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Background: Tillage practices can substantially affect soil properties depending on crop stage. The interaction between tillage and crop growth on arbuscular mycorrhizal fungi (AMF) communities remains unclear. We investigated the interactions between four tillage treatments (CT: conventional tillage, RT: reduced tillage, NT: no tillage with mulch, and SS: subsoiling with mulch), maintained for 25 years, and two wheat growth stages (elongation stage and grain filling stage) on AMF diversity and community composition. Results: The AMF community composition strongly changed during wheat growth, mainly because of changes in the relative abundance of dominant genera Claroideoglomus, Funneliformi, Rhizophagu, Entrophospora, and Glomus. Co-occurrence network analysis revealed that the grain filling stage had a more complex network than the elongation stage. Redundancy analysis results showed that keystone genera respond mainly to changes in soil organic carbon during elongation stage, whereas the total nitrogen content affected the keystone genera during grain filling. Compared with CT, the treatments with mulch, i.e., NT and SS, significantly changed the AMF community composition. The change of AMF communities under different tillage practices depended on wheat biomass and soil nutrients. NT significantly increased the relative abundances of Glomus and Septoglomus, while RT significantly increased the relative abundance of Claroideoglomus. Conclusion: Our findings indicate that the relative abundance of dominant genera changed during wheat growth stages. Proper tillage practices (e.g., NT and SS) benefit the long-term sustainable development of the Loess Plateau cropping systems. [ABSTRACT FROM AUTHOR]

Limax maximus, or great gray slug, is a common agriculture pest. The pest infests crops during their growth phase, creating holes in vegetable leaves, particularly in seedlings and tender leaves. A study was conducted to assess the insecticidal activity of Ageratina adenophora extract against these slugs. Factors such as fecundity, growth, hatching rate, offspring survival rate, protective enzyme activity, and detoxifying enzyme activity were examined in slugs exposed to the extract's sublethal concentration (LC50) for two different durations (24 and 48 h). The phytochemical variability of the extracts was also studied. The LC50 value of the A. adenophora extract against L. maximus was 35.9 mg/mL. This extract significantly reduced the hatching rate of eggs and the survival rate of offspring hatched from exposed eggs compared with the control. The lowest rates were observed in those exposed for 48 h. The survival, growth, protective enzyme, and detoxification activity of newly hatched and 40-day-old slugs decreased. The A. adenophora extract contained tannins, flavonoids, and saponins, possibly contributing to their biological effects. These results suggest that the extract could be used as an alternative treatment for slug extermination, effectively controlling this species. [ABSTRACT FROM AUTHOR]

It is well-known that freezing affects crop growth worldwide and significantly reduces crop production in the affected regions. The study objective was to investigate the effect of sodium silicate and sodium selenite individually or in combination on Alcea rosea plants grown under cold temperature stress. In this work, hollyhock plants were grown with sodium selenite and sodium silicate to 1/2 Hoagland solution, including 1) control, 1 mM sodium sulfate, 2) 1 mM sodium silicate 3), 0.03 mM sodium selenite, 4) 1 mM sodium silicate + 0.03 mM sodium selenite and exposed to nonfreezing (20 °C) and freezing temperature (−4 °C). Nutritional elements, photosynthesis parameters, electrolyte leakage, malondialdehyde, water content, osmolytes, and antioxidant enzymes were determined. The application of Si + Se effectively enhanced the Si and Se content of leaves (54% and 164%) compared to control plants. The combined Si and Se addition increased phenols, water-soluble sugars, proline, chlorophyll, net photosynthesis (Pn), and stomatal size under cold stress. Moreover, Si and Se in combination in stressed plants inhibited electrolyte leakage and malondialdehyde (MDA) by increasing the activities of enzymes such as superoxidase dismutase (SOD), ascorbate peroxidase (APX), and catalase (CAT). The maximal to minimal values of essential oil content, relative water content (RWC), and stomatal density depended on the treatment: Si + Se > Si = Se. By increasing K content, phenol, proline, and water-soluble sugars, Si + Se > Si > Se application decreased the adverse effects of cold stress on the dry weight of the hollyhock. [ABSTRACT FROM AUTHOR]

Cereal crops are crucial for global food security; however, they are susceptible to various environmental stresses that significantly hamper their productivity. In response, melatonin has emerged as a promising regulator, offering potential benefits for stress tolerance and crop growth. This review explores the effects of melatonin on maize, sorghum, millet, rice, barley, and wheat, aiming to enhance their resilience to stress. The application of melatonin has shown promising outcomes, improving water use efficiency and reducing transpiration rates in millet under drought stress conditions. Furthermore, it enhances the salinity and heavy metal tolerance of millet by regulating the activity of stress-responsive genes. Similarly, melatonin application in sorghum enhances its resistance to high temperatures, low humidity, and nutrient deficiency, potentially involving the modulation of antioxidant defense and aspects related to photosynthetic genes. Melatonin also exerts protective effects against drought, salinity, heavy metal, extreme temperatures, and waterlogging stresses in maize, wheat, rice, and barley crops by decreasing reactive oxygen species (ROS) production through regulating the antioxidant defense system. The molecular reactions of melatonin upregulated photosynthesis, antioxidant defense mechanisms, the metabolic pathway, and genes and downregulated stress susceptibility genes. In conclusion, melatonin serves as a versatile tool in cereal crops, bolstering stress resistance and promoting sustainable development. Further investigations are warranted to elucidate the underlying molecular mechanisms and refine application techniques to fully harness the potential role of melatonin in cereal crop production systems. [ABSTRACT FROM AUTHOR]

Nitrogen (N) is one of the primary macronutrients required for crop growth and yield. This nutrient is especially limiting wheat yields in the dry and low fertile agro-ecologies having low N in the root zone soil strata. Moreover, majority of farmers in India and South Asia are small to marginal with meagre capacity to invest in costly nitrogen fertilizers. Therefore, there is an immense need to identify lines that use nitrogen efficiently. A set of 50 diverse wheat genotypes consisting of indigenous germplasm lines (05), cultivars released for commercial cultivation (23) and selected elite lines from CIMMYT nurseries (22) were evaluated in an alpha-lattice design with two replications, a six-rowed plot of 2.5m length for 24 agro morphological, physiological and NUE related traits during two consecutive crop seasons in an N-depleted precision field under two different N levels of 50%-N50 (T1) and 100%-N100 (T2) of recommended N, i.e., 100 kg/ha. Analysis of variance revealed significant genetic variation among genotypes for all the traits studied. About 11.36% yield reduction was observed at reduced N levels. Significant correlations among NUE traits and yield component traits were observed which indicated pivotal role of N remobilization to the grain in enhancing yield levels. Among N-insensitive genotypes identified based on their yielding ability at low N levels, UASBW13356, UASBW13358, UASBW13354, UASBW13357 and KRL1-4 showed their inherent genotypic plasticity toward N application. The genotypes with more yield and high to moderate NUtE can be used as parents for the breeding of N efficient genotypes for marginal agro-ecologies. Low N tolerant genotypes identified from the current investigation may be further utilized in the identification of genomic regions responsible for NUE and its deployment in wheat breeding programs. The comprehensive data of 24 traits under different nitrogen levels for diverse genotypes from India and global sources (mainly CIMMYT) should be useful for supporting breeding for NUE and thus will be of great help for small and marginal farmers in India and South Asia. [ABSTRACT FROM AUTHOR]

Chickpea, being an important grain legume crop, is often confronted with the adverse effects of high temperatures at the reproductive stage of crop growth, drastically affecting yield and overall productivity. The current study deals with an extensive evaluation of chickpea genotypes, focusing on the traits associated with yield and their response to heat stress. Notably, we observed significant variations for these traits under both normal and high-temperature conditions, forming a robust basis for genetic research and breeding initiatives. Furthermore, the study revealed that yield-related traits exhibited high heritability, suggesting their potential suitability for marker-assisted selection. We carried out singlenucleotide polymorphism (SNP) genotyping using the genotyping-bysequencing (GBS) method for a genome-wide association study (GWAS). Overall, 27 marker--trait associations (MTAs) linked to yield-related traits, among which we identified five common MTAs displaying pleiotropic effects after applying a stringent Bonferroni-corrected p-value threshold of <0.05 [-log10(p) > 4.95] using the BLINK (Bayesian-information and linkagedisequilibrium iteratively nested keyway) model. Through an in-depth in silico analysis of these markers against the CDC Frontier v1 reference genome, we discovered that the majority of the SNPs were located at or in proximity to genecoding regions. We further explored candidate genes situated near these MTAs, shedding light on the molecular mechanisms governing heat stress tolerance and yield enhancement in chickpeas such as indole-3-acetic acid--amido synthetase GH3.1 with GH3 auxin-responsive promoter and pentatricopeptide repeat-containing protein, etc. The harvest index (HI) trait was associated with marker Ca3:37444451 encoding aspartic proteinase ortholog sequence of Oryza sativa subsp. japonica and Medicago truncatula, which is known for contributing to heat stress tolerance. These identified MTAs and associated candidate genes may serve as valuable assets for breeding programs dedicated to tailoring chickpea varieties resilient to heat stress and climate change. [ABSTRACT FROM AUTHOR]

Potato (Solanum tuberosum L.) is a heavy feeder and highly responsive to nutrient input, where the proper quantity and timing of nutrient supply is most critical component in achieving high productivity in potato cultivation. To assess the crop response and productivity, the potato variety 'Kufri Jyoti' was taken under different integrated nutrient management practices. The recommended dose of fertilizer was at 150:80:100 kg N: P2O5: K2O/ha, 25 kg/ha of ZnSO4 and 15 kg/ha of Borax were applied during the experiment. The results indicated that there were highly significant effects of higher doses of nitrogen with recommended P and K combined applied with Zinc and Boron on tuber yield, plant NPK uptake efficiency and enzymatic activities. Results from the experiment expressed that the application of 125% RDN along with the application of Zn and B ensured maximum total tuber yield (24.73 t/ha), crop growth rate (5.222 g/m2/day), relative growth rate (0.066 g/g/day) at peak growth stages and quality such as starch (15.64%) and sucrose synthase activity (695 µg/g of fresh weight of tuber) of potato grown with the above nutrient management practices. This study indicated that production variation for higher nitrogen doses from inorganic sources of fertilizer existed among 16 different nutrient application treatments, and with better quality parameters. [ABSTRACT FROM AUTHOR]

The sowing date is a crucial factor for jute and allied fiber crops for better crop growth as well as fiber production. It is more important for advanced breeding lines before variety release. The purpose of this study was to provide information to breeders on the sowing time of advanced breeding lines of smooth Mesta, so they can recommend suitable sowing times for specific varieties. This study was carried out in the Jute Research Substation at Dinajpur, Bangladesh from March to July 2023. For the experimental treatments, three distinct sowing dates-namely, March 20th, March 30th, and April 10th were used, alongside the utilization of an advanced Mesta breeding line, SM-2, developed by the Bangladesh Jute Research Institute. A high-yielding Mesta variety, BJRI Mesta 3 (SAMU-93) was used as a control. A factorial RCBD design with three replications was used. Results showed that advanced breeding lines and sowing dates significantly affected plant height, base diameter, green weight with leaves, green weight without leaves, fiber yield and stick yield. Both the highest fiber yield (2.50 tha-1) and stick yield (5.00 tha1) were found when SM-2 was sown on 30th March. The second highest fiber yield (2.32 tha-1) and stick yield (4.64 tha-1) were found when SM-2 was sown on 10th April. The research showed that fiber yield and stick yields were 21 and 33% higher than the control respectively, when it was sown on 30 March. [ABSTRACT FROM AUTHOR]

Micronutrients are critical for the development of plants and play major role in enhancing both quantitative and qualitative crop yield. To examine the impact of foliar fertilization with micronutrients on various crop growth attributes, an experiment was conducted during kharif season of 2020 and 2021. Foliar spray with different combinations of zinc sulfate, ferrous sulfate, and manganese sulfate was done at 20 and 40 days after sowing. Increased plant height, leaf area index, leaf weight ratio, leaf area ratio, specific leaf weight, specific leaf area, crop growth rate, relative growth rate, and net assimilation rate were observed. Positive effect of foliar spray was observed in all parameters through all treatments. But, the overall maximum effect was observed in the treatment of foliar spray with T9 (0.2% FeSO4 +0.5% ZnSO4) followed by T7 (0.2% FeSO4 +0.2% ZnSO4) and T8 (0.5% FeSO4 and 0.2% ZnSO4). Given the positive effect of zinc, iron and manganese micronutrients on leaf and crop growth attributes, these treatments are suggested to be applied for the development of sweet corn. [ABSTRACT FROM AUTHOR]

This study introduces a novel methodology for the dynamic extraction of information on cotton growth in terms of height utilizing the DJI Zenmuse L1 LiDAR sensor mounted onto a DJI Matrice 300 RTK Unmanned Aerial Vehicle (UAV), aimed at enhancing the precision and efficiency of growth monitoring within the realm of precision agriculture. Employing the Progressive TIN Densification (PTD) and Cloth Simulation Filter (CSF) algorithms, combined with Kriging interpolation, we generated Canopy Height Models (CHMs) to extract the cotton heights at two key agricultural sites: Zengcheng and Tumxuk. Our analysis reveals that the PTD algorithm significantly outperforms the CSF method in terms of accuracy, with its R2 values indicating a superior model fit for height extraction across different growth stages (Zengcheng: 0.71, Tumxuk: 0.82). Through meticulous data processing and cluster analysis, this study not only identifies the most effective algorithm for accurate height extraction but also provides detailed insights into the dynamic growth patterns of cotton varieties across different geographical regions. The findings highlight the critical role of UAV remote sensing in enabling large-scale, high-precision monitoring of crop growth, which is essential for the optimization of agricultural practices such as precision fertilization and irrigation. Furthermore, the study demonstrates the potential of UAV technology to select superior cotton varieties by analyzing their growth dynamics, offering valuable guidance for cotton breeding and cultivation. [ABSTRACT FROM AUTHOR]

Titanium has been reported to have positive effects on crop growth and production in various species. However, the impact of titanium on the Tartary buckwheat crops has not yet been studied. Therefore, an experiment was conducted to investigate the effect of spraying different concentrations of ionic titanium on the growth, photosynthesis, and uptake of mineral nutrients in Tartary buckwheat. The results showed that the application of titanium significantly improved dry matter accumulation, internode diameter, main stem node, root length, root average diameter, root surface area, root volume, grains per plant, and weight of grains per plant. Additionally, chlorophyll and photosynthetic parameters showed improvement regardless of the concentration of titanium used. The study found that titanium accumulation was mainly in leaves. The content of titanium in leaves showed a significant positive correlation with K, Ca, Mg, Mn, Cu, Zn, and B. This suggests a potential synergistic relationship between titanium and minerals in Tartary buckwheat leaves. Furthermore, the study also observed a significant increase in the total accumulation of P, K, Ca, Mg, Mn, Cu, Zn, and B in Tartary buckwheat plants. Overall, this study provides evidence for the positive effects of titanium on Tartary buckwheat and offers a theoretical foundation for practical production. [ABSTRACT FROM AUTHOR]

Cold stress is a major meteorological threat to crop growth and yield. Abscisic acid (ABA) plays important roles in plant cold tolerance by activating the expression of cold‐responsive genes; however, the underlying transcriptional regulatory module remains unknown. Here, we demonstrated that the cold‐ and ABA‐responsive transcription factor ETHYLENE RESPONSE FACTOR 15 (ERF15) positively regulates ABA‐mediated cold tolerance in tomato. Exogenous ABA treatment significantly enhanced cold tolerance in wild‐type tomato plants but failed to rescue erf15 mutants from cold stress. Transcriptome analysis showed that ERF15 was associated with the expression of cold‐responsive transcription factors such as CBF1 and WRKY6. Further RT‐qPCR assays confirmed that the ABA‐induced increased in CBF1 and WRKY6 transcripts was suppressed in erf15 mutants when the plants were subjected to cold treatment. Moreover, yeast one‐hybrid assays, dual‐luciferase assays and electrophoretic mobility shift assays demonstrated that ERF15 activated the transcription of CBF1 and WRKY6 by binding their promoters. Silencing CBF1 or WRKY6 significantly decreased cold tolerance. Overall, our study identified the role of ERF15 in conferring ABA‐mediated cold tolerance in tomato plants by activating CBF1 and WRKY6 expression. This study not only broadens our knowledge of the mechanism of ABA‐mediated cold tolerance in plants but also highlights ERF15 as an ideal target gene for cold‐tolerant crop breeding. Summary statement: This study demonstrated that the cold‐ and abscisic acid (ABA)‐responsive transcription factor ETHYLENE RESPONSE FACTOR 15 positively regulates ABA‐mediated cold tolerance in tomato plants by activating CBF1 and WRKY6 expression. [ABSTRACT FROM AUTHOR]

Pre-harvest yield prediction of direct-seeded rice is critical for guiding crop interventions and food security assessment in precision agriculture. Technology advances in unmanned aerial vehicle (UAV)-based remote sensing has provided an unprecedented opportunity to efficiently retrieve crop growth parameters instead of labor-intensive ground measurements. This study is aiming to evaluate the feasibility of fusing multi-temporal UAV-derived features collected at critical phenological stages in forecasting direct-seeded rice yield across different cultivars and nitrogen (N) management. The results showed that RGB sensor-derived canopy volume, canopy coverage, and spectral features including RBRI, WI etc., were identified to be most sensitive to the differences in aboveground biomass and grain yield. Heading stage was the suitable time for estimating yield performance (R2 = 0.75) for mono-temporal UAV observation. By contrast, multi-temporal features fusion could remarkably enhance the yield prediction accuracy. Moreover, the yield prediction accuracy can be further improved by integrating UAV features collected at panicle initiation and heading stages (i.e., rice reproductive phase) compared to multi-temporal features fusion (R2 increased from 0.82 to 0.85 and RMSE decreased from 35.1 to 31.5 g m−2). This can be attributed to the fact that the biomass accumulation during the reproductive phase was closely associated to the total spikelets and final yield. By using this proposed approach, the predicted yield showed a good spatial consistency with the measured yield across different cultivars and N management, and yield prediction error in the most of the plots (114 of 128 plots) was less than 45 g m−2. In summary, this study highlights that the reproductive phase is the optimal time window for UAV observing, which provides an effective method for accurate pre-harvest yield prediction of direct-seeded rice in precision agriculture. [ABSTRACT FROM AUTHOR]

Site-specific crop management is based on the postulate of varying soil and crop requirements in a field. Therefore, a field is separated into homogenous management zones, using available data to adapt management practices environment to maximize productivity and profitability while reducing environmental impacts. Due to advancing sensor technologies, crop growth and yield data on more minor scales are common, but soil data often needs to be more appropriate. Crop growth models have shown promise as a decision support tool for site-specific farming. The Decision Support System for Agrotechnology Transfer (DSSAT) is a widely used point-based model. To overcome the problem of inappropriate soil input data problem, this study introduces an external plug-in program called Soil Profile Optimizer (SPO), which uses the current DSSAT v4.8 to calibrate soil profile parameters on a site-specific level. Developed as an inverse modelling approach, the SPO can calibrate selected soil profile parameters by targeting available in-season plant data. Root Mean Square Error (RMSE) and normalized RMSE as error minimization criteria are used. The SPO was tested and evaluated by comparing different simulation scenarios in a case study of a 3-yr field trial with maize. The scenario with optimized soil profiles, conducted with the SPO, resulted in an R2 of 0.76 between simulated and observed yield and led to significant improvements compared to the scenario conducted with field scale soil profile information (R2 0.03). The SPO showed promise in using spatial plant measurements to estimate management zone scale soil parameters required for the DSSAT model. [ABSTRACT FROM AUTHOR]

Trichoderma has become one of the most studied filamentous fungi to be used as a greener and more sustainable solution for improving the production and growth of numerous crops, due to its capability to form symbiotic associations with plants. This study aimed to evaluate the effect of Trichoderma isolates obtained from the rhizosphere of organic rice fields in Sukabumi, Indonesia, in enhancing rice germination and seedling growth. A laboratory experiment used a completely randomized design consisting of seed treatments of 21 Trichoderma isolates (T1-T21) and a control treatment without Trichoderma (C). The inoculation was employed to elucidate any potential effects of Trichoderma isolates. Results showed that five isolates, i.e., T5, T7, T9, T10, and T14 stimulated the highest seedling vigor index, root and shoot length, and fresh weight and dry weight. These findings exhibited the potential of these five isolates as plant growth-promoting fungi to improve rice seedling growth and contribute to our understanding of the role of symbiotic fungi in sustainable rice crop production. [ABSTRACT FROM AUTHOR]

Elevated atmospheric CO2 concentration (e[CO2]) and varied nitrogen (N) fertilization levels may mediate the different responses of C4 crops to progressive soil drought. In this study, the effects of reduced N (N1, 0.8 g pot−1) and adequate N (N2, 1.6 g pot−1) supply on leaf physiology, plant growth and water use efficiency (WUE) of maize (C4 crop) exposed to progressive soil drought grown at ambient CO2 (a[CO2], 400 ppm) and elevated CO2 (e[CO2], 800 ppm) concentration were investigated. The results indicated that compared with a[CO2], net photosynthetic rate (An) and leaf water potential (Ψl) at e[CO2] were maintained in maize leaves, while stomatal conductance (gs), transpiration rate and leaf hydraulic conductance were decreased, leading to enhanced WUE from stomatal to leaf scale. Despite An and Ψl of e[CO2] plants were more sensitive to progressive soil drought under both N fertilization levels, e[CO2] would increase leaf ABA concentration ([ABA]leaf) but decline the gs response to [ABA]leaf under N1 supply. e[CO2] coupled with N1 fertilization was conducive to enlarging leaf area, promoting specific leaf area, root and total dry mass, whereas reduced stomatal aperture and plant water use under progressive drought stress, contributing to an improvement in plant WUE, implying a better modulation of maize leaf stomata and water status under reduced N supply combined with e[CO2] responding to progressive soil drought. These findings in the current study would provide valuable advice for N management on maize (C4) crop efficient water use in a drier and CO2‐enriched environment. [ABSTRACT FROM AUTHOR]

Increased frequency and severity of chilling damage events pose potential risks to crop performance and productivity due to climate change. Accurate and real‐time access to chilling damage is important for crop growth and yield stability based on field's actual environment. To precisely identify regional chilling events and evaluate the impacts on crops, this study presents a model to estimate field air temperature in view of field crop situations. Land surface temperature, enhanced vegetation index, solar‐induced chlorophyll fluorescence and solar declination were involved in the model. With field simultaneous continuous monitoring and multisource fused remote sensing data, the model was calibrated and validated in Jiefangzha Irrigation Area (JIA) and Changchun City (CC) in North China, accompanied by the determination coefficient ≥0.756, root mean square error ≤0.782°C, relative error ≤0.041 and consistency index ≥0.902. Meanwhile, sensitivities of the model factors were determined through path analysis, where the factors performed according to the order solar‐induced chlorophyll fluorescence >solar declination >land surface temperature > enhanced vegetation index. Using the validated model, chilling damage to maize was further detected in JIA and CC from 2010 to 2020. Results showed that the severity of chilling damage was greater in CC than in JIA, along with the sterile‐type occurring three events in JIA and seven in CC, while the delayed‐type only twice in JIA in 2012 and 2016, but five times in CC in 2013, 2014, 2016, 2017 and 2019, respectively, being consistent with local statistics. In response to chilling damage, enhanced vegetation index and solar‐induced chlorophyll fluorescence demonstrated the negative chilling effects on greenness and light use efficiency for fluorescence. Serious yield losses were caused, with yield‐reducing by 5.00% (Dehui, 2013), 19.00% (Jiutai, 2014), 21.65% (Suburban district, 2016), 8.83% (Shuangyang, 2017) and 2.19% (Jiutai, 2019) in CC. The linear relationship between yield and growing degree days was a bit weakened by chilling damage, with the determination coefficient varying from 0.614 to 0.531. The increasing rate of yield with growing degree days decreased from 20.365 kg/(°C·d) in non‐chilling damage years to 9.670 kg/(°C·d) in chilling damage years. These findings indicate that the presented model is especially adaptive for agricultural field environments, enabling rapid precision detection of chilling damage on crops at regional scales. It will provide references for gauging the impact of chilling damage on crops, finding efficient solutions to the stress and ensuring sustainable development of agriculture. [ABSTRACT FROM AUTHOR]

Chlorophyll and nitrogen (N) content in rice at critical crop growth stages are important input parameters for crop growth and nutrient uptake models used to optimize N application. Hence, the study was conducted to predict chlorophyll and N content in rice using multiple regression-based models involving normalized difference vegetation index (NDVI), Soil Plant Analysis Development (SPAD), Customized leaf color chart (CLCC), chlorophyll and N content. An experiment was conducted with six varieties i.e. CR Dhan 312, CR Dhan 310, Lalat, Shatabdi, Swarna Shreya, CR Dhan 206 with four N levels (i.e. 0, 80, 100 and 120 kg N ha-1) in split plot design and replicated thrice. The NDVI, SPAD and CLCC readings were taken at 45, 49 and 54 days after transplanting (DAT). Plant sampling was done for estimating the chlorophyll and nitrogen content in laboratory following standard methodology. Multiple linear regressions were performed between NDVI, SPAD and CLCC readings and chlorophyll & N content in rice in different variables combinations. Multiple linear regression (MLR) models with two variables i.e. NDVI and SPAD predicted the chlorophyll and N content of rice varieties. The predicted values for nitrogen and chlorophyll were comparable to those obtained using models from individual varieties when combined data from six different varieties were used to create MLR models. The study concludes that variations in chlorophyll and N concentrations in rice can be estimated using data from optical sensors with notable accuracies. [ABSTRACT FROM AUTHOR]

Accurately obtaining the spatial distribution and planting patterns of crops is very important for agricultural planning and food security. At present, time-series images have been proved to be an effective tool to characterize crop seasonal growth patterns, and identifying crop information by measuring the time-series similarity between unknown classes and known crop phenology curves is also considered to be a useful way. However, the existing methods of selecting feature ignore the connection between each phenological stage of crops and the unique growth rules of the whole phenology, which makes it difficult to select time-series spectral features that are potentially important for crop mapping. In order to make up for this problem, a Whole Phenology-based Spectral Feature Selection (WPS) method was proposed. The aim was to select the time-series feature sets with great differences among winter crops from a large number of spectral features, so as to improve the mapping accuracy of winter rapeseed and winter wheat. Firstly, spectral separability between all classes is calculated. Secondly, the key phenological periods of winter crops were selected according to the importance of temporal features, and the spectral feature sets with high separability were selected according to the key phenological periods. Finally, a Time-weighted Dynamic Time Warping (TWDTW) algorithm was used to generate the winter rapeseed and winter wheat maps of two cities in the middle and lower reaches of the Yangtze River. The mapping accuracy of the two crops is more than 92%, which matches the crop planting area well. The research shows that combining the WPS method with the TWDTW mapping method has great potential to accurately map crop types based on satellite time-series images. [ABSTRACT FROM AUTHOR]

[Display omitted] Field path planning provides the basis for the autonomous navigation of agricultural vehicles. Existing path planning approaches are constrained to a 2D plane, disregarding the impact of terrain factors on navigation tasks. Furthermore, these methods generate non-global paths, as evidenced by their inability to accommodate the headland turning area while performing path planning based on the actual crop growth in the farmland. Low-altitude remote sensing technology, characterized by its high spatial resolution, timely data acquisition, and strong terrain perception, holds great potential for application in autonomous navigation. This study aims to integrate low-altitude remote sensing technology with path-planning tasks for agricultural vehicles by constructing oblique photography models of fields. The objective is to achieve global 3D path planning leveraging advanced methodologies rooted in deep learning and image processing. Four main steps were included in the proposed method. Low-altitude remote sensing models of field blocks were constructed first. Secondly, the models were converted to image patches for dataset establishment. Thirdly, primary crop row identification was conducted by semantic segmentation. Finally, global 3D paths covering the farmland and headland areas were generated. Tea fields in hilly areas were used to test the algorithm. Experiments revealed that the proposed method could be adapted to different field shapes, row numbers, row spacing, and vehicle turning radii. The proposed method uses deep learning and image processing as the primary technical tools but goes beyond traditional crop row detection to form a global path-planning strategy. In addition, the elevation information enabled by the 3D detection manner allows agricultural vehicles to gain a comprehensive understanding of both their own position and that of their destination. The dataset and the code are available at: https://github.com/ZeroHeading/Global-3D-path-generation.git. [ABSTRACT FROM AUTHOR]

Digital Twin is an emerging agritech technology that involves creating virtual representations of physical systems, which can be used for various purposes, such as optimizing crop management, predicting yield, and managing resources efficiently. The research is focusing to build a accurate digital twin model for crop growth, considering factors like evaporation (ET), growing degrees days (GDD), crop type, soil data, and agricultural practices. The model handles data streams related with geolocation, IOT historical sensor data and weather forecasts streams to simulate the crop risk and yield. Frequent updates based on realtime data enhance accuracy. Aside essential water management crop flow, the model is processing historical data related with nutrients like nitrogen (N), phosphorus (P), and potassium (K) elements are vital for plant growth and health, and their optimal balance can significantly impact corn yield. The research is extended on five locations in both Romania and Luxembourg handling wheat, corn and rapeseed crop simulation. [ABSTRACT FROM AUTHOR]

Elevated surface ozone (O 3) concentrations can negatively impact growth and development of crop production by reducing photosynthesis and accelerating leaf senescence. Under unabated climate change, future global O 3 concentrations are expected to increase in many regions, adding additional challenges to global agricultural production. Presently, few global process-based crop models consider the effects of O 3 stress on crop growth. Here, we incorporated the effects of O 3 stress on photosynthesis and leaf senescence into the Decision Support System for Agrotechnology Transfer (DSSAT) crop models for maize, rice, soybean, and wheat. The advanced models reproduced the reported yield declines from observed O 3 -dose field experiments and O 3 exposure responses reported in the literature (O 3 relative yield loss RMSE <10 % across all calibrated models). Simulated crop yields decreased as daily O 3 concentrations increased above 25 ppb, with average yield losses of 0.16 % to 0.82 % (maize), 0.05 % to 0.63 % (rice), 0.36 % to 0.96 % (soybean), and 0.26 % to 1.23 % (wheat) per ppb O 3 increase, depending on the cultivar O 3 sensitivity. Increased water deficit stress and elevated CO 2 lessen the negative impact of elevated O 3 on crop yield, but potential yield gains from CO 2 concentration increases may be counteracted by higher O 3 concentrations in the future, a potentially important constraint to global change projections for the latest process-based crop models. The improved DSSAT models with O 3 representation simulate the effects of O 3 stress on crop growth and yield in interaction with other growth factors and can be run in the parallel DSSAT global gridded modeling framework for future studies on O 3 impacts under climate change and air pollution scenarios across agroecosystems globally. [ABSTRACT FROM AUTHOR]

Premise: With the global atmospheric CO2 concentration on the rise, developing crops that can thrive in elevated CO2 has become paramount. We investigated the potential of hybridization as a strategy for creating crops with improved growth in predicted elevated atmospheric CO2. Methods: We grew parent accessions and their F1 hybrids of Arabidopsis thaliana in ambient and elevated atmospheric CO2 and analyzed numerous growth traits to assess their productivity and underlying mechanisms. Results: The heterotic increase in total dry mass, relative growth rate and leaf net assimilation rate was significantly greater in elevated CO2 than in ambient CO2. The CO2 response of net assimilation rate was positively correlated with the CO2 response of leaf nitrogen productivity and with that of leaf traits such as leaf size and thickness, suggesting that hybridization‐induced changes in leaf traits greatly affected the improved performance in elevated CO2. Conclusions: Vegetative growth of hybrids seems to be enhanced in elevated CO2 due to improved photosynthetic nitrogen‐use efficiency compared with parents. The results suggest that hybrid crops should be well‐suited for future conditions, but hybrid weeds may also be more competitive. [ABSTRACT FROM AUTHOR]

Agroforestry, the integration of trees, crops, and animals, is expected to increase environmental sustainability of fruit production compared to traditional orchards. Virtual experiments with models would allow the performance and sustainability of these systems to be evaluated in a range of pedoclimatic and management scenarios, taking into account the interactions of fruit trees with crops. The models should represent tree and crop growth in 3D, run simulations over the whole life cycle of the orchard, and account for management practices that influence tree-crop interactions. We reviewed existing fruit tree and agroforestry models and have proposed a decision tree to guide future modellers in choosing a model that meets their simulation objectives. None of the reviewed models met all requirements, but we identified improvements that could be made to two existing models to accurately simulate temperate fruit tree based agroforestry systems. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to investigate the effects of vermicompost leachate on the growth and water use of tomatoes in an unequal distribution of salinity in a hydroponic system. Method: Roots of tomato seedlings were separated into approximately two equal parts, each half was grown in a media culture part containing a 3-liter perlite and cocopeat mixture of a separated two-part box. The nutrient solution, irrigation water, and vermicompost leachate were applied for the irrigation of treatments according to the statistical design. Results: The results showed that the treatment in which the nutrient solution was used for one side of root media culture and the leachate with the salinity of 4 dS/m on the other side had an acceptable amount of dry and fresh weight and increased crop per drop. Conclusion: The results showed that the unequal distribution of salinity in the root media culture is an applicable technique for using vermicompost leachate although the success of this system is strongly dependent on the leachate correction. [ABSTRACT FROM AUTHOR]

Sweet potato is a crucial crop for food security and income generation. Sweet potato vine length, number of stems, average number of roots per plant, average root weight, marketable root yield, non-marketable root yield, and total sweet potato root yield were determined by the NPSB and nitrogen fertilizer application rates (p<0.01). Using the right fertilizer recommendations can improve crop growth and yield while minimizing resource use. Both NPSB and Nitrogen fertilizer rates had a highly significant impact on root number, root weight, marketable root yield, unmarketable root yield, and total root yield. The combination of 100 kg ha-1 NPSB fertilizer and 69 kg ha-1 of Nitrogen fertilizer gave the highest marketable root yield (553.09 qt ha-1). The treatment with 100 kg ha-1 NPSB fertilizer and 46 kg ha-1 Nitrogen fertilizer demonstrated the best result in terms of marginal rate of returns, with a marginal revenue of 17872%. To optimize sweet potato productivity in the Adola rede region, it is recommended to apply 100 kg ha-1 NPSB and 46 kg ha-1 nitrogen fertilizer. In general, cultivation in the Adola rede region can be optimized by applying a combination of 100 kg ha-1 of NPSB fertilizer and 46 kg ha-1 of nitrogen, resulting in improved plant growth and marketability, higher root yields and cost efficiency. [ABSTRACT FROM AUTHOR]

Chitosan is a derivative of chitin that is one of the most abundant biopolymers in nature, found in crustacean shells as well as in fungi cell walls. Most of the commercially available chitosans are produced from the exoskeletons of crustaceans. The extraction process involves harsh chemicals, has limited potential due to the seasonal and limited supply and could cause allergic reactions. However, chitosan has been shown to alleviate the negative effect of environmental stressors in plants, but there is sparse evidence of how chitosan source affects this bioactivity. The aim of this study was to investigate the ability of chitosan from mushroom in comparison to crustacean chitosan in enhancing drought stress tolerance in tomato plants (cv. MicroTom). Chitosan treatment was applied through foliar application and plants were exposed to two 14-day drought stress periods at vegetative and fruit set growth stages. Phenotypic (e.g., fruit number and weight), physiological (RWC) and biochemical-stress-related markers (osmolytes, photosynthetic pigments and malondialdehyde) were analyzed at different time points during the crop growth cycle. Our hypothesis was that this drought stress model will negatively impact tomato plants while the foliar application of chitosan extracted from either crustacean or mushroom will alleviate this effect. Our findings indicate that drought stress markedly decreased the leaf relative water content (RWC) and chlorophyll content, increased lipid peroxidation, and significantly reduced the average fruit number. Chitosan application, regardless of the source, improved these parameters and enhanced plant tolerance to drought stress. It provides a comparative study of the biostimulant activity of chitosan from diverse sources and suggests that chitosan sourced from fungi could serve as a more sustainable and environmentally friendly alternative to the current chitosan from crustaceans. [ABSTRACT FROM AUTHOR]

Purpose: The application of magnesium (Mg) fertilizer to alleviate Mg deficiency and improve crop yield has gained wide recognition. However, high Mg leaching loss is a growing concern in high rainfall areas, especially in acidic soils. Developing Mg fertilizer with less risk of leaching and adequate Mg supply to crops in a convenient way is worth considering in agricultural production. Methods: In this study, five Mg-fortified mono-ammonium phosphate (MAP) fertilizers were produced with anhydrous magnesium sulfate (MgSO4) and dolomite (CaMg(CO3)2) in various ratios. Nutrient solubility, Mg nutrient release, Mg leaching, and agronomic effectiveness under rainfall conditions in an acidic soil were evaluated. Results: Addition of the Mg sources to the MAP fertilizer did not affect P solubility of the fertilizer. The MAP fertilizers fortified with both MgSO4 and dolomite showed an initially fast release of Mg followed by slower release. In a pot experiment with simulated rainfall, the amount of Mg leached significantly decreased with increasing proportion of dolomite in the Mg-fortified fertilizers, which varied from 19.1% for the MgSO4 treatment to 3.8% for the dolomite treatment. Shoot dry matter yield and Mg concentration of soybean were higher for treatments with Mg-fortified MAP than for MAP-only. Conclusions: The use of dual-release Mg sources in macronutrient fertilizers could be a promising strategy to better meet crop Mg demands and effectively reduce Mg leaching losses, especially in sandy soils of high rainfall areas. [ABSTRACT FROM AUTHOR]

A field experiment was conducted during 2016-17 on rapid multiplication of turmeric to know the suitability of the technology to Chamarajanagara conditions. The data revealed that by practicing rapid multiplication of turmeric a farmers can save >80% of the seed rhizome requirement per unit area. Here, only 500 kg seed rhizomes are sufficient for producing turmeric seedlings for planting in a hectare instead of 2000 to 2500 kg in present farmers' practice. Weeding and irrigation water can be saved up to 45 days in main field. Rapid multiplication technique of turmeric recorded significantly higher number of plantlets per kg of seed rhizomes (206.71). The size of cut seed rhizome (6.77 g) has not affected the performance of the crop in the main field as at all the crop growth stages, it was recorded a significantly higher plant height (139.51 cm) and equal number of clumps (7.38) as compared to conventional propagation method provided proper seed rhizome preparation, nursery activities and growing of healthy seedlings are achieved. As relatively higher biomass (1.95 kg/plant), fresh rhizome yield per plant (1.59 kg), fresh rhizome yield (33.85 tonnes/ha) and cured rhizome yield (6.97 tonnes/ha) were recorded and overall 3.16 per cent increase in yield was also observed in the rapid multiplication technique adopted plots. Uniform establishment, growth and uniform maturity of the crop are the added advantage of this technology. For promotion of precision farming in turmeric, this technology is the first step to farmer has to adopt. The results are confirmed that rapid multiplication of turmeric is very much suited to Chamarajanagara condition. [ABSTRACT FROM AUTHOR]

Salinity is a significant abiotic factor that has adverse effects on crop growth and productivity. The objective of this current study was to investigate the potential of Piriformospora indica, arbuscular mycorrhizal fungi (AMF), and plant growth-promoting bacteria (PGPB) in alleviating salinity stress in the Maharaja BIO 9637 hybrid maize variety. The experiment employed a completely randomized design, where plants were subjected to two salinity levels: 0 and 200 mM NaCl (corresponding to electrical conductivity values of 0.02 and 17.1 mS cm−1, respectively) under greenhouse conditions. The findings of this study demonstrate that microbial inoculation significantly enhanced plant growth, biomass, photosynthetic efficiency, photosynthetic pigment concentration, osmolyte accumulation, and nutrient uptake compared to control plants under salinity stress. Moreover, microbe-colonized plants exhibited reduced levels of malondialdehyde, membrane permeability, and lipoxygenase activity. The microbe-colonized maize plants also displayed elevated levels of antioxidant enzymes, viz. superoxide dismutase (SOD), catalase (CAT), and ascorbate peroxidase (APX). However, AMF colonization did not affect CAT activity and decreased at high salinity levels. Remarkably, microbe-colonized plants exhibited less damage at the ultrastructural level than control plants, irrespective of the salinity levels. Henceforth, PGPB, P. indica, and AMF possess substantial promise as feasible choices for advancing sustainable agricultural methodologies in situations marked by environmental stress. [ABSTRACT FROM AUTHOR]

Not only is solving freshwater resource shortages effective but also an important measure for realizing the sustainable development of agriculture through the development and use of unconventional water resources. This pot experiment investigated the role of exogenous silicon in the risk of secondary soil salinization and the growth physiology of Lvxiu pakchoi cabbage under irrigation by using brackish water alone (BW), reclaimed water alone (RW), and compound irrigation with brackish water and reclaimed water at a ratio of 1:1, as well as the distribution of silicon in a soil–crop system. The results showed that with the extension of the spraying period of silicon fertilizer, the electrical conductivity (EC) decreased under 1:1 compound irrigation. The pH values in all treatments ranged from 7.95 to 8.10 without a potential risk of alkalization. Spraying silicon fertilizer had a positive effect on increasing the ratio of exchangeable potassium to sodium in soil. Spraying silicon fertilizer significantly reduced the percentage of exchangeable sodium (ESP) and the sodium adsorption ratio (SAR) in soils irrigated using BW, and increased the soil ESP and SAR under compound irrigation and RW irrigation, but these factors did not exceed the threshold of soil salinization. The proper application of silicon fertilizer had no significant effect on the total silicon content in the soil but increased the total silicon content in the plants to some extent. In addition, the yield was improved through proper silicon fertilizer application. In summary, exogenous silicon has positive effects on soil physical and chemical properties and crop growth, and relieves secondary salinization risk under compound irrigation via brackish water and reclaimed water. [ABSTRACT FROM AUTHOR]

The main factors affecting crop growth and yield are soil, climate, and crops. The influence of clime is more than soil on crop growth under certain conditions. The evidence is that some cover vegetation growth conditions are much different even though they grow on the same land. In each distinct place, the harvest time of one type of crops is not the same. One crucial factor that affects this is the daily growth rate or the degree of Growing Degree Days (GDD). Know parameters such as soil type, slope, land use, rainfall, and GDD temperature by using geographic information systems in determining the suitability of agricultural commodity development areas. The study aims to determine the suitability of soybean cropland in West Sumatra based on GDD value. Conducting land suitability analysis using the GDD method through several stages, namely, the classification of soybean land suitability parameters, making a map of soybean crop land suitability in physical characteristics, classifying the GDD value of soybean crops for the West Sumatra region, and making a soybean cropland suitability map based on GDD value. The potential land for soybean cultivation in West Sumatra based on land suitability class, physical characteristics, and GDD value is 267,539.09 hectares in class S1 (very suitable) and an area of 1,612,438.84 hectares in class S2 (appropriate enough). The most optimal planting time for soybean cultivation is in August. Lima Puluh Kota Regency, Pasaman Regency, Sijunjung Regency, and Solok Regency have land suitable for soybean cultivation with more than 200 thousand hectares of areas and are in areas with growing degree days suitable for soybean growth. [ABSTRACT FROM AUTHOR]

Premise: With the global atmospheric CO2 concentration on the rise, developing crops that can thrive in elevated CO2 has become paramount. We investigated the potential of hybridization as a strategy for creating crops with improved growth in predicted elevated atmospheric CO2. Methods: We grew parent accessions and their F1 hybrids of Arabidopsis thaliana in ambient and elevated atmospheric CO2 and analyzed numerous growth traits to assess their productivity and underlying mechanisms. Results: The heterotic increase in total dry mass, relative growth rate and leaf net assimilation rate was significantly greater in elevated CO2 than in ambient CO2. The CO2 response of net assimilation rate was positively correlated with the CO2 response of leaf nitrogen productivity and with that of leaf traits such as leaf size and thickness, suggesting that hybridization‐induced changes in leaf traits greatly affected the improved performance in elevated CO2. Conclusions: Vegetative growth of hybrids seems to be enhanced in elevated CO2 due to improved photosynthetic nitrogen‐use efficiency compared with parents. The results suggest that hybrid crops should be well‐suited for future conditions, but hybrid weeds may also be more competitive. [ABSTRACT FROM AUTHOR]

Plant growth regulators (PGRs) play an important role in increasing crop yield, and quality, and enhancing crop stress resistance in agricultural production, especially for important crops. PGRs can affect the transport and distribution of assimilates by changing the content and distribution of endogenous hormones in plants. Numerous empirical research results have proven that PGRs have an important impact on the growth, development, and yield composition of wheat. Taking wheat plants as an example, this study reviews the application of PGRs in wheat production and explores their impact on wheat growth and yield. Furthermore, residues and microbial degradation of PGRs are summarized in detail. Finally, future research directions on PGR application in wheat production are proposed. This summary is of great significance for understanding the role of PGRs in wheat production.

Given the critical role of precise meteorological parameter estimation in water resources management, particularly concerning the water footprint (WF) concept and considering the scarcity of data, this study utilized thirty years of data from four meteorological datasets to estimate the WF of two main cereals, wheat and maize, in Qazvin province, Iran. AquaCrop was used to calculate the WF parameters based on a synoptic station and the closest datasets to the synoptic station. Coefficient of determination (R2), root-mean-square deviation (RMSE) and its normalization (NRMSE), and maximum error (ME) were used to compare the results. The results showed that these datasets efficiently estimate the WF components and can be used instead of synoptic stations. Also, all datasets were more efficient in estimating the green WF than the blue WF. The Global Precipitation Climatology Center (GPCC) dataset was the most efficient dataset in assessing the WF components for wheat, where the RMSE and NRMSE were 84.8 m3/ton and 17.18%. These amounts were 55.1 m3/ton and 12.96% for the green WF. For estimating the blue WF of maize, the Climatic Research Unit (CRU) datasets were the most efficient datasets in assessing the WF components of maize, which were 35.58 m3/ton and 15.91%. This study demonstrated the robustness of meteorological datasets in accurately estimating the components of the WF. Furthermore, the study advocates for the utilization of diverse datasets in estimating meteorological and crop parameters, recommending this approach for different crops across various regions.

Phytocannabinoids represent the hallmark of the secondary metabolism of Cannabis sativa. The content of major phytocannabinoids is closely related to genetic variation as well as abiotic elicitors such as temperature, drought, and saline stress. The present study aims to evaluate hemp response to saline irrigation supplied as NaCl solutions with an electrical conductivity (EC) of 2.0, 4.0, and 6.0 dS m-1 (S1, S2, and S3, respectively) compared to a tap water control (S0). In addition, the potential beneficial effect of a plant-based biostimulant (a legume protein hydrolysate) inmitigating the detrimental effects of saline irrigation on crop growth and phytocannabinoid composition was investigated. Sodium chloride saline irrigation significantly reduced biomass production only with S2 and S3 treatments, in accordancewith an induced nutrient imbalance, as evidenced by the mineral profile of leaves. Multivariate analysis revealed that the phytocannabinoid composition, both in inflorescences and leaves, was affected by the salinity level of the irrigation water. Interestingly, higher salinity levels (S2-S3) resulted in the predominance of cannabidiol (CBD), compared to lower salinity ones (S0-S1). Plant growth and nitrogen uptake were significantly increased by the biostimulant application, with significant mitigation of the detrimental effect of saline irrigations [ABSTRACT FROM AUTHOR]

Tartary buckwheat (Fagopyrum tataricum) is a significant medicinal crop, with flavonoids serving as a crucial measure of its quality. Presently, the artificial cultivation of Tartary buckwheat yields low results, and the quality varies across different origins. Therefore, it is imperative to identify an effective method to enhance the yield and quality of buckwheat. Endophytic fungi reside within plants and form a mutually beneficial symbiotic relationship, aiding plants in nutrient absorption, promoting host growth, and improving secondary metabolites akin to the host. In this study, high-throughput sequencing technology was employed to assess the diversity of endophytic fungi in Tartary buckwheat. Subsequently, a correlation analysis was performed between fungi and metabolites, revealing potential increases in flavonoid content due to endophytic fungi such as Bipolaris, Hymenula, and Colletotrichum. Additionally, a correlation analysis between fungi and phenotypic traits unveiled the potential influence of endophytic fungi such as Bipolaris, Buckleyzyma, and Trichosporon on the phenotypic traits of Tartary buckwheat. Notably, the endophytic fungi of the Bipolaris genus exhibited the potential to elevate the content of Tartary buckwheat metabolites and enhance crop growth. Consequently, this study successfully identified the resources of endophytic fungi in Tartary buckwheat, explored potential functional endophytic fungi, and laid a scientific foundation for future implementation of biological fertilizers in improving the quality and growth of Tartary buckwheat. [ABSTRACT FROM AUTHOR]

There is great demand for the amelioration of saline–alkali soils, which requires efficient and economical amendments. Biochar addition could alleviate the adverse impacts of saline–alkali stress in crops. However, their efficiency and optimal amounts in saline–alkali soil restoration remain contradictory and inconclusive. The objective of this study was to investigate the effects of biochar application on the properties of saline–alkali soil and crop growth, as well as to determine the optimal application rate of biochar. We conducted pot experiments with biochar (B) application rates, including 0 (CK), 1% (B-1%), 2.5% (B-2.5%), 5% (B-5%), and 10% (B-10%), studying the impact of biochar on soil water content (SWC), soil salinity, soil electrical conductivity (EC), soil ion content, soil nutrients, soil enzyme activity, and crop growth. A four-parameter Gaussian function was established for the curves depicting the relationship between soil salinity characteristics and the biochar application rates to determine the most optimal application rate. The results indicated that: (1) Compared to the CK, all biochar treatments improved soil water-holding capacity and reduced soil Na+ content and sodium adsorption ratio (SAR). (2) B-1%, B-2.5%, and B-5% treatments reduced soil content, EC, Cl−, and SO42− content over CK, while the results were reversed for the B-10% treatment. (3) Compared to the CK, all biochar treatments significantly increased soil fertility, enhanced soil enzyme activity (alkaline phosphatase, catalase, and urease activity), and significantly promoted the growth of maize. (4) The results of the Gaussian model suggested that a biochar application rate of 3.16% is the optimal rate for alleviating soil salinity in saline–alkali soils. This research demonstrated the potential of biochar to improve soil properties and promote crop growth and provided useful information on biochar application rates for ameliorating saline–alkali soils. [ABSTRACT FROM AUTHOR]

Aboveground biomass (AGB) is a crucial physiological parameter for monitoring crop growth, assessing nutrient status, and predicting yield. Texture features (TFs) derived from remote sensing images have been proven to be crucial for estimating crops AGB, which can effectively address the issue of low accuracy in AGB estimation solely based on spectral information. TFs exhibit sensitivity to the size of the moving window and directional parameters, resulting in a substantial impact on AGB estimation. However, few studies systematically assessed the effects of moving window and directional parameters for TFs extraction on rice AGB estimation. To this end, this study used Unmanned aerial vehicles (UAVs) to acquire multispectral imagery during crucial growth stages of rice and evaluated the performance of TFs derived with different grey level co-occurrence matrix (GLCM) parameters by random forest (RF) regression model. Meanwhile, we analyzed the importance of TFs under the optimal parameter settings. The results indicated that: (1) the appropriate window size for extracting TFs varies with the growth stages of rice plant, wherein a small-scale window demonstrates advantages during the early growth stages, while the opposite holds during the later growth stages; (2) TFs derived from 45° direction represent the optimal choice for estimating rice AGB. During the four crucial growth stages, this selection improved performance in AGB estimation with R²=0.76 to 0.83 and rRMSE = 13.62% to 21.33%. Furthermore, the estimation accuracy for the entire growth season is R²=0.84 and rRMSE =21.07%. However, there is no consensus regarding the selection of the worst TFs computation direction; (3) Correlation (Cor), Mean, and Homogeneity (Hom) from the first principal component image reflecting internal information of rice plant and Contrast (Con), Dissimilarity (Dis), and Second Moment (SM) from the second principal component image expressing edge texture are more important to estimate rice AGB among the whole growth stages; and (4) Considering the optimal parameters, the accuracy of texture-based AGB estimation slightly outperforms the estimation accuracy based on spectral reflectance alone. In summary, the present study can help researchers confident use of GLCM-based TFs to enhance the estimation accuracy of physiological and biochemical parameters of crops. [ABSTRACT FROM AUTHOR]

Individual hydrological and crop growth models often oversimplify underlying processes, reducing the accuracy of both simulated hydrology and crop growth dynamics. While crop models tend to generalize soil moisture processes, most hydrological models commonly use constant vegetation parameters and prescribed phenologies, neglecting the dynamic nature of crop growth. Despite some studies that have coupled hydrological and crop models, a limited understanding exists regarding the feedbacks between hydrology and crop growth. Our objective is to quantify the feedback between crop systems and hydrology on a fine-grained spatio-temporal level. To this end, the PCR-GLOBWB 2 hydrological model was coupled with the WOFOST crop growth model to quantify both the one-way and two-way interactions between hydrology and crop growth on a daily timestep and at 5 arc minutes (~10 km) resolution. Our study spans the Contiguous United States (CONUS) region and covers the period from 1979 to 2019, allowing a comprehensive evaluation of the feedback between hydrology and crop growth dynamics. We compare individual (stand-alone) as well as one-way and two-way coupled WOFOST and PCR-GLOBWB 2 model runs and evaluate the average crop yield and its interannual variability for rainfed and irrigated crops as well as simulated irrigation water withdrawal for maize, wheat and soybean. Our results reveal distinct patterns in the temporal and spatial variation of crop yield depending on the included interactions between hydrology and crop systems. Evaluating the model results against reported yield and water use data demonstrates the efficacy of the coupled framework in replicating observed irrigated and rainfed crop yields. Our results show that two-way coupling, with its dynamic feedback mechanisms, outperforms one-way coupling for rainfed crops. This improved performance stems from the feedback of WOFOST crop phenology to the crop parameters in the hydrological model. Our results suggest that when crop models are combined with hydrological models, a two-way coupling is needed to capture the impact of interannual climate variability on food production. [ABSTRACT FROM AUTHOR]

Trichoderma spp. are widely used to enhance crop growth and suppress diverse diseases. However, inconsistent field efficacy remains a major barrier to their use as a reliable alternative to synthetic pesticides. Various strategies have been investigated to enhance the robustness of their application. Here, we evaluated how T. virens application methods (pre-, at-, and post-transplant) affect the growth of two tomato varieties and their rhizosphere fungal and bacterial communities. Although the greatest rhizosphere abundance of T. virens was observed in the post-transplant application, the at-transplant application promoted tomato growth the most, indicating that greater rhizosphere abundance does not necessarily result in better tomato growth. None of the application methods significantly altered the global rhizosphere fungal and bacterial communities of the tested varieties. Changes in specific microbial genera and guilds may underpin the enhanced tomato growth. We also investigated whether the resulting microbiome changes affect the mycelial growth and conidial germination of Fusarium oxysporum f. sp. lycopersici and F. oxysporum f. sp. radicis-lycopersici, soilborne fungal pathogens of tomato, upon exposure to volatile compounds emitted by culturable rhizosphere microbes and metabolites extracted from the rhizosphere soils after Trichoderma treatments. Volatile compounds produced by cultured rhizosphere microbes after the at-transplant application suppressed the mycelial growth of both pathogens better than those after the other treatments. Similarly, water-soluble metabolites extracted from the rhizosphere soil samples after the at-transplant application most effectively suppressed the germination rate of F. oxysporum spores. Overall, our results suggest that the at-transplant application is most advantageous for promoting the growth of the tested tomato varieties and building soil suppressiveness against the tested fusaria. However, further studies are needed before applying this method to support tomato production. We discuss critical future questions. [ABSTRACT FROM AUTHOR]

Salinity is a major abiotic stress that seriously affects crop growth worldwide. In this work, we aimed to isolate potential halotolerant plant growth-promoting rhizobacteria (PGPR) to mitigate the adverse impacts of salt stress in rice. An isolate, D2, with multiple plant growth-promoting (PGP) characteristics was identified as Enterobacter asburiae D2. Strain D2 could produce indole-3-acetic acid and siderophore. It also exhibited phosphate solubilization and 1-aminocyclopropane-1-carboxylic deaminase activity. Genome analysis further provided insights into the molecular mechanism of its PGP abilities. Strain D2 inoculation efficiently stimulated rice growth under both normal and saline conditions. Compared with the non-inoculated plants, a significant increase in plant height (18.1–34.7%), root length (25.9–57.1%), root dry weight (57.1–150%), and shoot dry weight (17.3–50.4%) was recorded in inoculated rice seedlings. Meanwhile, rice seedlings inoculated with strain D2 showed improvement in chlorophyll and proline content, while the oxidant damage was reduced in these plants in comparison with the control group. Moreover, the K+/Na+ ratio of the inoculated rice seedlings exposed to NaCl and Na2CO3 was higher than that of the uninoculated groups. These results imply that Enterobacter asburiae D2 is a potential PGPR that can be used for alleviation of salt stress in rice. [ABSTRACT FROM AUTHOR]

An Elite Spring Wheat Yield Trial (EWYT) was conducted with 50 diverse genotypes of Wheat (Triticum aestivum L.) and analyzed by multivariate analysis during 2018-19 rabi season. Correlation analysis revealed positive association of plant height, grains per spike, spike length, test weight and biomass with grain yield. Path analysis revealed the highest direct effect on grain yield/metre by biomass/metre (1.508) which was also positively associated with grain yield/metre (0.833). PCA analysis showed 11 principal components out of which five principal components (PC1 to PC5) exhibited eigen value greater than one. The correlation between AUDPC and physiological characters indicated that chlorophyll loss was associated with high spot blotch disease incidence at later stages of crop growth. [ABSTRACT FROM AUTHOR]

The structure of soil is critical for the ecosystem services it provides since it regulates many key soil processes, including water, air and solute movement, root growth and the activity of soil biota. Soil structure is dynamic, driven by external factors such as land management and climate and mediated by a wide range of biological agents and physical processes operating at strongly contrasting time‐scales, from seconds (e.g., tillage) to many decades (e.g., faunal activity and soil aggregation). In this respect, positive feedbacks in the soil–plant system may lead in the longer term to soil physical degradation or to the recovery of structurally poor soils. As far as we are aware, no existing soil‐crop model can account for such processes. In this paper, we describe a new soil‐crop model (USSF, Uppsala model of Soil Structure and Function) that accounts for the effects of soil structure dynamics on water and organic matter cycling at the soil profile scale. Soil structure dynamics are expressed as time‐varying physical (bulk density, porosity) and hydraulic properties (water retention, hydraulic conductivity) responding to the activity of biological agents (i.e., earthworms, plant roots) and physical processes (i.e., tillage, soil swell‐shrink) at seasonal to decadal time‐scales. In this first application of the model, we present the results of 30‐year scenario simulations that illustrate the potential role and importance of soil structure dynamics for the soil water balance, carbon storage in soil, root growth, and winter wheat yields on two soils (loam and clay) in the climate of central Sweden. A sensitivity analysis was also performed for these two scenarios using the Morris method of elementary effects, which revealed that the most sensitive parameters controlling soil structure dynamics in the USSF model are those determining aggregation induced by organic matter turnover and swell/shrink. We suggest that the USSF model is a promising new tool to investigate a wide range of processes and phenomena triggered by land use and climate change. Results from this study show that feedback in the soil‐crop system mediated by the dynamics of soil physical and hydraulic properties are potentially of central importance for long‐term predictions of soil water balance, crop production, and carbon sequestration under global change. [ABSTRACT FROM AUTHOR]

In order to reveal the yield-increasing mechanism of relay intercropping (RI) maize with different varieties from the perspective of plant growth, source sink relationship, and root growth, a two-factor randomized block design trial was designed, which includes different maize varieties (Rongyu1210 (RY1210), Zhongyu 3 (ZY3)) and plant pattern (RI, Sole cropping (SC)). The leaf area index (LAI), dry matter accumulation and distribution, root dry weight (RDW), root length (RL), root surface area (RSA), root volume (RV), and maize yield were determined. LAI of RI RY1210 was significantly higher than that of the SC RY1210 at the filling stage and maturity stage. The dry matter accumulation of RI RY1210 ear was significantly higher than that of SC RY1210 and RI ZY3, and the RDW of RY1210 was significantly higher than that of ZY3. The ratio of RDW of RI RY1210 was higher than that of RI ZY3 in the 20–40 and 40–60 cm soil layers, respectively. The RDW, RL, RV, and RSA of RI RY1210 were significantly lower than that of sole RY1210 by 25.43%, 10.75%, 30.79%, and 23.73%, respectively, but higher than that of RI ZY3 by 143.98%, 278.29%, 54.40%, and 29.57%, respectively. The average yield of RI RY1210 was 8782.71 kg ha−1, with no significant difference compared to SC, which was mainly attributed to a larger ear dry matter accumulation, higher LAI in later growth stages, larger RDW, and the ratio of roots in deeper soil layers. This study will be useful and helpful to farmers for how to select and plant high-yielding maize varieties in strip relay intercropping. [ABSTRACT FROM AUTHOR]

The effects of the co-location of energy production from a photovoltaic (PV) plant and aromatic crops (thyme, oregano, and Greek mountain tea) in a hot and dry environment have been investigated in Enel Green Power PV plant located in Kourtesi (Greece). The study was aimed at evaluating the influence of the PV plant on microclimate, on soil temperature and water potential, and on the crops' growth in a testing area (the corridors between two modules rows) compared to a full sunlight control area. The net radiation and of the wind speed recorded in the testing area showed a 44% and 38% reduction respectively, compared to the control area, while air temperature and relative humidity did not show any difference. Among crop/soil monitored parameters, cumulative reference evapotranspiration (ET0) and the average soil temperature were found 29% and 8% lower in the testing area, conversely the soil water potential (SWP) was 34% higher compared to control area. No significant differences in the plant growth have been detected between testing and control areas, except for oregano whose weight was higher in testing area. The results suggest that in hot and dry climatic conditions, the reduction of climatic stress could compensate the decrease of photosynthesis due to the shading effect of the PV modules, thus not damaging crops' growth. [ABSTRACT FROM AUTHOR]

To sustain crop growth following soil water deficit, it is essential to have rapid recovery of leaf gas exchange. One basis for rapid recovery would be the rapid return of root hydraulic conductance to predrought levels to support water transport to the plant shoot. In this study, transpiration and root hydraulic conductance were measured over a 9‐day recovery period following an initial water‐deficit treatment of three maize (Zea mays L.) cultivars. In addition, xylem vessel diameter was measured during the recovery period at different positions from the root tip. The initiation of recovery in the transpiration rate occurred in all three cultivars within 3 days after watering, although the root conductance and transpiration rate of one cultivar were much lower than the other two cultivars. Root conductance and vessel diameter increased more slowly than the recovery of transpiration. There was an indication that transpiration could have been limited by root hydraulic conductance only when its values were low during recovery. The relationship between hydraulic conductance and vessel diameter did not, however, indicate a Poiseuille's law relationship between the two variables. Overall, cultivar variability in recovery from water deficit of the transpiration rate and root hydraulic conductance indicates that the selection for rapid recovery of leaf gas exchange following water deficit could be an important component of genotype selection in maize breeding programs. Core Ideas: Root hydraulic flow characteristics are rarely studied following water‐deficit treatments.Transpiration in three maize cultivars recovered 3 days after watering.Root hydraulic conductance and xylem vessel diameter recovered over a longer time period than transpiration.Differences were found among cultivars in their temporal recovery pattern of hydraulic flow characteristics. [ABSTRACT FROM AUTHOR]

A comparative evaluation of grain legumes is essential for the effective planning of legume-based agricultural systems in a given environment. The goal of this work was to contrast the growth, translocation of assimilates, and grain yield of spring-planted common vetch (Vicia sativa L.), red pea (Lathyrus cicera L.), lentil (Lens culinaris Medik.), chickpea (Cicer arietinum L.), and field pea (Pisum sativa L.) under rainfed Mediterranean conditions. Two cultivars of each species were cultivated on a silty clay soil in northeastern Greece for 2 years (2014 and 2015) with contrasting rainfall patterns. Chickpea and field pea exhibited better early crop growth rate than any other legume. Species differences in assimilates availability prior to grain filling affected the remobilization of assimilates to seed, which increased by 45% for every kg ha−1 rise in early dry matter accumulation. Dry matter translocation efficiency varied from 9 to 51% depending on species and year. Red pea was the best option in terms of seed yield, regardless of the seasonal rainfall. Chickpea in the drier year (2015) and field pea in the wetter year (2014) produced seed yields that were comparable to that of red pea. Lentil and common vetch were generally less productive species in terms of seed yield. Species seed yield was associated with their ability to accumulate biomass either before podding (r = 0.52, P < 0.05) or at maturity (r = 0.51, P < 0.05), but not with harvest index or translocation of dry matter. Findings provide new knowledge regarding growth attributes and reallocation of assimilate in five legume species grown simultaneously in the same environment, which has never been studied before. In addition, results highlight that selecting species with enhanced early or final biomass potential as well as adopting cultural practices that promote biomass accumulation in the growing season appear to be effective management strategies for improving seed yield of the tested grain legumes under Mediterranean conditions. [ABSTRACT FROM AUTHOR]