencing the chlorophyll content from multiple perspectives to obtain the optimal model. Paulownia seedlings were selected as the experimental materials for the potted water control experiments. Four drought stress treatments were set up to obtain four types of Paulownia seedlings: one pair of top leaves (T1), two pairs of leaves (T2), three pairs of leaves (T3), and four pairs of leaves (T4). In total, 23 spectral transformations were selected, and the following four methods were adopted to construct the prediction model, select the best spectral preprocessing method, and explore the influence of water bands: partial least squares modeling with all spectral bands (all-band partial least squares, AB-PLS), principal component analysis partial least squares (PCA-PLS), correlation analysis partial least squares (CA-PLS), correlation analysis (water band) partial least squares, ([CA(W)-PLS]), and vegetation index modeling. Based on the prediction accuracy and the uniformity of different leaf positions, the optimal model was systematically explored. The results of the analysis of spectral reflectance showed significant differences at different leaf positions. The sensitive bands of chlorophyll were located near 550 nm, whereas the sensitive bands of water were located near 1440 and 1920 nm. The results of the vegetation index models indicate that the multiple-index models outperformed the single-index models. Accuracy decreased as the number of indicators decreased. We found that different model construction methods matched different optimal spectral preprocessing methods. First derivative spectra ( R ′ ) was the best preprocessing method for the AB-PLS, PCA-PLS, and CA-PLS models, whereas the inverse log spectra ( l o g (1 / R) ) was the best preprocessing method for the CA(W)-PLS model. Among the 14 indices, the green normalized difference vegetation index (GNDVI) was most correlated with the chlorophyll content sensitivity indices, and the water index (WI) was most correlated with the water sensitive indices. At the same time, the water band affected the cross validation accuracy. When characteristic bands were used for modeling, the cross validation accuracy was significantly increased. In contrast, when vegetation indices were used for modeling, the accuracy of the cross validation increased slightly but its predictive ability was reduced; thus, these changes could be ignored. We found that leaf position also affected the prediction accuracy, with the first pair of top leaves exhibiting the worst predictive ability. This was a bottleneck that limited predictive capability. Finally, we found that the CA(W)-PLS model was optimal. The model was based on 23 spectral transformations, four PLS construction methods, water bands, and different leaf positions to ensure systematicity, stability, and applicability. [ABSTRACT FROM AUTHOR]

Fossil fuels, particularly oil, face sustainability challenges due to depletion and their role in increasing atmospheric CO2 levels, contributing to climate change and impacting global agriculture. Renewable energy sources like solar power offer a viable alternative. This study explores the feasibility of agro-photovoltaic (APV) systems, which integrate solar panels with agricultural land to generate electricity while cultivating crops. Specifically, the impact of APV systems on rice production and quality was investigated. Solar modules with a total capacity of 99.84 kW were installed on a 2580 m² site, with two module configurations tested. Two rice (Oryza sativa L.) cultivars, Woonkwang and Saenuri, were transplanted and monitored for growth characteristics, chlorophyll content, and fluorescence, as well as yield and quality. Growth analysis of rice under APV systems showed minimal impact on plant height and tiller numbers, though chlorophyll content analysis indicated delayed leaf aging and extended maturation time. Rice yield decreased due to altered panicle and spikelet numbers. Quality analysis revealed changes in head rice rate and broken rice, stressing optimal harvest timing in APV systems. Shading conditions also affected physicochemical properties and taste profiles. Yields dropped by about 20% under APV systems, but the financial returns from electricity generation significantly outweighed the crop revenue loss. Despite the high initial installation costs and regulatory challenges, APV systems present a promising dual-use approach for enhancing farm income and promoting renewable energy. Continued research and investment are essential for optimizing APV systems and expanding their adoption. [ABSTRACT FROM AUTHOR]

The chlorophyll content (CC) directly affects photosynthesis, growth, and yield. However, the genetic basis of CC is still unclear in maize (Zea mays L.). Here, we conducted a genome-wide association study using mixed linear model for CC of the fifth leaves at seedling stage (CCFSS) and the ear leaves at filling stage (CCEFS) for 334 maize inbred lines. The heritability estimates for CCFSS and CCEFS, obtained via variance components analysis using the lme4 package in R, were 70.84% and 78.99%, respectively, indicating that the CC of leaves is primarily controlled by genetic factors. A total of 15 CC-related SNPs and 177 candidate genes were identified with a p-value < 4.49 × 10−5, which explained 4.98–7.59% of the phenotypic variation. Lines with more favorable gene variants showed higher CC. Meanwhile, Gene Ontology (GO) analysis implied that these candidate genes were probably related to chlorophyll biosynthesis. In addition, gene-based association analyses revealed that six variants in GRMZM2G037152, GRMZM5G816561, GRMZM2G324462, and GRMZM2G064657 genes were significantly (p-value < 0.01) correlated with CC, of which GRMZM2G064657 (encodes a phosphate transporter protein) and GRMZM5G816561 (encodes a cytochrome P450 protein) were specifically highly expressed in leaves tissues. Interestingly, these candidate genes were previously reported to involve in the regulation of the contents of chlorophyll in plants or Chlamydomonas. These results may contribute to the understanding of genetic basis and molecular mechanisms of maize CC and the selection of maize varieties with improved CC. [ABSTRACT FROM AUTHOR]

Quantifying the vertical distribution of leaf chlorophyll content (LCC) is integral for a comprehensive understanding of the physiological status and function of winter wheat crops, having significant implications for crop management and yield optimization. In this study, we investigated the vertical LCC trait of winter wheat during two consecutive field growth seasons using proximal multispectral imaging measurements to evaluate vertical variations of LCC within winter wheat canopies. The results revealed the non-uniform vertical LCC distribution varied across the entire growth season. The effects of nitrogen fertilization rate on LCC among vertical layers increased gradually from upper to lower layers of canopy. To enhance LCC prediction accuracy, this study proposes a deep transfer learning network model for leaf trait estimation (LeafTNet). It integrates the advantages of physical radiative transfer simulations with deep neural network through transfer learning. The results demonstrate that the LeafTNet achieved remarkable predictive performance and strong robustness. Furthermore, the proposed method exhibits superior estimation accuracy compared to empirical statistical method and traditional machine learning method. This study highlights the performance of LeafTNet in accurately and efficiently quantifying LCC from proximal multispectral data, which provide technical support for the estimation of the vertical distribution of leaf traits and improve crop management. [ABSTRACT FROM AUTHOR]

Drought stress is a universal crisis in sustaining the growth and production of major legumes, including the chickpea. Drought severely reduces the biomass of chickpea plants, with the effect on leaves appearing the most apparent. The aim of this study was to investigate, using various physiological and biochemical markers throughout the pod filling stage, how 78 desi chickpea genotypes tolerated drought stress. Most of the evaluated characteristics showed significant variations between control and drought treatments. The mean performance of most of the investigated parameters significantly decreased under moisture-stressed conditions. RWC, SWD, MSI, and CTD were investigated under terminal drought-stressed conditions. Except for saturated water deficit (SWD), all remaining characteristics declined with increasing stress. Genotypes SAGL152210, SAGL152252, SAGL152347, SAGL22-115, and JG11 were recognized as drought-tolerant based on physiological characteristics. Biochemical markers viz., protein content, total soluble sugar, lipid peroxidation, and proline content, had an impact on osmotic adjustment. Based on non-enzymatic biochemical traits, genotypes SAGL22-115, ICC4958, ICCV201108, ICCV201107, SAGL152252, and JG11 were identified for their capability to survive under drought-stressed conditions. H2O2 content, CAT, SOD, POD, APX, and DPPH were considered antioxidant agents. Genotypes SAGL152208, SAGL22-105, SAGL22-112, ICC201108, SAGL152278, SAGL152252, SAGL162371, SAGL162390, ICC 4958, and JG315 may be considered drought-tolerant based on antioxidant activities. These genotypes are believed to be better equipped with physio-biochemical mechanisms and antioxidant defense systems at the cellular level and can be used in breeding programs to breed drought-tolerant cultivar(s). They can also be screened in the future, allowing the line(s) that have remained consistent over time to be recognized and registered as drought-tolerant donors. [ABSTRACT FROM AUTHOR]

Key message: Ash dieback causes alterations in leaf physiology and morphology, particularly affecting the specific leaf area, which can be used to discriminate between different degrees of damage. Since the introduction of the invasive fungal pathogen Hymenoscyphus fraxineus in Europe, the European common ash (Fraxinus excelsior L.) has been threatened by ash dieback. An infection leads, for example, to typical symptoms of dying shoots, but changes of leaf physiology and morphology are still largely unexplored. Therefore, five physiological and morphological traits, chlorophyll content, chlorophyll fluorescence, specific leaf area, leaf thickness, and fluctuating asymmetry, were investigated in four different study sites in southern Germany regarding possible changes due to ash dieback and their relationship to different degrees of damage. Both higher and lower levels of chlorophyll with increasing damage due to ash dieback were observed. Chlorophyll fluorescence and fluctuating asymmetry proved to be less suitable indicators of damage. Leaf thickness showed the tendency (however not significant) of an increase in more severely damaged trees. The specific leaf area was identified as a suitable indicator of the damage severity, with significant smaller values in less healthy trees. Therefore, ash dieback can also result in notable alterations in leaf physiology and morphology. [ABSTRACT FROM AUTHOR]

Melatonin (MT) is considered as an antistress molecule that plays a constructive role in the acclimation of plants to both biotic and abiotic stress conditions. In the present study, we assessed the impact of 10 and 100 μM MT foliar spray, on chlorophyll content, and photosystem II (PSII) function, under moderate drought stress, on oregano (Origanum vulgare L.) plants. Our aim was to elucidate the molecular mechanism of MT action on the photosynthetic electron transport process. Foliar spray with 100 μM MT was more effective in mitigating the negative impact of moderate drought stress on PSII function, compared to 10 μM MT. MT foliar spray significantly improved the reduced efficiency of the oxygen-evolving complex (OEC), and PSII photoinhibition (Fv/Fm), which were caused by drought stress. Under moderate drought stress, foliar spray with 100 μM MT, compared with the water sprayed (WA) leaves, increased the non-photochemical quenching (NPQ) by 31%, at the growth irradiance (GI, 205 μmol photons m−2 s−1), and by 13% at a high irradiance (HI, 1000 μmol photons m−2 s−1). However, the lower NPQ increase at HI was demonstrated to be more effective in decreasing the singlet-excited oxygen (1O2) production at HI (−38%), in drought-stressed oregano plants sprayed with 100 μM MT, than the corresponding decrease in 1O2 production at the GI (−20%), both compared with the respective WA-sprayed leaves under moderate drought. The reduced 1O2 production resulted in a significant increase in the quantum yield of PSII photochemistry (ΦPSII), and the electron transport rate (ETR), in moderate drought-stressed plants sprayed with 100 μM MT, compared with WA-sprayed plants, but only at the HI (+27%). Our results suggest that the enhancement of PSII functionality, with 100 μM MT under moderate drought stress, was initiated by the NPQ mechanism, which decreased the 1O2 production and increased the fraction of open PSII reaction centers (qp), resulting in an increased ETR. [ABSTRACT FROM AUTHOR]

Assessing salt tolerance in plants under field conditions is a challenging task. The objective of this research was to assess the effectiveness of different methods (leaf disc assay and pot experiment) for evaluating salt tolerance in rice. Using two varieties with different salt tolerance, Changmaogu (CM) and 9311, under three NaCl levels (0, 0.3%, and 1.0%), we evaluated the photosynthetic performance in terms of chlorophyll content in leaf disc assays, as well as the photosynthetic rate (Pn), chlorophyll content, linear electron flow (LEF), and non-photochemical quenching (NPQ), in a semi-controlled pot experiment. In the leaf disc assay, CM showed a smaller decrease in chlorophyll content compared to 9311, especially under 1.0% salinity. Simultaneously, in the pot experiment, the CM variety employed flexible photosynthetic strategies, actively decreasing LEF and Pn after 5 days of salt stress (day 5) and then increasing photosynthetic capacity (chlorophyll content, LEF, and Pn) on day 10. Notably, the total chlorophyll content for the CM variety under 1.0% salinity was significantly higher than in the control, showing a 25.0% increase. Additionally, CM demonstrated NPQt sensitivity under 0.3% salinity, requiring an LEF of 150 to achieve an NPQt value of 3.0, compared to an LEF of 180 in the control. These results suggest that a simple leaf disc assay may not fully capture the adaptive mechanisms of rice plants under salinity stress. Therefore, we advocate for the use of more comprehensive methods, such as outdoor pot or field experiments, to gain a deeper understanding and more accurate evaluation of salt tolerance in rice. [ABSTRACT FROM AUTHOR]

Rice is one of the major grain crops in the world. It is of great significance to accurately inverse the chlorophyll content during growth and development in the field. However, there are some deficiencies using conventional interpretability that are driven by data inversion of the physical and chemical parameters. The leaf radiative transfer model can be expected to effectively simulate the spectral information of rice leaves, and then describe the effects of leaf parameters on spectral reflectance. A strong mechanism model can be used for the inversion of chlorophyll content of rice leaves, according to the physically driven method. The PIOSL (PROSPECT considering the internal optical structure of the leaves) model can be utilized to assume that the internal structure of the leaf blade is composed of the superposition of two layers of optical properties, which is much more in line with the actual growth of the plant. This study aims to verify the feasibility of retrieving rice leaf chlorophyll content by the PIOSL model. Firstly, the sensitivity analysis was carried out on each input parameter into the PIOSL model. The parameters Cab and Cab12 were determined as the high sensitivity in the 400-750 nm band. The inversion of chlorophyll content (Cab) was then implemented. The projection (SPA) was used to extract the features of spectral data. Five characteristic bands were sensitive to chlorophyll: 490, 575, 645, 675, and 725 nm. A multiple regression model was constructed to realize the inversion of rice leaf chlorophyll. The inversion performance of the mechanism model was then evaluated using the PIOSL model. The chlorophyll content of rice leaves was also inverted to construct an initial lookup table. LSE (least squares estimate) was used to screen the simulated sample data in the initial lookup table closer to the measured spectra. A classification prediction model was constructed using a support vector machine (SVM), in order to determine whether the combination of the screened sample parameters was in line with the actual growth of the leaves. The improved lookup table was randomly split into the training and test sets in the ratio of 7:3. The hierarchical inversion of chlorophyll content of rice leaves was performed to construct the WOA-ELM (whale optimization, WOA; extreme learning machine, ELM) inversion model. A comparison was made on the commonly-used PROSPECT model with the same data. An improved lookup table was then obtained using the PROSPECT model. The WOA-ELM model was used for the chlorophyll inversion. The results showed that the R² and RMSE of the inversion model using PIOSL-WOA-ELM were 0.977 and 2.356 μg/cm2, respectively, and the inversion accuracies of both models were above 0.9, compared with the PROSPECT-WOA-ELM model. According to the numerically driven inversion model and the physically-driven radiative transfer model, the inversion accuracy of the PIOSLWOA-ELM model was higher than that of the multivariate regression with continuous projection. Therefore, it is feasible for a more effective inversion with the radiative transfer mechanism. The finding can provide new ideas for the accurate inversion of the distribution of rice chlorophyll in the leaf, further effectively retrieving the crop physicochemical parameters. [ABSTRACT FROM AUTHOR]

The objective of this study was to determine the optimal irrigation needs of six popular Egyptian bread wheat (Triticum aestivum L.) cultivars and to establish baseline effect of reduced irrigation on yield. The varieties included were Sids1, Sids14, Sakha94, Sakha95, Gemmiza12, and Shandawee1. The experiment was conducted at two different locations, Nubaria and Sids Agricultural Research Stations, Egypt over two consecutive seasons, 2020–2021 and 2021–2022. There was a reduction in yield with the decrease in the number of irrigations. However, several cultivars performed better for yield and other traits with one less irrigation than the current irrigation practices in the region. Therefore, the study may help revise irrigation recommendations. Overall, the cultivars Sakha95, Sids1, and Sids14 were taller and had more kernels per spike, higher seed index, and greater grain yield under reduced irrigations and showed the best drought tolerance index. The tested bread wheat cultivars were genotyped using Inter-Retrotransposon Amplified Polymorphism (IRAP) and Start Codon Targeted (SCoT) markers which showed relation among the cultivars. Among the two types of markers, IRAP was better than SCoT markers for reliability and robustness. Among the six cultivars, 58% of the IRAP markers detected polymorphism as compared to 38% with SCoT markers. The two wheat cultivars Sids1 and Sids14, which performed better for important agronomic traits under water stress conditions, could be used as donors for the national wheat breeding program for drought tolerance. [ABSTRACT FROM AUTHOR]

In order to study the effects of combined application of compound fertilizer and branch fertilizer on the growth and yield of machine-transplanted rice, four hybrid rice varieties were used as experimental materials, and four fertilization treatments were set up by completely random design: compound fertilizer (T0), compound fertilizer + conventional branch fertilizer (T1), compound fertilizer + (branch fertilizer − 20%) (T2), compound fertilizer + (branch fertilizer + 20%) (T3). The results showed that the branch fertilizer could effectively promote the early growth and rapid development of tillers, and increase the agronomic traits such as chlorophyll content, LAI and dry matter accumulation. Among the four varieties, the yield of the V4 variety was the highest under T3 treatment, which was 11,471.15 kg·hm−2, which was 37.34% higher than that of the control, and the yield increase effect was the most significant. The correlations showed that dry matter accumulation and LAI were significantly or highly significantly positively correlated with the number of effective spikes and yield, and the number of effective spikes was highly significantly positively correlated with the yield. In general, the application of pitchfork fertiliser increased the effective number of spikes and the number of grains per spike of each variety to different degrees, which effectively promoted the improvement of the rice yield. [ABSTRACT FROM AUTHOR]

The objective of this work was to investigate the impact of electric current and magnetic field to the growth, yield, and seedling characteristics of chickpea by examining the response of chickpea to magnetic and electric treatments of varying intensities and durations. The ICC 30-70 seeds were obtained from the Department of Genetics and Plant Breeding and subjected to treatments involving AC magnetic flux intensities ranging from 75 mT to 125 mT for 3 and 5 minutes in the magnetic field, as well as AC electric current ranging from 75 mA to 125 mA for 30, 60, and 90 seconds treatments, separated by equal rest periods. Throughout the study, statistically significant differences were found in field emergence (84.30%), leaf area (8.62cm²), plant height (35.60cm), biological yield (10.70gm), number of pods per plant (30), and total yield per plot (118.67gm). Within the seedling parameters, all treated seeds exhibited the highest germination percentage compared to the control. Additionally, there was a favorable impact on seedling length (27.85cm), fresh weight (0.74gm), dry weight (0.30gm), and vigour indices I (2683) and II (28.71) following the seed treatment. The present study leads to the conclusion that the magnetic and electric treatments shown superior performance when compared to the control. Throughout the investigation, it was noted that the application of magnetic and electric treatments positively influenced the vegetative growth of plants. Furthermore, the dry matter partitioning showed a substantial rise in seeds treated with electric current, leading to a higher yield-per plot. [ABSTRACT FROM AUTHOR]

The effects of different drought stress levels on the plant growth, physiological and biochemical characteristics of cucumber (Cucumis sativus L.) seedlings were investigated using different mass fractions of polyethylene glycol (PEG) 6000 (0, 2.5, 5, 10%) to simulate the drought stress. The results showed that the plant height, root length, leaf dry weight (DW), stem DW, root DW, and plant DW all showed no significant difference under mild (2.5% PEG 6000) drought stress, while they exhibited a decreasing trend with an increasing level of PEG. The changing trend in the photosynthetic efficiency, chlorophyll a, and carotenoid content was consistent with the growth index under drought stress. Besides, the content of chlorophyll b in the cucumber seedlings increased under moderate (5% PEG 6000) drought stress, but decreased under severe (10% PEG 6000) drought stress. However, the antioxidase activities, soluble protein content, malondialdehyde (MDA) content, total phenols, and total flavonoid content in the cucumber seedlings increased gradually with the increase in the mass fraction of PEG. The results indicated that higher the level of drought stress, the higher inhibition on the seedling growth or more severe damage on the cell membrane, and higher contents of total phenols and flavonoids were obtained.

Abstract Potatoes (Solanum tuberosum L.) are a significant food crop cultivated around the world. Caffeic acid (CA) can enhance plant growth by promoting antioxidant activity and stimulating root development, contributing to overall plant health and vigor. Cobalt sulfate (CoSO4) boosts plant growth by promoting nitrogen (N) fixation, healthier root development, and chlorophyll synthesis, enhancing photosynthesis and overall plant health. Nanoparticle-coated urea (NPCU) improves nutrient uptake, promoting plant growth efficiency and reducing environmental impact. This study investigates the effects of combining CA, CoSO4, and NPCU as amendments on potatoes with and without NPCU. Four treatments, control, 20 μM CA, 0.15 mg/L CoSO4, and 20 μM CA + 0.15 mg/L CoSO4 with and without NPCU, were applied in four replications using a completely randomized design. Results demonstrate that the combination of CA + CoSO4 with NPCU led to an increase in potato stem length (~ 6%), shoot dry weight (~ 15%), root dry weight (~ 9%), and leaf dry weight (~ 49%) compared to the control in nutrient stress. There was a significant rise in chlorophyll a (~ 27%), chlorophyll b (~ 37%), and total chlorophyll (~ 28%) over the control under nutrient stress also showed the potential of CA + CoSO4 with NPCU. In conclusion, the findings suggest that applying CA + CoSO4 with NPCU is a strategy for alleviating potato nutrient stress.

Abstract A two-year field trial was set up to investigate the effects of applying 3 tons ha-1 of wheat (3WB) and cotton biochar (3CB) alone or in combination with chemical nitrogen (N) and phosphorus (P) fertilizers on biochemical properties, yield and nutrient content of safflower under normal irrigation and water stress (irrigation cut-off at flowering stage) conditions. The total water applied in the chemical treatments [150 kg ha−1 N + 50 kg ha−1 P (100% of the recommended dose) and 112.5N + 37.5P (75% of the recommended dose)] under water stress, was significantly higher than other treatments. Application of 112.5N + 37.5P + 3CB increased RWC from 57.5 to 59.4% and the total chlorophyll content from 80.7 to 128.1%, compared to the control. The carotenoid content, catalase and peroxidase in 112.5N + 37.5P + 3CB were lower than chemical fertilizers. Under water stress, the seed yield of 112.5N + 37.5P + 3CB was 10.2–12.6% higher than 112.5N + 37.5P + 3WB. The higher chlorophyll content, RWC, remobilization efficiency and nutrient content in 112.5N + 37.5P + 3CB compared to other treatments was associated with seed yield enhancement. The findings indicate that the combination of CB with 75% recommended dosage of N and P, may be the optimal approach for enhancing safflower production under water stress conditions.

Abstract Investigating differences in resistance to alkaline stress among three willow species can provide a theoretical basis for planting willow in saline soils. Therefore we tested three willow species (Salix matsudana, Salix gordejevii and Salix linearistipularis), already known for their high stress tolerance, to alkaline stress environment at different pH values under hydroponics. Root and leaf dry weight, root water content, leaf water content, chlorophyll content, photosynthesis and chlorophyll fluorescence of three willow cuttings were monitored six times over 15 days under alkaline stress. With the increase in alkaline stress, the water retention capacity of leaves of the three species of willow cuttings was as follows: S. matsudana > S. gordejevii > S. linearistipularis and the water retention capacity of the root system was as follows: S. gordejevii > S. linearistipularis > S. matsudana. The chlorophyll content was significantly reduced, damage symptoms were apparent. The net photosynthetic rate (Pn), rate of transpiration (E), and stomatal conductance (Gs) of the leaves showed a general trend of decreasing, and the intercellular CO2 concentration (Ci) of S. matsudana and S. gordejevii first declined and then tended to level off, while the intercellular CO2 concentration of S. linearistipularis first declined and then increased. The quantum yield and energy allocation ratio of the leaf photosystem II (PSII) reaction centre changed significantly (φPo, Ψo and φEo were obviously suppressed and φDo was promoted). The photosystem II (PSII) reaction centre quantum performance index and driving force showed a clear downwards trend. Based on the results it can be concluded that alkaline stress tolerance of three willow was as follows: S. matsudana > S. gordejevii > S. linearistipularis. However, since the experiment was done on young seedlings, further study at saplings stage is required to revalidate the results.

Abstract Drought stress can have negative impacts on crop productivity. It triggers the accumulation of reactive oxygen species, which causes oxidative stress. Limited water and nutrient uptake under drought stress also decreases plant growth. Using cobalt and fulvic acid with biochar in such scenarios can effectively promote plant growth. Cobalt (Co) is a component of various enzymes and co-enzymes. It can increase the concentration of flavonoids, total phenols, antioxidant enzymes (peroxidase, catalase, and polyphenol oxidase) and proline. Fulvic acid (FA), a constituent of soil organic matter, increases the accessibility of nutrients to plants. Biochar (BC) can enhance soil moisture retention, nutrient uptake, and plant productivity during drought stress. That’s why the current study explored the influence of Co, FA and BC on chili plants under drought stress. This study involved 8 treatments, i.e., control, 4 g/L fulvic acid (4FA), 20 mg/L cobalt sulfate (20CoSO4), 4FA + 20CoSO4, 0.50%MFWBC (0.50 MFWBC), 4FA + 0.50MFWBC, 20CoSO4 + 0.50MFWBC, 4FA + 20CoSO4 + 0.50MFWBC. Results showed that 4 g/L FA + 20CoSO4 with 0.50MFWBC caused an increase in chili plant height (23.29%), plant dry weight (28.85%), fruit length (20.17%), fruit girth (21.41%) and fruit yield (25.13%) compared to control. The effectiveness of 4 g/L FA + 20CoSO4 with 0.50MFWBC was also confirmed by a significant increase in total chlorophyll contents, as well as nitrogen (N), phosphorus (P), and potassium (K) in leaves over control. In conclusion4g/L, FA + 20CoSO4 with 0.50MFWBC can potentially improve the growth of chili cultivated in drought stress. It is suggested that 4 g/L FA + 20CoSO4 with 0.50MFWBC be used to alleviate drought stress in chili plants.

Abstract The excessive accumulation of sodium chloride (NaCl) in soil can result in soil salinity, which poses a significant challenge to plant growth and crop production due to impaired water and nutrient uptake. On the other hand, hydropriming (WP) and low level of NaCl priming can improve the germination of seeds, chlorophyll contents, oil and seed yield in plants. That’s why this study investigates the impact of hydro and different levels of NaCl (0.5, 1.0, 1.5 and 2.0%) priming, as pre-treatment techniques on canola seeds germination, growth and yield of two varieties Punjab and Faisal Canola. Results showed that, WP performed significant best for increase in germination (~ 20 and ~ 22%) and shoot length (~ 6 and ~ 10%) over non-priming (NP) in Punjab Canola and Faisal Canola respectively. A significant increase in plant height (~ 6 and ~ 7%), root length (~ 1 and ~ 7%), shoot fresh weight (~ 5 and ~ 7%), root fresh weight (~ 6 and ~ 7%) in Punjab Canola and Faisal Canola respectively. It was also observed that plants under WP and 0.5%NaCl priming were also better in production of seed yield per plant, oil contents, silique per plant, seeds per silique, and branches per plant chlorophyll contents and leaf relative water contents over NP. In conclusion, WP and 0.5%NaCl has potential to improve the germination, growth, yield and oil attributes of canola compared to non-priming, 1.0%NaCl priming, 1.5%NaCl priming and 2.0%NaCl priming.

Abstract Due to the high solubility of Cd in water, it is considered a potential toxin which can cause cancer in humans. In plants, it is associated with the development of oxidative stress due to the generation of reactive oxygen species. To overcome this issue, the roles of different plant hormones are vital. Strigolactones, one of such natural plant hormones, show promise in alleviating cadmium toxicity by mitigating its harmful effects. Acidified biochar (AB) can also effectively mitigate cadmium toxicity via ion adsorption and pH buffering. However, the combined effects of strigolactone and AB still need in-depth investigations in the context of existing literature. This study aimed to assess the individual and combined impacts of SLs (0 and 25 µM) and AB (0 and 0.75% w/w) on radish growth under Cd toxicity, i.e., 0 and 20 mg Cd/kg soil. Using a fully randomized design (CRD), each treatment was administered in four replicates. In comparison to the control under 20 mg Cd/kg soil contamination, the results showed that 25 µM strigolactone + 0.75% AB significantly improved the following: radish shoot length (~ 17%), root length (~ 47%), plant fresh weight (~ 28%), plant dry weight (~ 96%), chlorophyll a (~ 43%), chlorophyll b (~ 31%), and total chlorophyll (~ 37%). It was also noted that 0.75% AB was more pronounced in decreasing antioxidant activities than 25 µM strigolactone under 20 mg Cd/ kg soil toxicity. However, performing 25 µM strigolactone + 0.75% AB was far better than the sole application of 25 µM strigolactone and 0.75% AB in decreasing antioxidant activities in radish plants. In conclusion, by regulating antioxidant activities, 25 µM strigolactone + 0.75% AB can increase radish growth in cadmium-contaminated soils.

Abstract Salinity stress significantly hinders plant growth by disrupting osmotic balance and inhibiting nutrient uptake, leading to reduced biomass and stunted development. Using saponin (SAP) and boron (B) can effectively overcome this issue. Boron decreases salinity stress by stabilizing cell walls and membranes, regulating ion balance, activating antioxidant enzymes, and enhancing water uptake. SAP are bioactive compounds that have the potential to alleviate salinity stress by improving nutrient uptake, modulating plant hormone levels, promoting root growth, and stimulating antioxidant activity. That’s why the current study was planned to use a combination of SAP and boron as amendments to mitigate salinity stress in sweet potatoes. Four levels of SAP (0%, 0.1%, 0.15%, and 0.20%) and B (control, 5, 10, and 20 mg/L B) were applied in 4 replications following a completely randomized design. Results illustrated that 0.15% SAP with 20 mg/L B caused significant enhancement in sweet potato vine length (13.12%), vine weight (12.86%), root weight (8.31%), over control under salinity stress. A significant improvement in sweet potato chlorophyll a (9.84%), chlorophyll b (20.20%), total chlorophyll (13.94%), photosynthetic rate (17.69%), transpiration rate (16.03%), and stomatal conductance (17.59%) contrast to control under salinity stress prove the effectiveness of 0.15% SAP + 20 mg/L B treatment. In conclusion, 0.15% SAP + 20 mg/L B is recommended to mitigate salinity stress in sweet potatoes.

Abstract Salinity stress significantly impacts crops, disrupting their water balance and nutrient uptake, reducing growth, yield, and overall plant health. High salinity in soil can adversely affect plants by disrupting their water balance. Excessive salt levels can lead to dehydration, hinder nutrient absorption, and damage plant cells, ultimately impairing growth and reducing crop yields. Gallic acid (GA) and zinc ferrite (ZnFNP) can effectively overcome this problem. GA can promote root growth, boost photosynthesis, and help plants absorb nutrients efficiently. However, their combined application as an amendment against drought still needs scientific justification. Zinc ferrite nanoparticles possess many beneficial properties for soil remediation and medical applications. That’s why the current study used a combination of GA and ZnFNP as amendments to wheat. There were 4 treatments, i.e., 0, 10 µM GA, 15 μM GA, and 20 µM GA, without and with 5 μM ZnFNP applied in 4 replications following a completely randomized design. Results exhibited that 20 µM GA + 5 μM ZnFNP caused significant improvement in wheat shoot length (28.62%), shoot fresh weight (16.52%), shoot dry weight (11.38%), root length (3.64%), root fresh weight (14.72%), and root dry weight (9.71%) in contrast to the control. Significant enrichment in wheat chlorophyll a (19.76%), chlorophyll b (25.16%), total chlorophyll (21.35%), photosynthetic rate (12.72%), transpiration rate (10.09%), and stomatal conductance (15.25%) over the control validate the potential of 20 µM GA + 5 μM ZnFNP. Furthermore, improvement in N, P, and K concentration in grain and shoot verified the effective functioning of 20 µM GA + 5 μM ZnFNP compared to control. In conclusion, 20 µM GA + 5 μM ZnFNP can potentially improve the growth, chlorophyll contents and gas exchange attributes of wheat cultivated in salinity stress. More investigations are suggested to declare 20 µM GA + 5 μM ZnFNP as the best amendment for alleviating salinity stress in different cereal crops.

Plant functional traits are often considered as indicators of plant-environment relationship; however, some plant features can be highly taxonomic-specific. The study of intraspecific trait variation is essential to understand what functional traits are influenced by the phylogeny and what traits are more dependent on environment. We studied six common steppe plant species in two natural vegetation plots near lake Baikal in Southern Siberia different in climate aridity and grazing degree: site 1 - native true grass steppe under lower climate aridity, site 2 - high disturbed sagebrush steppe under higher aridity. Plant functional traits showed different relevance to species and environment. Plant height, leaf thickness (LT), mesophyll cell volume (Vcell), and the chloroplast number per cell had the greatest contribution to differences between species and varied slightly within a species. Photosynthesis (Amax) and transpiration (E) rates, chlorophyll content, mesophyll surface area per leaf area unit (Ames/A) were more dependent on environment than on species. Amax and E decreased in all studied species in more adverse conditions of site 2, however plants differed in mechanisms of these changes. In Stipa krylovii, Artemisia frigida and Potentilla acaulis, most abundant in true steppe (site 1) mesophyll cell sizes, cell and chloroplast number per leaf area decreased in site 2. Other species, Artemisia scoparia, Potentilla bifurca and Allium anisopodium which were more abundant in disturbed steppe (site 2), had larger cells and showed an increase in cell and chloroplast number per leaf area in site 2 and decrease in the photosynthetic capacity of a chloroplast. We concluded that the leaf thickness and cell size belong to species-specific features, whereas Amax, pigment content and integral mesophyll traits as Ames/A are more indicative for plant-environment relationships and their response to growth conditions depend on the ecological strategy of a species.

Long-term use of inorganic fertilizers has negatively influenced rice productivity, being unsafe environmentally. The planned strategy sought to improve rice (Oryza sativa L.) production with a quality of environment-friendly rice cultivation by reducing the excessive inorganic fertilizers. The latest research aimed to analyze the effects of liquid organic fertilizer and urea on the growth and productivity of lowland rice managed with irregular irrigation. The urea (U) comprised four doses, i.e., control 0 kg/ha (U0), 50, 100, and 150 kg/ha (U1-U3, respectively), which fertilized the main plots. The liquid organic fertilizer (LOF) (P) also comprised four levels, viz., control 0 cc/L (P0), 2, 4, and 6 cc/L of water (P1-P3, respectively), which treated the subplots. The urea (100 kg/ha) application resulted in the highest average number of productive tillers (16.8) and the topmost percentage of full grain (84.47%). However, the urea fertilizer (150 kg/ha) produced the maximum flag leaf length (32.3 cm). The LOF concentration (4 cc/L) produced the superior 100-grain weight (2.84 g). The LOF (6 cc/L) produced the utmost index of chlorophyll a (236.43 μmol/m2), chlorophyll b (95.83 μmol.m-2), and total chlorophyll (339.64 μmol.m-2). The results showed that the combination of urea fertilizer (150 and 100 kg/ha) and liquid organic fertilizer concentration (LOF 6 cc/L) provided the best productivity of 6.26 and 6.13 t/ha, respectively. [ABSTRACT FROM AUTHOR]

Heat stress is a major environmental stress that affects the growth and development of plants. Korean fir (Abies koreana), a rare species endemic to South Korea, is sensitive to global climate change. The effect of exogenous methyl jasmonate (MeJA) on heat stress tolerance was, therefore, investigated in this species. During heat stress, the expression levels of eight genes (AkNAC19, AkMPK6, AkERF4, AkEFP, AkNAC2, AkbHLH, AkHSP17.6, and AkMYB123) were assessed in needles of A. koreana following treatment with 0, 0.1, 1.0, or 2.0 mM MeJA. Optimal upregulation of expression of most genes was observed 24 h post-treatment with 2.0 mM MeJA. Similar results were obtained when gene expression was analyzed 1, 2, 4, and 8 days post-treatment with 2.0 mM MeJA. Under heat stress conditions, plants treated with 2.0 mM MeJA initially showed a rapid decline in electrolyte leakage and higher chlorophyll content after 28 days of heat stress; however, opposite trends were observed in untreated plants, indicating that MeJA mediated tolerance to heat stress. Higher levels of expression of AkERF4, AkNAC2, and AkHSP17.6 were observed in MeJA-treated needles than in untreated needles, indicating these genes were strongly associated with MeJA-mediated heat tolerance. Therefore, these results suggest that the ability of Korean fir to tolerate abiotic stress is associated with endogenous MeJA synthesis or signaling, and identifies AkERF4, AkNAC2, and AkHSP17.6 as potential candidates for genes involved in the stress-tolerance mechanism. [ABSTRACT FROM AUTHOR]

Blue honeysuckle (Lonicera caerulea L.) is a deciduous shrub with perennial rootstock found in China. The objectives of this study were to explore the drought tolerance of blue honeysuckle, determine the effect of drought stress on two photosystems, and examine the mechanism of acquired drought tolerance. In this study, blue honeysuckle under four levels of simulated field capacity (100%, 85%, 75%, and 65% RH) was grown in split-root pots for drought stress treatment, for measuring the changes in chlorophyll content, photosynthetic characteristics, and leaf chlorophyll fluorescence parameters. The chlorophyll content of each increased under mild stress and decreased under moderate and severe stress. The net photosynthetic rate, transpiration rate, intercellular carbon dioxide concentration, and stomatal conductance of blue honeysuckle decreased with the increase in water stress. However, the water utilization rate and stomatal limit system increased under mild and moderate stress and decreased under severe stress. The maximum fluorescence (Fm), maximum photochemical efficiency, and quantum efficiency of photosystem II decreased with the decrease in soil water content, and the initial fluorescence increased significantly (p < 0.01). With the decrease in soil water content, the energy allocation ratio parameters decreased under severe drought stress. The main activity of the unit reaction center parameters first increased and then decreased. ABS/CSm, TRo/CSm, ETo/CSm, and REo/CSm gradually declined. After a comprehensive analysis, the highest scores were obtained under adequate irrigation (CK). Overall, we concluded that the water irrigation system of blue honeysuckle should be considered adequate. [ABSTRACT FROM AUTHOR]

In the face of escalating environmental challenges, understanding crop responses to abiotic stress is pivotal for sustainable agriculture. The present studymeticulously investigates the intricate interplay between drought and salinity stress in barley (Hordeum vulgare L.). Employing three distinct barley genotypes--Traveller, Prunella, and Zahna--we scrutinize their physiological, biochemical, and molecular adaptations under stress conditions. Our findings underscore genotype-specific responses, unravelling the multifaceted mechanisms that govern stress tolerance. Chlorophyll content, a vital indicator of photosynthetic efficiency, exhibits significant variations across genotypes. Salinity stress induces a decline in chlorophyll levels, while drought stress triggers a more nuanced response. Stomatal conductance, a key regulator of water loss, also diverges among the genotypes. Traveller displays remarkable stomatal closure under drought, conserving water, whereas Prunella and Zahna exhibit contrasting patterns. Antioxidant enzyme activities, crucial for combating oxidative stress, fluctuate significantly. Activities of superoxide dismutase (SOD) and catalase (CAT) surge under salinity stress, while drought predominantly impacts SOD. Gene expression profiling reveals genotype-specific signatures, with stress-responsive genes modulating adaptive pathways. Correlation analyses revealed the intricate interplay of the physiological and biochemical parameters. Genotype-specific adaptations, coupled with dynamic physiological and molecular responses, underscore the plasticity of barley's stress tolerance mechanisms. Throughout the study, the Zahna genotype demonstrated notable tolerance in terms of performance. These insights hold promise for breeding resilient cultivars, bolstering food security in an increasingly unpredictable climate. By deciphering the barley stress symphony, we contribute to the harmonious orchestration of sustainable agricultural practices. [ABSTRACT FROM AUTHOR]

The accumulation of cadmium (Cd) in plants poses a major risk to consumer health, in addition to affecting plant growth, development and quality. The study aimed to examine the effects of cadmium on the plants' ability for photosynthesis and antioxidant enzyme activity. In this study, radishes were planted in Petri dishes and pots containing soil supplemented with different concentrations of cadmium sulphate (25, 50, and 100 mg Cd kg-1 soil). The results showed that the percentage of germination, seedlings length, and fresh and dry matter significantly declined its increasing cadmium concentrations. In addition, cadmium hindered plant growth, as evidenced by the fresh and dried weight of radish roots and leaves after a 100 mg Cd kg-1 soil treatment. There was also a notable decrease in chlorophyll a and chlorophyll b, total chlorophyll, and total leaf area per plant. The leaves of radish plant exhibited a significant increase in lipid peroxidation and electrolyte leakage contents under Cd stress, while, the relative water content (RWC) decreased. However, leaves and roots of radish plant showed a considerable increase in antioxidant enzymes (catalase; CAT, peroxidase; POD, and superoxide dismutase; SOD). Furthermore, radish showed a significant increase in Cd accumulation in all applications, however, there were no obvious symptoms of Cd toxicity following the 25 and 50 mg Cd kg-1 soil applications. In conclusion, the radish plants accumulated cadmium at higher concentrations (100 mg Cd kg-1 soil). So, we recommended cultivating the radish plants in soil that has low concentrations of cadmium. [ABSTRACT FROM AUTHOR]

Developing new bread wheat varieties that can be successfully grown in saline conditions has become a pressing task for plant breeders. High-throughput phenotyping tools are crucial for this task. Proximal remote sensing is gaining popularity in breeding programs as a quick, cost-effective, and non-invasive tool to assess canopy structure and physiological traits in large genetic pools. Limited research has been conducted on the effectiveness of combining RGB and thermal imaging to assess the salt tolerance of different wheat genotypes. This study aimed to evaluate the effectiveness of combining several indices derived from thermal infrared and RGB images with artificial neural networks (ANNs) for assessing relative water content (RWC), chlorophyll a (Chla), chlorophyll b (Chlb), total chlorophyll (Chlt), and plant dry weight (PDW) of 18 recombinant inbred lines (RILs) and their 3 parents irrigated with saline water (150 mM NaCl). The results showed significant differences in various traits and indices among the tested genotypes. The normalized relative canopy temperature (NRCT) index exhibited strong correlations with RWC, Chla, Chlb, Chlt, and PDW, with R2 values ranging from 0.50 to 0.73, 0.53 to 0.76, 0.68 to 0.84, 0.68 to 0.84, and 0.52 to 0.76, respectively. Additionally, there was a strong relationship between several RGB indices and measured traits, with the highest R2 values reaching up to 0.70. The visible atmospherically resistant index (VARI), a popular index derived from RGB imaging, showed significant correlations with NRCT, RWC, Chla, Chlb, Chlt, and PDW, with R2 values ranging from 0.49 to 0.62 across two seasons. The different ANNs models demonstrated high predictive accuracy for NRCT and other measured traits, with R2 values ranging from 0.62 to 0.90 in the training dataset and from 0.46 to 0.68 in the cross-validation dataset. Thus, our study shows that integrating high-throughput digital image tools with ANN models can efficiently and non-invasively assess the salt tolerance of a large number of wheat genotypes in breeding programs. [ABSTRACT FROM AUTHOR]

Plants, being sessile organisms, rely on their antioxidant systems to respond to the stress factors induced by both abiotic and biotic stresses in their environment. Among abiotic stress factors, salinity and alkalinity pose the most significant challenges to plant growth. To counteract these stresses, plants activate various signalling pathways to enhance their stress tolerance. While a wide range of pesticides, including insecticides and herbicides, are employed to protect agricultural crops from biotic agents, there exists no established practice for fortifying their defence mechanisms against abiotic stresses. This study delves into the effect of H2O2 pre-treatment on mitigating salt stress in tomato seedlings. Four experimental groups were established: control, H2O2, Salt, and Salt+H2O2. The study evaluated changes in chlorophyll content, malondialdehyde (MDA) accumulation, superoxide dismutase (SOD), catalase (CAT), and ascorbate peroxidase (APX) enzyme activities and expressions. The results revealed that priming treatment led to increased chlorophyll levels and reduced MDA accumulation compared to the group only exposed to salt stress. Additionally, the activation of stress-related enzymes was significantly higher in the priming group compared to the group only exposed to salt stress. Expression levels exhibited a statistically significant increase compared to the control group; however, CAT and APX expression levels were found to be lower than those in the the group only exposed to salt stress. These findings suggest that H2O2 priming can enhance plant stress tolerance. Priming can serve as a highly effective tool to alleviate stress in plants; however, the type, concentration, and exposure time of the priming agent are crucial factors in regulating the priming effect. [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]

The spectrophotometer method is costly, time-consuming, laborious, and destructive to the plant. Samples will be lost during the transportation process, and the method can only obtain sample point data. This poses a challenge to the estimation of chlorophyll content at the regional level. In this study, in order to improve the estimation accuracy, a new method of collaborative inversion of chlorophyll using Landsat 8 and Global Ecosystem Dynamics Investigation (GEDI) is proposed. Specifically, the chlorophyll content data set is combined with the preprocessed two remote-sensing (RS) factors to construct three regression models using a support vector machine (SVM), BP neural network (BP) and random forest (RF), and the better model is selected for inversion. In addition, the ordinary Kriging (OK) method is used to interpolate the GEDI point attribute data into the surface attribute data for modeling. The results showed the following: (1) The chlorophyll model of a single plant was y = 0.1373x1.7654. (2) The optimal semi-variance function models of pai, pgap_theta and pgap_theta_a3 are exponential models. (3) The top three correlations between the two RS data and the chlorophyll content were B2_3_SM, B2_3_HO, B2_5_EN and pai, pgap_theta, pgap_theta_a3. (4) The combination of the Landsat 8 imagery and GEDI resulted in the highest modeling accuracy, and RF had the best performance, with R2, RMSE and P values of 0.94, 0.18 g/m2 and 83.32%, respectively. This study shows that it is reliable to use Landsat 8 images and GEDI to retrieve the chlorophyll content of Dendrocalamus giganteus (D. giganteus), revealing the potential of multi-source RS data in the inversion of forest ecological parameters. [ABSTRACT FROM AUTHOR]

In aquatic ecological restoration projects, V. natans (Vallisneria natans (Lour.) Hara), a species of submergent plant, after being transplanted often experiences a poor growing condition and a lengthy adaption period, however, brassinolides possess considerable effectiveness of plant development and metabolism according to available research reports. In an attempt to employ a phytohormone soaking pre-treatment method to study the effect of brassinolides' effect on V. natans development, a laboratory experiment was conducted probing into the influencing factors: brassinolides dosage (0, 0.25, 0.5, 1, 2 and 4 mg/L) and soaking time (10, 20, and 40 minutes). The results showed that the pre-treatment with brassinolide facilitated the improvement to some extent of biomass, plant height, number of leaves, number of tillers, and chlorophyll of V. natans, and that the effect of soaking solution concentration was more pronounced than immersion time; it appeared that under the condition of above three soaking intervals the biomass of V. natans increased to the maximum at the solution concentration of 0.5 mg/L; however, 10 min soaking time gave rise to biggst boosting effect, and from the perspective of plant height indicator, as the soaking time was 10 min brassinolide of 0.25-2 mg/L concentration had a notable positive effect on the plant height of V. natans (P<0.05). In terms of chlorophyll indicators, it was the best condition that the content of chlorophyll a and chlorophyll b of V. natans was boosted when brassinolide concentration ranged 0.5-1 mg/L and soaking time was 10 min. In accordance with the experimental data obtained and considering economic cost and time cost, it is recommended that prior to the transplantation V. natans be soaked with brassinolide at a concentration of 0.5 mg/L for 10 min, in this way the problem of V. natans colonizationcan could be successfully solved. Finally, it is expected that the experimental results could provide theoretical references for the quick recovery of submerged macrophytes in aquatic environment. [ABSTRACT FROM AUTHOR]

As a vital pigment for photosynthesis in rice, chlorophyll content is closely correlated with growth status and photosynthetic capacity. The estimation of chlorophyll content allows for the monitoring of rice growth and facilitates precise management in the field, such as the application of fertilizers and irrigation. The advancement of hyperspectral remote sensing technology has made it possible to estimate chlorophyll content non-destructively, quickly, and effectively, offering technical support for managing and monitoring rice growth across wide areas. Although hyperspectral data have a fine spectral resolution, they also cause a large amount of information redundancy and noise. This study focuses on the issues of unstable input variables and the estimation model's poor applicability to various periods when predicting rice chlorophyll content. By introducing the theory of harmonic analysis and the time-frequency conversion method, a deep neural network (DNN) model framework based on wavelet packet transform-first order differential-harmonic analysis (WPT-FD-HA) was proposed, which avoids the uncertainty in the calculation of spectral parameters. The accuracy of estimating rice chlorophyll content based on WPT-FD and WPT-FD-HA variables was compared at seedling, tillering, jointing, heading, grain filling, milk, and complete periods to evaluate the validity and generalizability of the suggested framework. The results demonstrated that all of the WPT-FD-HA models' single-period validation accuracy had coefficients of determination (R2) values greater than 0.9 and RMSE values less than 1. The multi-period validation model had a root mean square error (RMSE) of 1.664 and an R2 of 0.971. Even with independent data splitting validation, the multi-period model accuracy can still achieve R2 = 0.95 and RMSE = 1.4. The WPT-FD-HA-based deep learning framework exhibited strong stability. The outcome of this study deserves to be used to monitor rice growth on a broad scale using hyperspectral data. [ABSTRACT FROM AUTHOR]

The rapid and accurate estimation of leaf chlorophyll content (LCC), an important indicator of crop photosynthetic capacity and nutritional status, is of great significance for precise nitrogen fertilization management. To explore the existence of a versatile regression model that can be successfully used to estimate the LCC for different varieties under different growth stages and nitrogen stress conditions, a study was conducted in 2023 across the growing season for winter wheat with five species and five nitrogen application levels. Two machine learning regression algorithms, support vector machine (SVM) and random forest (RF), were used to establish the bridge between UAV-derived multispectral vegetation indices and ground truth LCC (relative chlorophyll content, SPAD), taking the multivariate linear regression (MLR) algorithm as a reference. The results show that the visible atmospherically resistant index, vegetative index, and normalized difference vegetation index had the highest correlation with ground truth LCC, with a Pearson's correlation coefficient of 0.95. All three regression algorithms (MLR, RF, and SVM) performed well on the training dataset (R2: 0.932–0.944, RMSE: 3.96 to 4.37), but performed differently on validation datasets with different growth stages, species, and nitrogen application levels. Compared to winter wheat species and nitrogen application levels, the growth stages had the greatest influence on the generalization ability of LCC estimation models, especially for the dough stage. At the dough stage, compared to MLR and RF, SVM performed best, with R2 increasing by 0.27 and 0.10, respectively, and RMSE decreasing by 1.13 and 0.46, respectively. Overall, this study demonstrated that the combination of UAV-derived multispectral VIs and the SVM regression algorithm could be successfully applied to map the LCC of winter wheat for different species, growth stages, and nitrogen stress conditions. Ultimately, this research is significant as it shows the successful application of UAV data for mapping the LCC of winter wheat across diverse conditions, offering valuable insights for precision nitrogen fertilization management. [ABSTRACT FROM AUTHOR]

Leaf chlorophyll content (LCC) is an important indicator of plant nutritional status and can be a guide for plant disease diagnosis. In this study, we took apple leaves infected with mosaic disease as a research object and extracted two types of information on spectral and textural features from hyperspectral images, with a view to realizing non-destructive detection of LCC. First, the collected hyperspectral images were preprocessed and spectral reflectance was extracted in the region of interest. Subsequently, we used the successive projections algorithm (SPA) to select the optimal wavelengths (OWs) and extracted eight basic textural features using the gray-level co-occurrence matrix (GLCM). In addition, composite spectral and textural metrics, including vegetation indices (VIs), normalized difference texture indices (NDTIs), difference texture indices (DTIs), and ratio texture indices (RTIs) were calculated. Third, we applied the maximal information coefficient (MIC) algorithm to select significant VIs and basic textures, as well as the tandem method was used to fuse the spectral and textural features. Finally, we employ support vector regression (SVR), backpropagation neural network (BPNN), and K-nearest neighbors regression (KNNR) methods to explore the efficacy of single and combined feature models for estimating LCC. The results showed that the VIs model (R2 = 0.8532, RMSE = 2.1444, RPD = 2.6179) and the NDTIs model (R2 = 0.7927, RMSE = 2.7453, RPD = 2.2032) achieved the best results among the single feature models for spectra and texture, respectively. However, textural features generally exhibit inferior regression performance compared to spectral features and are unsuitable for standalone applications. Combining textural and spectral information can potentially improve the single feature models. Specifically, when combining NDTIs with VIs as input parameters, three machine learning models outperform the best single feature model. Ultimately, SVR achieves the highest performance among the LCC regression models (R2 = 0.8665, RMSE = 1.8871, RPD = 2.7454). This study reveals that combining textural and spectral information improves the quantitative detection of LCC in apple leaves infected with mosaic disease, leading to higher estimation accuracy. [ABSTRACT FROM AUTHOR]

Due to the high solubility of Cd in water, it is considered a potential toxin which can cause cancer in humans. In plants, it is associated with the development of oxidative stress due to the generation of reactive oxygen species. To overcome this issue, the roles of different plant hormones are vital. Strigolactones, one of such natural plant hormones, show promise in alleviating cadmium toxicity by mitigating its harmful effects. Acidified biochar (AB) can also effectively mitigate cadmium toxicity via ion adsorption and pH buffering. However, the combined effects of strigolactone and AB still need in-depth investigations in the context of existing literature. This study aimed to assess the individual and combined impacts of SLs (0 and 25 µM) and AB (0 and 0.75% w/w) on radish growth under Cd toxicity, i.e., 0 and 20 mg Cd/kg soil. Using a fully randomized design (CRD), each treatment was administered in four replicates. In comparison to the control under 20 mg Cd/kg soil contamination, the results showed that 25 µM strigolactone + 0.75% AB significantly improved the following: radish shoot length (~ 17%), root length (~ 47%), plant fresh weight (~ 28%), plant dry weight (~ 96%), chlorophyll a (~ 43%), chlorophyll b (~ 31%), and total chlorophyll (~ 37%). It was also noted that 0.75% AB was more pronounced in decreasing antioxidant activities than 25 µM strigolactone under 20 mg Cd/ kg soil toxicity. However, performing 25 µM strigolactone + 0.75% AB was far better than the sole application of 25 µM strigolactone and 0.75% AB in decreasing antioxidant activities in radish plants. In conclusion, by regulating antioxidant activities, 25 µM strigolactone + 0.75% AB can increase radish growth in cadmium-contaminated soils. [ABSTRACT FROM AUTHOR]

Salinity stress significantly impacts crops, disrupting their water balance and nutrient uptake, reducing growth, yield, and overall plant health. High salinity in soil can adversely affect plants by disrupting their water balance. Excessive salt levels can lead to dehydration, hinder nutrient absorption, and damage plant cells, ultimately impairing growth and reducing crop yields. Gallic acid (GA) and zinc ferrite (ZnFNP) can effectively overcome this problem. GA can promote root growth, boost photosynthesis, and help plants absorb nutrients efficiently. However, their combined application as an amendment against drought still needs scientific justification. Zinc ferrite nanoparticles possess many beneficial properties for soil remediation and medical applications. That's why the current study used a combination of GA and ZnFNP as amendments to wheat. There were 4 treatments, i.e., 0, 10 µM GA, 15 μM GA, and 20 µM GA, without and with 5 μM ZnFNP applied in 4 replications following a completely randomized design. Results exhibited that 20 µM GA + 5 μM ZnFNP caused significant improvement in wheat shoot length (28.62%), shoot fresh weight (16.52%), shoot dry weight (11.38%), root length (3.64%), root fresh weight (14.72%), and root dry weight (9.71%) in contrast to the control. Significant enrichment in wheat chlorophyll a (19.76%), chlorophyll b (25.16%), total chlorophyll (21.35%), photosynthetic rate (12.72%), transpiration rate (10.09%), and stomatal conductance (15.25%) over the control validate the potential of 20 µM GA + 5 μM ZnFNP. Furthermore, improvement in N, P, and K concentration in grain and shoot verified the effective functioning of 20 µM GA + 5 μM ZnFNP compared to control. In conclusion, 20 µM GA + 5 μM ZnFNP can potentially improve the growth, chlorophyll contents and gas exchange attributes of wheat cultivated in salinity stress. More investigations are suggested to declare 20 µM GA + 5 μM ZnFNP as the best amendment for alleviating salinity stress in different cereal crops. [ABSTRACT FROM AUTHOR]

Hyperspectral remote sensing technology plays a vital role in advancing modern precision agriculture due to its non-destructive and efficient nature. To achieve accurate monitoring of winter wheat chlorophyll content, this study utilized 68 sets of chlorophyll content data and hyperspectral measurements collected during the jointing stage of winter wheat over two consecutive years (2019–2020), under various fertilization types and nitrogen application levels. Continuous wavelet transform was applied to transform the original reflectance, ranging from 21 to 210, and the correlation matrix method was utilized to identify the spectral index at each scale, with the highest correlation to winter wheat chlorophyll content as the optimal spectral index combination input. Subsequently, winter wheat chlorophyll content prediction models were developed using three machine learning methods: random forest (RF), support vector machine (SVM), and a genetic algorithm-optimized backpropagation neural network (GA-BP). The results indicate that the spectral data processed through continuous wavelet transform at seven scales, from 21 to 27, show the highest correlation with winter wheat chlorophyll content at a scale of 26, with a correlation coefficient of 0.738, compared with the correlation of 0.611 of the original reflectance, and the accuracy is improved by 20.7%. The average highest correlation value between the spectral index at scale 26 and winter wheat chlorophyll content is 0.752. As the scale of wavelet transform increases, the correlation between the spectral index and winter wheat chlorophyll content and the accuracy of the predictive model show a trend of first increasing and then decreasing. The optimal input variables for predicting winter wheat chlorophyll content and the best machine learning method are the spectral data at a scale of 26 processing combined with the GA-BP model. The optimal predictive model has a validation set coefficient of determination (R2) of 0.859, root mean square error (RMSE) of 1.366, and mean relative error (MRE) of 2.920%. The results show that the prediction model can provide a technical basis for improving the hyperspectral inversion accuracy of winter wheat chlorophyll and modern precision agriculture. [ABSTRACT FROM AUTHOR]

Cool-season plant growth and development are impacted by high temperatures. As a biostimulant, glycine betaine is responsible for inducing tolerance to both biotic and abiotic stressors. However, the mechanism by which glycine betaine protects cool-season crops against high-temperature stress is not clear. In the present study, under the conditions of high temperatures (35 °C/30 °C day/night), cherry radishes (Raphanus sativus var. radicula Pers.) (Brassicaceae) were cultured for 9, 18, and 27 days, and different concentrations (0, 0.067, 8.79, 11.72, 14.65, and 17.58 mg L−1) of glycine betaine were applied to investigate the influence of glycine betaine on cherry radish biomass, quality, net photosynthetic rate, chlorophyll content, antioxidant enzyme activity, and endogenous hormone content under high-temperature stress. The results showed that, under high-temperature conditions, cherry radishes grew best with the 17.58 mg L−1 glycine betaine treatment. At day 27, comparing the 17.58 mg L−1 glycine betaine treatment with 0 mg L−1 glycine betaine under high-temperature stress, the cherry radish biomass increased by 44.7%, while the soluble protein and vitamin C content increased by 14.4% and 21.6%, respectively, the net photosynthetic rate and chlorophyll a content increased by 7.8% and 44.1%, respectively, and the peroxidase and catalase levels increased by 81.0% and 146.3%, respectively. On day 9, the auxin, abscisic acid, and glycine betaine contents significantly increased by 67.4%, 6.8%, and 32.9%, respectively, in comparing the 17.58 mg L−1 glycine betaine treatment with 0 mg L−1 glycine betaine under high-temperature stress. Therefore, the application of 17.58 mg L−1 betaine to cherry radishes grown under high-temperature stress had positive effects. The appropriate concentration of glycine betaine can improve the resistance of cherry radish to high temperatures and maintain yield. [ABSTRACT FROM AUTHOR]

Despite global warming, the response of rice yield to long-term warming in cool regions and its physiological mechanisms remain unknown. This study used the widely cultivated japonica rice Jiyang100 in Northeast China. Taking rice grown under natural temperatures as a control (CK), field warming treatments were conducted at the tillering-panicle initiation (T1), whole growth (T2), and grain-filling (T3) stages. The positive effects of T1, T2, and T3 on the total number of spikelets per hole increased the yield in both years, with average increases of 11.5%, 9.9% and 6.5% compared to CK, respectively. Warming treatments improved the stay-green traits, photosynthesis, sucrose synthesis, and nitrogen metabolism of rice. The yield was positively correlated with the relative chlorophyll content (SPAD), soluble sugar content, sucrose content, and the activities of sucrose phosphate synthase (SPS), nitrate reductase (NR), glutamine synthetase (GS), glutamine oxoglutarate aminotransferase (GOGAT) in flag leaves. In addition, SPAD had a positive correlation with soluble sugar content, soluble protein content, and the activities of NR, GS, GOGAT, glutamate dehydrogenase (GDH), but a negative correlation with acid invertase (AI) activity. The stay-green ability was positively correlated to the net photosynthetic rate (Pn), soluble sugar content and soluble protein content. The coupling interactions of stay-green traits, nitrogen and carbon metabolism increased the yield potential and yield supply capacity, increased yield under long-term warming conditions in the cool regions. Under gradual warming, the physiological response of rice in cool regions promotes plant growth and development, thereby increasing yield. [ABSTRACT FROM AUTHOR]

This study presents a novel Spectral Triad feature selection (STfs) technique based on music theory and compares it to the entire Sentinel-2 feature space and Random Forest-Recursive Feature Elimination (RF-RFE). The optimal subsets were evaluated with Random Forest for retrieving Leaf Area Index (LAI), Leaf Chlorophyll Content (LCab), and Canopy Chlorophyll Content (CCC) in a semi-arid agricultural landscape. The results indicated that the proposed STfs algorithm obtained equivalent or better (i.e. by 1 - 3%) retrieval accuracies for LAI (R2 cv of 66%, root mean squared error of cross-validation [RMSEcv] of 0.53 m2 m-2), LCab (R2 cv: 74%, RMSEcv: 7.09 mg cm-2) and CCC (R2 cv: 77%, RMSEcv: 33.69 mg cm-2), using only 5, 7 and 7 variables, respectively, when compared to RF-RFE and entire Sentinel-2 feature space. Overall, the proposed STfs algorithm has great potential to optimize the spectral feature space of quasi-hyperspectral sensors for rapid crop biophysical and biochemical parameter retrieval. [ABSTRACT FROM AUTHOR]