Crop Plants Research Articles

Optimizing germination dynamics in seven key industrial and medicinal hemp varieties through seed priming techniques: An initial study for hemp cultivation in Pakistan

Seed germination is crucial for studying factors influencing production conditions since it represents the initial physiological stage of the plant's life cycle. Hemp seeds are grown to obtain cannabinoids; however, these varieties, hybrids, and feminized seeds are costly in the market with low germination rates. Therefore, optimizing the germination of hemp seeds can play an important role in maintaining plant populations and crop establishment and can reduce seed costs. This study was aimed at evaluating the germination potential of seven hemp varieties/cultivars (Cannabis sativa L.) in response to priming with Indole Butyric Acid (IBA), moringa leaf crude extract, hydro-priming, and a control. Results showed that IBA at 1000 ppm significantly improved germination rates; while the hydro-priming exhibited the fastest germination across all varieties/cultivars. Two cultivars viz., Santhica-70 and Fedora-17 exhibited the highest germination percentages of 83% and 77%, respectively with IBA treatment; while CBD Pink Kush exhibited a germination rate of 63%. This study represents the first comprehensive investigation into seed germination and seedling growth of hemp varieties, offering insights into optimized priming agent selection for industrial and medicinal hemp crop cultivation in Pakistan, highlighting the importance of variety-specific traits and priming techniques for maximizing crop yield.

OsKANADI1 and OsYABBY5 regulate rice plant height by targeting GIBERELLIN 2-OXIDASE6.

Plant height is an important agronomic characteristic of rice (Oryza sativa L.). Map-based cloning analyses of a natural semi-dwarf rice mutant with inwardly curled leaves found in the field revealed that the defects were due to a mutation of a SHAQKYF-class MYB family transcription factor, OsKANADI1 (OsKAN1). OsKAN1 directly bound to the OsYABBY5 (OsYAB5) promoter to repress its expression and interacted with OsYAB5 to form a functional OsKAN1-OsYAB5 complex. GIBERELLIN 2-OXIDASE6 (OsGA2ox6), encoding an enzyme in the gibberellin (GA) catabolic pathway, was activated by OsYAB5. Furthermore, the OsKAN1-OsYAB5 complex suppressed the inhibitory effect of OsKAN1 toward OsYAB5 and inhibited OsYAB5-induced OsGA2ox6 expression. The proOsKAN1:OsYAB5 transgenic plants were taller than wild-type plants, whereas oskan1 proOsKAN1:OsYAB5 plants exhibited a severe dwarf phenotype due to the absence of the OsKAN1-OsYAB5 complex. The OsKAN1-OsYAB5 complex modulated OsGA2ox6 expression, thereby regulating the levels of bioactive gibberellins and, consequently, plant height. This study elucidated the mechanism underlying the effect of the OsKAN1-OsYAB5-OsGA2ox6 regulatory pathway on plant height at different positions in rice stems and provided insights on stem development and candidate genes for the aerial architecture improvement of crop plants.

DNA Damage, Cell Death, and Alteration of Cell Proliferation Insights Caused by Copper Oxide Nanoparticles Using a Plant-Based Model.

The speedy growth of copper oxide nanoparticle (CuO NP) manufacturing due to their wide application in industries has caused concerns due to their increased discharge into the environment from both purposeful and accidental sources. Their presence at an elevated concentration in the environment can cause potential hazards to the plant kingdom, specifically to staple food crops. However, limited research is available to determine the consequences of CuO NPs. The present study aimed to assess the morphological and cytological changes induced by CuO NPs on Pisum sativum L., a key staple food crop. Seeds of Pisum sativum were exposed to various concentrations of CuO NPs (0, 25, 50, 75, 100, and 125 ppm) for 2 h, and their effects on seed germination (SG), radicle length (RL), cell proliferation kinetics (CPK), mitotic index (MI), cell death (CD), micronucleus frequency (MNF), and chromosomal aberration frequency (CAF) were studied. The results indicate a significant reduction in SG, RL, CPK, and MI and a significant dose-dependent increase in CD, MNF, and CAF. CuO NP treatment has led to abnormal meiotic cell division, increased incidence of micronucleus frequency, and chromosomal aberration frequency. Additionally, the CuO NP-treated groups showed an increase in the percentage of aberrant meiotic cells such as laggard (LG), double bridge (DB), stickiness (STC), clumped nuclei (CNi), precocious separation (PS), single bridge (SB), and secondary association (SA). CuO NP treatment led to reductions in SG as follows: 55% at 24 h, 60.10% at 48 h, and 65% at 72 h; reductions in RL as follows: 0.55 ± 0.021 cm at 24 h, 0.67 ± 0.01 cm at 48 h, and 0.99 ± 0.02 cm at 72 h; reductions in CPK as follows: 34.98% at prophase, 7.90% at metaphase, 3.5% at anaphase, and 0.97% at telophase. It also led to a 57.45% increase in CD, a 39.87% reduction in MI, and a 60.77% increase in MNF at a higher concentration of 125 ppm. The findings of this study clearly show that CuO NPs have a genotoxic effect on the food crop plant Pisum sativum.

An asymptomatic geminivirus activates autophagy and enhances plant defenses against diverse pathogens

Plant viral diseases cause great losses in agricultural production. Virus cross-protection is a strategy in which a mild virus is employed to shield plants against subsequent infections by severe viral strains. However, this approach is restricted to protection against the same viruses. In this study, we observed that pre-inoculation with apple geminivirus (AGV) reduced the accumulation of secondarily infected heterologous viruses, such as cucumber mosaic virus, potato virus X, and tobacco mosaic virus in Nicotiana benthamiana, tomato, and pepper plants. Transcriptional expression analysis showed that autophagy-related genes were transcriptionally up-regulated upon AGV inoculation at an early stage of infection. Accordingly, autophagic activity was observed to be elevated following AGV infection. Interestingly, AGV accumulation was reduced in autophagy-deficient plants, suggesting that autophagy activation promotes AGV infection in the plant. Moreover, pre-inoculation with AGV provided cross-protection against infection with a phytopathogenic bacterium (Pseudomonas syringae) and fungus (Botrytis cinerea) in Nicotiana species. In summary, our study showed that AGV, an asymptomatic virus, could protect plants against severe viral, fungal, and bacterial diseases to some extent through the activation of autophagy pathways, highlighting its potential as a biocontrol agent for managing a wide range of plant crop diseases in the field.

Estimating Energy Needs for Climate-Controlled Greenhouses in Syria with a Software Tool

Amid the current conditions in Syria, the study of energy consumption within plastic greenhouses emerges as a fundamental element in the agricultural economy, especially in areas subject to extreme climate variations. With many thermal power stations ceasing operation due to conflicts and the diminishing sources of energy, understanding energy consumption becomes more urgent to enhance productivity and reduce costs. Successful management of protected agriculture requires in-depth knowledge of weather dynamics and the optimal environmental conditions for crops. To implement effective management of plastic greenhouses, it is essential to recognize how climatic fluctuations affect plant growth and production throughout the various seasons. Heating systems form a significant part of the costs in constructing plastic greenhouses, and deficiencies in these systems can lead to negative impacts on quality, quantity, duration of cultivation, and production volume. Therefore, accurately calculating heating costs is crucial for reducing operational expenses. This study included the development of a computer program to determine the heating needs of plastic greenhouses, considering various factors such as the geographical location of the greenhouse, crop type, covering materials, heating system used, and land area. The results showed that Syria needs 4.56 megawatts of energy for the greenhouses, with the Tartus Governorate consuming the largest share, with energy consumption rates in Tartus, Latakia, Homs, and Damascus countryside amounting to 3.6, 0.3, 0.51, and 0.19 megawatts, respectively. The crops of tomatoes, vegetables, strawberries, and tropical plants consumed 2.2, 1.66, 2.21, and 0.244 megawatts of energy, respectively. This study is an important step towards achieving sustainable and efficient agriculture that contributes to supporting the economy and protecting the environment in Syria.

Integrating Automated Labeling Framework for Enhancing Deep Learning Models to Count Corn Plants Using UAS Imagery.

Plant counting is a critical aspect of crop management, providing farmers with valuable insights into seed germination success and within-field variation in crop population density, both of which are key indicators of crop yield and quality. Recent advancements in Unmanned Aerial System (UAS) technology, coupled with deep learning techniques, have facilitated the development of automated plant counting methods. Various computer vision models based on UAS images are available for detecting and classifying crop plants. However, their accuracy relies largely on the availability of substantial manually labeled training datasets. The objective of this study was to develop a robust corn counting model by developing and integrating an automatic image annotation framework. This study used high-spatial-resolution images collected with a DJI Mavic Pro 2 at the V2-V4 growth stage of corn plants from a field in Wooster, Ohio. The automated image annotation process involved extracting corn rows and applying image enhancement techniques to automatically annotate images as either corn or non-corn, resulting in 80% accuracy in identifying corn plants. The accuracy of corn stand identification was further improved by training four deep learning (DL) models, including InceptionV3, VGG16, VGG19, and Vision Transformer (ViT), with annotated images across various datasets. Notably, VGG16 outperformed the other three models, achieving an F1 score of 0.955. When the corn counts were compared to ground truth data across five test regions, VGG achieved an R2 of 0.94 and an RMSE of 9.95. The integration of an automated image annotation process into the training of the DL models provided notable benefits in terms of model scaling and consistency. The developed framework can efficiently manage large-scale data generation, streamlining the process for the rapid development and deployment of corn counting DL models.

A WUSCHEL-related homeobox transcription factor, SlWOX4, negatively regulates drought tolerance in tomato.

CRISPR/Cas9-mediated knockout of SlWOX4 gene in tomato enhances tolerance to drought stress. Drought stress is one of the major abiotic factors that seriously affects plant growth and crop yield. WUSCHEL-related homeobox (WOX) transcription factors are involved in plant growth, development and stress response. However, little is known about the role of WOX genes in drought tolerance in tomato. Here, SlWOX4, a member of the WOX family in tomato, was functionally characterized in mediating drought tolerance. SlWOX4 was homologous to Nicotiana tabacum NtWOX4 with a conserved HD domain, and was localized in the nucleus. SlWOX4 was significantly down-regulated by drought and abscisic acid (ABA) treatments. The loss-of-functionmutations of SlWOX4 produced using the CRISPR-Cas9 system in tomato improved drought tolerance by reducing water loss rate and enhancing stomatal closure. In addition, the wox4 lines exhibited reduced accumulation of reactive oxygen species (ROS) and malondialdehyde (MDA), increased antioxidant enzyme activity, proline contents and ABA contents under drought stress. Moreover, gene editing of SlWOX4 in tomato enhanced drought tolerance by regulating the expression of genes encoding antioxidants and ABA signaling molecules. In summary, SlWOX4 gene might negatively regulate drought stress tolerance in tomato and has great potential as a drought-resistant crop-breeding target genes.

Greenhouse gas emissions and mitigation potential of crop production in Northeast China

Agricultural management practices that reduce greenhouse gas (GHG) emissions have been identified as effective mitigation strategies. However, research on carbon emissions from major crops in Northeast China focuses on national and provincial data, overlooking city-scale variability and uncertainties, which prevents fine-scale assessment of crop emissions reduction potential. To address this, a life cycle assessment (LCA) combined with the Monte Carlo method was conducted to estimate the carbon footprint of rice, maize, and soybean production for different cities in Northeast China from 1991 to 2020. The results showed that the top one-third of cities with the highest total carbon emissions (TCE) account for approximately 40 % of the region's TCE. Nitrogen losses and production processes related to nitrogen fertilizer application were identified as the primary contributors to TCE from crop production, accounting for 29.6–62.5 % of the total, with a relative importance of 58.5–78.2 %. Scenario analysis indicated that optimizing nitrogen fertilizer management and reducing active nitrogen losses are the most effective strategies for reducing TCE from major crop production, offering a reduction potential of 34.5–60.6 %. Recommended strategies include phased application of nitrogen fertilizer, the addition of nitrification inhibitors, or using slow-release nitrogen fertilizers, combined with appropriate increases in crop planting density, straw return decomposition technologies and water-saving irrigation methods to reduce GHG emissions. These strategies aim to achieve low-carbon sustainable grain production and provide a foundation for exploring the emissions reduction potential of agricultural inputs and optimizing regional crop layouts, offering new insights for developing more effective GHG reduction strategies.

Combination of the degrading bacterium Bacillus cereus MZ-1 and corn straw biochar enhanced the removal of imazethapyr from water solutions

Long residual herbicide imazethapyr has caused a serious threat to subsequent sensitive crop plants and ecological security. Efficient immobilized microorganism technology offers a sustainable solution for remediating pesticides contamination. In this study, three corn straw biochars produced at 300℃, 500℃, and 700℃ were used as carriers to immobilize the imazethapyr degrading strain Bacillus cereus MZ-1, aiming to efficiently remove imazethapyr from the water environment. Response surface methodology was employed to optimize the best immobilization conditions based on the efficiency of imazethapyr removal. The results indicate that the biochar produced at 500 ℃ was the most effective carrier for immobilization, despite having a lower imazethapyr removal capacity compared to the biochar produced at 700 ℃. Additionally, the optimal strain addition amount was a suspension of strain MZ-1 (OD600=1) in a 3.5-fold biochar solution, and the best immobilized time was 18 h. The prepared immobilized MZ-1 achieved a maximum imazethapyr removal efficiency of 79.85 %. Moreover, the immobilized MZ-1 demonstrated enhanced detoxification efficacy against imazethapyr-induced harm in sensitive oilseed rape crops, surpassing the effects of using MZ-1 or biochar alone. Results of this work suggests biochar immobilized degradation strain MZ-1 is a highly effective in-situ remediation strategy for bioremediation of imazethapyr contamination.

Identification of potential auxin response candidate genes for soybean rapid canopy coverage through comparative evolution and expression analysis.

Throughout domestication, crop plants have gone through strong genetic bottlenecks, dramatically reducing the genetic diversity in today's available germplasm. This has also reduced the diversity in traits necessary for breeders to develop improved varieties. Many strategies have been developed to improve both genetic and trait diversity in crops, from backcrossing with wild relatives, to chemical/radiation mutagenesis, to genetic engineering. However, even with recent advances in genetic engineering we still face the rate limiting step of identifying which genes and mutations we should target to generate diversity in specific traits. Here, we apply a comparative evolutionary approach, pairing phylogenetic and expression analyses to identify potential candidate genes for diversifying soybean (Glycine max) canopy cover development via the nuclear auxin signaling gene families, while minimizing pleiotropic effects in other tissues. In soybean, rapid canopy cover development is correlated with yield and also suppresses weeds in organic cultivation. We identified genes most specifically expressed during early canopy development from the TIR1/AFB auxin receptor, Aux/IAA auxin co-receptor, and ARF auxin response factor gene families in soybean, using principal component analysis. We defined Arabidopsis thaliana and model legume species orthologs for each soybean gene in these families allowing us to speculate potential soybean phenotypes based on well-characterized mutants in these model species. In future work, we aim to connect genetic and functional diversity in these candidate genes with phenotypic diversity in planta allowing for improvements in soybean rapid canopy cover, yield, and weed suppression. Further development of this and similar algorithms for defining and quantifying tissue- and phenotype-specificity in gene expression may allow expansion of diversity in valuable phenotypes in important crops.

Screening the characteristic hyperspectral wavelength variables of peanut leaves based on coupled algorithms to predict SPAD value in peanut

ABSTRACT The accurate acquisition and prediction of the chlorophyll content in peanuts can provide reference for scientifically sound planting and management of peanut crops. In this study, peanut canopy leaves analysed during the flowering and pegging period were taken as the research object, and the spectral data collected by a portable hyperspectral spectrometer were used as the data source to study the inversion model of peanut leaf soil and plant analyser development (SPAD). To address the issues of randomness, the need for multiple iterations, and strong subjectivity in threshold selection in the initial variable set of the random frog (RF) algorithm, an improved RF algorithm was developed based on the sparse group lasso tool. By analysing and comparing the results of variable extraction of the improved RF algorithm and six characteristic wavelength screening algorithms, three algorithms were selected for pairwise coupling. These six algorithms were the correlation coefficient method (CC), successive projections algorithm, iteratively retains informative variables (IRIV), uninformative variable elimination (UVE), competitive adaptive reweighed sampling, and a genetic algorithm. The results show that: (1) the results of CC, UVE, and IRIV algorithms are better in a single algorithm experiment; and (2) in the coupled algorithms experiment, CC-UVE, CC-IRIV, and UVE-IRIV methods can effectively reduce dimensions, and the model has a certain level of stability. Among them, the UVE-IRIV-Extreme gradient boosting model had the highest accuracy, R 2 = 0.652, RMSE = 1.867, and the variable compression rate was as high as 97.84%. The research results can provide a theoretical basis for rapid and accurate monitoring of the SPAD values of peanut leaves.

Sinusoidal LED light recipes can improve rocket edible biomass and reduce electricity costs in indoor growth environments.

Accumulation of edible biomass by crop plants relies on maintenance of a high photosynthetic rates across the photoperiod, with assimilation rate (A) generally responding to increasing light intensity in a hyperbolic fashion. In natural environments light fluctuates greatly over the course of the day, however in Controlled Environmental Agricultural (CEA) systems, light intensity can be supplemented or precisely controlled using LEDs to create near optimum conditions. In such indoor growth environments light is often delivered as a square wave and recommendations to horticulturalists are given in the form of Daily Light Integrals (DLI). However, this does not take into account the slow photosynthetic induction at the start of the photoperiod and the decline of A towards the end of the photoperiod, which has been demonstrated by several previous studies. Square wave light regimes therefore potentially cause suboptimal photosynthetic utilization of the applied lighting and waste electricity. Here we have adapted light recipes to gradually increase and decrease in intensity to take account of these findings. We demonstrate that, utilising a sinusoidal light regime capped at 250 μmol m-2 s-1, it is possible to increase edible biomass of rocket (by ca. 20%) compared to square wave delivered at 250 at the same DLI. Additionally, this can be achieved using less electricity (0.6%), therefore reducing energy costs and improving profitability. We suggest that capping maximum light intensity at 250 µmol m-2 s-1 improves the operating efficiency of PSII photochemistry (Fq'/Fm') also known as the photosynthetic efficiency by maintaining A later in the photoperiod. We show that a higher electron transfer rate (ETR) is maintained in these treatments over the photoperiod compared to higher light intensity caps, resulting in a greater Daily Photochemical Integral (DPI). We attribute this to less NPQ due to a greater sink capacity for the end products of electron transport, ATP and NADPH, as A is kept high for longer.

From the discovery of a novel arepavirus in diseased arecanut palms (Areca catechu L.) in India to the identification of known and novel arepaviruses in bee and plant transcriptomes through data-mining

Arecanut palm is a commercially important plantation crop valued for its nut. In this investigation, we report the discovery of a putative novel arepavirus, named areca palm necrotic ringspot virus 2 (ANRSV2), in necrotic ringspot diseased areca palms in Bantwal, Dakshina Kannada, Karnataka, India through RNA-sequencing and transmission electron microscopy. Further, the presence of ANRSV2 in the diseased samples was confirmed through reverse transcriptase-polymerase chain reaction assays. In addition, by mining public domain transcriptome data for arepaviral sequences, we identified a putative novel arepavirus in Psychotria rubra, a non-palm host. We recovered the genome sequences of the areca palm necrotic ringspot virus in honey bees, tomato, Onobrychis viciifolia, and Rhamnus heterophylla. These findings broaden our comprehension of arepaviral diversity and host range, and suggest an intriguing possibility of pollen-mediated arepaviral transmission that necessitates empirical validation. Further studies are needed to understand the biology of identified putative novel arepaviruses.

Brassica juncea pre-season cover crops reduce soybean root colonization by Macrophomina phaseolina, the fungus causing charcoal rot

Macrophomina phaseolina (Tassi) Goid. is a soilborne fungus that causes charcoal rot in numerous crop plants, reducing yield and profits. This study assessed the efficacy of pre-season mustard cover crops (Brassica juncea), a chemical fungicide seed treatment, a combination of both, and a non-treated control in a set of varieties that ranged in maturity. In 2016 and 2017, 'AG4135 RR2Y/SR' consistently yielded lower compared to other varieties. Early maturity varieties exhibited reduced yields relative to mid and late maturity pairs in 2016 and 2017. Root colonization was influenced by treatment, with the combined pre-season cover crop and seed treatment exhibiting the lowest colonization rates in 2015, while all treatments had significantly reduced colonization in 2017 compared to untreated controls. Additionally, differences in root colonization were observed among soybean varieties, suggesting genotype-specific responses to disease management strategies. M. phaseolina soil populations showed a marked increase from pre-cover crop to post-soybean harvest underscoring the pathogen's proliferation throughout the growing season. Correlation analyses revealed significant negative relationships between root colonization and yield for untreated controls, suggesting that higher root colonization adversely affected crop performance. These findings suggest that specific treatments may help mitigate M. phaseolina population build-up in roots and soil and indicate that the effectiveness of control measures may be influenced by pathogen variability in response to environmental conditions and management practices. These findings also contribute to our understanding of effective strategies for managing charcoal rot disease and highlights the importance of integrating chemical and biological control methods.

Occasional Occurrences and Distributions of Red Billed Quelea (Quelea quelea) Birds on Cultivating Crops during the Belg Season at Raya Azebo District of Tigray, Ethiopia

The Belg season plays a crucial role in the agricultural calendar of the Raya District, particularly due to the shortage of rainfall during the summer season. This seasonal pattern of rainfall scarcity necessitates the significance of the Belg season for agricultural activities in this region. Aim of the study was to assess the Quelea bird incidence and its association agronomic practice and environmental factors. Field survey was conducted in Raya-azebo district during 2024 Belg season. A total of 49 farmers field were assessed for the incidence and prevalence of the quelea bird. Result indicated that out of the assessed fields, 69.39% was affected by Quelea birds the assessed fields. The damage level caused by birds was varied from 0% to 100%. On average, it was determined that approximately 32.37% of the cultivated crops were affected by birds. The mean percentage of crop damage across all kebelles was observed. Ewo had the highest mean damage at 61.45%, followed by Kara-Adishaho at 57.5%. On the other hand, Tsigea experienced a significantly lower damage rate of 1.67% followed by Genete with damage rat of 11%. Independent variables such as crop types, planting time, harvesting time, source of water, and coverage of trees play a significant (p<0.05) role in influencing bird damage in belg season crops. The lowest bird damage percentage were observed in crops planted in middle March, with 6.19% and late May harvesting, with a rate of 19.38%. Adopting practices such as cultivating crops in clusters and planting crops of similar maturity at the same time can be effective strategies for controlling Quelea birds’ damage in agricultural settings.

Identifying Crop Distress and Stress-Induced Plant Diseases Using Hyper Spectral Image Analysis

The purpose of this study is to determine whether hyper spectral images can be used to identify plant diseases and crop pressure from aerial photographs. With extensive research on the prevalent methods used closer to the problem, this study offers a potent strategy for identifying crop distress and illnesses using this efficient imaging technique. To identify the spectral fingerprints of common indications and symptoms of plant diseases and crop strains, this study evaluates the available hyper spectral photo datasets. After that, the data are examined using two learning algorithms—the highly randomized trees and the Random Woodland set of rules—to create predictions that are entirely dependent on the results that are discovered. In the end, a benchmarked set of test statistics is used to assess the prediction accuracy. The results of this study show that hyper spectral photo evaluation has a strong and promising utility for crop stress and disease identification. Hyper spectral light evaluation is a method for identifying plant diseases caused by strain on crops. By gathering and evaluating high-dimensional spectral reflection data from satellite or aircraft structures, details regarding the physiological homes of flowers can be identified. The health of plants, illnesses brought on by stress, and agricultural productivity predictions can all be made using these facts. Hyper spectral recordings can also be used to create actions that reduce agricultural losses and enhance the health of plants that are prone to disease.

Soil Diversities in Regards to Horticultural Variabilities

This review paper focuses on the impacts of soil diversity on a variety of horticultural crops in India. Different soil types of India have been discussed in this paper with their preferable horticultural crops those grow best on them. Major horticultural crops including fruits, vegetables, flowers, plantation crops, spices and medicinal crops with their appropriate soil types have also been highlighted. Important measures can be taken both scientifically and economically for the improvement of soil health that will eventually lead to increase in horticultural crop yield.

Influence of indole acetic acid and trehalose, with and without zinc oxide nanoparticles coated urea on tomato growth in nitrogen deficient soils

Nitrogen deficiency in low organic matter soils significantly reduces crop yield and plant health. The effects of foliar applications of indole acetic acid (IAA), trehalose (TA), and nanoparticles-coated urea (NPCU) on the growth and physiological attributes of tomatoes in nitrogen-deficient soil are not well documented in the literature. This study aims to explore the influence of IAA, TA, and NPCU on tomato plants in nitrogen-deficient soil. Treatments included control, 2mM IAA, 0.1% TA, and 2mM IAA + 0.1% TA, applied with and without NPCU. Results showed that 2mM IAA + 0.1% TA with NPCU significantly improved shoot length (~ 30%), root length (~ 63%), plant fresh (~ 48%) and dry weight (~ 48%), number of leaves (~ 38%), and leaf area (~ 58%) compared to control (NPCU only). Additionally, significant improvements in chlorophyll content, total protein, and total soluble sugar, along with a decrease in antioxidant activity (POD, SOD, CAT, and APX), validated the effectiveness of 2mM IAA + 0.1% TA with NPCU. The combined application of 2mM IAA + 0.1% TA with NPCU can be recommended as an effective strategy to enhance tomato growth and yield in nitrogen-deficient soils. This approach can be integrated into current agricultural practices to improve crop resilience and productivity, especially in regions with poor soil fertility. To confirm the efficacy of 2mM IAA + 0.1% TA with NPCU in various crops and climatic conditions, additional field studies are required.

Human-driven evolution of cultivated plants and the origin of early civilizations: The concept of Neolithic revolution in the works of Nikolai Vavilov

The concept of centers of origin of cultivated plants (crop biodiversity hotspots) developed by Nikolai Vavilov (1887-1943) is essential for understanding the origin and evolution of human civilization. Vavilov formulated the principles of Neolithic agricultural revolution and substantiated the basic patterns for the emergence of agricultural civilizations. He established that the center of speciation of the plants that have a potential for cultivation determines the origin of primary civilization. Humans actively performed the selection of plants with valuable properties, which led to the formation of new cultivated species and varieties, while the starting point for such unconsciously human-directed evolution was the presence of potentially useful traits due to the increased genetic diversity in the center of origin. The spreading of agriculturally important cultivars from the center of their origin led to the propagation of beneficial farming technologies over large areas. The establishment of human civilization resulted from the dynamic quasi-symbiotic relationship between humans and domesticated plants and animals, which human-driven evolution became an essential factor for the transformation and dynamics of human societies. In the addendum, we present archive materials on the cooperation of Nikolai Vavilov with the historians and ethnologists from the editorial board of the journal “Novy Vostok” (“Nouvel Orient”). These materials include his letters to Professor Ilya Borozdin.

Increasing corn cultivation exacerbated crop residue burning in Northeast China in 21st century

China's endeavors to mitigate recurrent crop residue burning (CRB) and improve air quality have yielded positive results owing to recent pollution prevention policies. Nonetheless, persistent challenges remain, particularly in the Northeast China (NEC), where low temperature complicates crop residue management. Here, we examined the effects of cropping pattern adjustment on variations of CRB patterns in NEC during 2001–2021, utilizing the Moderate-resolution Imaging Spectroradiometer (MODIS) burned area dataset, the Visible Infrared Imaging Radiometer Suite (VIIRS) active fire dataset, and the high-accuracy crop planting area maps. Our results revealed an overall upward trend of 805.96 km2/yr in NEC CRB from 2001 to 2021. The corn CRB area accounted for more than 50% of the total CRB area in each CRB-intensive year (2013–2021), and the increasing corn CRB generally aligns with the growing corn cultivation fields. A seasonal shift in CRB was found around 2017, with intensive CRB activities transitioning from both autumn and spring to primarily spring, particularly in the Songnen Plain and Sanjiang Plain. The changing trend of PM2.5 concentration aligned spatially with the shift. Moreover, the CRBs in spring of 2020 and 2021 were more severe than the major burning seasons in previous years, likely due to the disruptions during COVID-19 lockdowns. In certain years, the explanatory power of spring CRB on PM2.5 concentration was comparable to that of other natural factors, such as precipitation. This study underscores the critical need for sustained and region-specific strategies to tackle the challenges posed by CRBs.