Growth Status Research Articles

Plant Biostimulants Enhance Tomato Resilience to Salinity Stress: Insights from Two Greek Landraces

Salinity, one of the major abiotic stresses in plants, significantly hampers germination, photosynthesis, biomass production, nutrient balance, and yield of staple crops. To mitigate the impact of such stress without compromising yield and quality, sustainable agronomic practices are required. Among these practices, seaweed extracts (SWEs) and microbial biostimulants (PGRBs) have emerged as important categories of plant biostimulants (PBs). This research aimed at elucidating the effects on growth, yield, quality, and nutrient status of two Greek tomato landraces (‘Tomataki’ and ‘Thessaloniki’) following treatments with the Ascophyllum nodosum seaweed extract ‘Algastar’ and the PGPB ‘Nitrostim’ formulation. Plants were subjected to bi-weekly applications of biostimulants and supplied with two nutrient solutions: 0.5 mM (control) and 30 mM NaCl. The results revealed that the different mode(s) of action of the two PBs impacted the tolerance of the different landraces, since ‘Tomataki’ was benefited only from the SWE application while ‘Thessaloniki’ showed significant increase in fruit numbers and average fruit weight with the application of both PBs at 0.5 and 30 mM NaCl in the root zone. In conclusion, the stress induced by salinity can be mitigated by increasing tomato tolerance through the application of PBs, a sustainable tool for productivity enhancement, which aligns well with the strategy of the European Green Deal.

Multitemporal Field-Based Maize Plant Height Information Extraction and Verification Using Solid-State LiDAR

Plant height is regarded as a key indicator that is crucial for assessing the crop growth status and predicting yield. In this study, an advanced method based on solid-state LiDAR technology is proposed, which is specifically designed to accurately capture the phenotypic characteristics of plant height during the maize growth cycle. By segmenting the scanned point cloud of maize, detailed point cloud data of a single maize plant were successfully extracted, from which stem information was accurately measured to obtain accurate plant height information. In this study, we will concentrate on the analysis of individual maize plants. Leveraging the advantages of solid-state LiDAR technology in precisely capturing phenotypic information, the data processing approach for individual maize plants, as compared to an entire maize community, will better restore the maize’s original growth patterns. This will enable the acquisition of more accurate maize plant height information and more clearly demonstrate the potential of solid-state LiDAR in capturing detailed phenotypic information. To enhance the universality of the research findings, this study meticulously selected key growth stages of maize for data validation and comparison, encompassing the tasseling, silking, and maturity phases. At these crucial stages, 20 maize plants at the tasseling stage, 40 at the flowering stage, and 40 at the maturity stage were randomly selected, totaling 100 samples for analysis. Each sample not only included actual measurement values but also included plant height information extracted using point cloud technology. The observation period was set from 20 June to 20 September 2021. This period encompasses the three key growth stages of maize described above, and each growth stage included one round of data collection, with three rounds of data collection each, each spaced about a week apart, for a total of nine data collections. To ensure the accuracy and reliability of the data, all collections were performed at noon when the natural wind speed was controlled within the range of 0 to 1.5 m/s and the weather was clear. The findings demonstrate that the root mean square error (RMSE) of the maize plant height data, procured through LiDAR technology, stands at 1.27 cm, the mean absolute percentage error (MAPE) hovers around 0.77%, and the peak R2 value attained is 0.99. These metrics collectively attest to the method’s ongoing high efficiency and precision in capturing the plant height information. In the comparative study of different stem growth stages, especially at the maturity stage, the MAPE of the plant height was reduced to 0.57%, which is a significant improvement compared to the performance at the nodulation and sprouting stage. These results effectively demonstrate that the maize phenotypic information extraction method based on solid-state LiDAR technology is not only highly accurate and effective but is also effective on individual plants, which provides a reliable reference for applying the technique to a wider range of plant populations and extending it to the whole farmland.

Continuous Leaf Area Index (LAI) Observation in Forests: Validation, Application, and Improvement of LAI-NOS

The leaf area index (LAI) is one of the core parameters reflecting the growth status of vegetation. The continuous long-term observation of the LAI is key when assessing the dynamic changes in the energy exchange of ecosystems and the vegetation’s response indicators to climate change. The errors brought about by non-standard operations in manual LAI measurements hinder the further research utilization of this parameter. The long-term automatic LAI observation network is helpful in reducing errors from manual measurements. To further test the applicability of automatic LAI observation instruments in forest environments, this study carried out comparative validation research of the LAI-NOS (LAI automatic network observation system) at the Wanglang Mountain Ecological Remote Sensing Comprehensive Observation Station, China, comparing it with the results measured by the LAI-2200 Plant Canopy Analyzer (LI-COR, Lincoln, NE, USA), the LAI-probe handheld instrument, and a fisheye lens digital camera (DHP method). Instead of using the original “smoothest window” method, a new method, the “sunrise–sunset” method, is used to extract daily LAI-NOS LAI, and the corresponding confidence level is used to filter the data. The results of the data analysis indicate the following: LAI-NOS has a high data stability. The automatically acquired daily data between two consecutive days has a small deviation and significant correlations. Single-angle/multi-angle LAI measurement results of the LAI-NOS have good correlations with the LAI-2200 (R2 = 0.512/R2 = 0.652), the LAI-probe (R2 = 0.692/R2 = 0.619), and the DHP method (R2 = 0.501/R2 = 0.394). The daily LAI obtained from the improved method, when compared to the original method, both show the same vegetation growth trend. However, the improved method has a smaller dispersion. This study confirms the stability and accuracy of automatic observation instruments in mountainous forests, demonstrating the distinct advantages of automatic measurement instruments in the long-term ground observation of LAIs.

Safety and efficacy of monthly high-dose vitamin D3 supplementation in children and adolescents with sickle cell disease.

Little is known about the impact of vitamin D supplementation on hand grip strength (HGS) and health-related quality of life (HRQoL) in children and adolescents with sickle cell disease (SCD). We aimed to evaluate the safety and efficacy of monthly high-dose vitamin D3 supplementation and its implications on bone mineral density (BMD), HGS, and HRQoL in patients with SCD and healthy controls. The study included 42 children with SCD and 42 healthy matched controls. The study participants were supplemented with high-dose monthly oral vitamin D3. Changes in the serum level of 25(OH) vitamin D3, maximum HGS, and BMD from baseline to 6months were assessed, and the HRQoL questionnaire and Childhood Health Assessment Questionnaire (CHAQ) were used to evaluate the functional capacity. At baseline, SCD subjects had poorer growth status indicated by negative Z scores. Suboptimal BMD was detected by significantly lower Z score, and lower HGS and worse HRQL parameters were found compared to the controls (P < 0.001). Median 25(OH) vitamin D3 was significantly lower in SCD patients compared to controls (16.5 vs. 28ng/mL, respectively (P < 0.001)). After 6months of vitamin D supplementation, there was significant improvement in the DEXA Z-score (P < 0.001), limitation of physical health (P = 0.02), pain scores (P < 0.001), and CHAQ grades (P = 0.01) in SCD patients. A significant improvement in HGS (P < 0.001 and P = 0.005) as well as the CHAQ score (P < 0.001 and P = 0.003) was detected in the SCD group and controls, respectively. There were no reported clinical adverse events (AEs) or new concomitant medications (CMs) during the study duration, and safe levels of Ca and 25 (OH) D3 were observed at 3 and 6months for both groups. There was a significant positive correlation between HGS and total physical score (r = 0.831, P < 0.001) and a negative correlation with CHAQ score (r = - 0.685, P < 0.001). We also detected a significant positive correlation between vitamin D levels at 6months and HGS (r = 0.584, P < 0.001), pain score (r = 0.446, P < 0.001), and a negative correlation with CHAQ score (r = - 0.399, P < 0.001). Conclusion: Monthly oral high-dose vitamin D supplementation was safe and effective in improving vitamin D levels, HGS, and HRQoL in SCD children and healthy subjects, and BMD scores in SCD patients. Further randomized controlled trials are warranted to assess an optimal dosing strategy and to investigate the impact on clinically significant outcomes in children and adolescents with SCD and their healthy counterparts. Trial registration: ClinicalTrials.gov , identifier NCT06274203, date of registration: 23/02/2024, retrospectively registered. What is known: • Several studies have reported a high prevalence of vitamin D deficiency and suboptimal bone mineral density (BMD) in sickle cell disease (SCD) patients. • Musculoskeletal dysfunction is reported in SCD patients with a negative impact on physical activity and health-related quality of life (HRQL). • Little is known regarding the impact of vitamin D3 supplementation in children and adolescents with SCD. What is new: • We found that monthly oral high-dose vitamin D3 supplementation was safe, tolerated, and effective in improving serum vitamin D levels, HGS, BMD scores, and HRQL in SCD patients.

Animal Detection based Smart Farming in Animal Repellent Using AI and Deep Learning

The combination of artificial intelligence (AI) and deep learning in agriculture has ushered in a new era in agriculture with new solutions designed to solve many problems. This paper presents an animal killing system for smart agriculture that uses artificial intelligence and deep learning to reduce the growing problem of animal damage. As the world population continues to grow, increasing food availability is important; Therefore, it is critical to protect crops from wild animals and pests. Deforestation due to livestock farming has become one of the largest human-wildlife conflicts due to human interference with habitats and deforestation. Wild animals can kill farmers working in the fields, causing major crop losses. Farmers suffered huge crop losses due to wild animals such as elephants, wild boars and deer attacking agriculture. Protecting crops from wild animals is one of the biggest concerns of today's farmers. There are many ways to solve this problem, both lethal (such as shooting and trapping) and non-lethal. (such as railings, pesticides, organic matter, netting or electric fencing). The sensor rotates around the lens and uses DCNN software to detect the target. If an animal is found, it sends a message to the Animal Repellent Module with information on the type of ultrasound that should be produced based on the animal. The development of drones with controlled flight control, as well as lightweight and powerful hyperspectral snapshot cameras that can be used to calculate crop biomass growth and fertilization status, responds to complex agricultural management strategies. KEYWORDS: Animal detection, VGG-Net, Bi-LSTM, convolutional neural network, activity recognition, video surveillance, wild animal monitoring, alert system.

Design of intelligent agricultural landscape planning and ecological balance control system based on remote sensing images

Abstract With the modernization of agricultural production and the acceleration of urbanization, agricultural landscape planning and ecological balance control have become important issues in promoting sustainable development. Traditional agricultural production methods have problems such as resource waste, environmental pollution, and ecological damage. This article aimed to achieve scientific planning and management of agricultural landscapes, and promote the efficiency of agricultural production, rational utilization of resources, and protection of the ecological environment, thereby promoting sustainable agricultural development. This study first focused on denoising and feature extraction of agricultural remote sensing data images, using remote sensing technology to obtain agricultural landscape information. After that, artificial intelligence was adopted to achieve intelligent agricultural landscape planning, with the goal of maintaining ecological balance and promoting efficient, eco-friendly, and sustainable agricultural production. This study took the landscape of a certain city as an example to test the processing effect of remote sensing images, and it was proved that the effect was good. We tested the performance of an intelligent agricultural landscape planning and ecological balance control system based on remote sensing images. According to the experimental results, it can be concluded that the resource utilization efficiency of farmland A monitored by the intelligent agricultural landscape planning system using remote sensing image technology was 82%, while the traditional one was only 60%. This indicated that the collection effect of remote sensing image technology was much better than that of traditional technology. This article comprehensively and timely monitored and evaluated farmland through remote sensing image technology, including crop growth status, soil moisture, nutritional status, etc. The system can provide precise planting and management suggestions for farmers based on this information, and help them optimize farmland layout, crop selection, and irrigation management, thereby improving the production efficiency of farmland and crop yield.

SIRT3 protects endometrial receptivity in patients with polycystic ovary syndrome.

The sirtuin family is well recognized for its crucial involvement in various cellular processes. Nevertheless, studies on its role in the human endometrium are limited. This study aimed to explore the expression and localization of the sirtuin family in the human endometrium, focusing on sirtuin 3 (SIRT3) and its potential role in the oxidative imbalance of the endometrium in polycystic ovary syndrome (PCOS). Endometrial specimens were collected from both patients with PCOS and controls undergoing hysteroscopy at the Center for Reproductive Medicine, Peking University Third Hospital, from July to August 2015 and used for cell culture. The protective effects of SIRT3 were investigated, and the mechanism of SIRT3 in improving endometrial receptivity of patients with PCOS was determined using various techniques, including cellular bioenergetic analysis, small interfering ribonucleic acid (siRNA) silencing, real-time quantitative polymerase chain reaction, Western blot, immunofluorescence, immunohistochemistry, and flow cytometry analysis. The sirtuin family was widely expressed in the human endometrium, with SIRT3 showing a significant increase in expression in patients with PCOS compared with controls (P <0.05), as confirmed by protein and gene assays. Concurrently, endometrial antioxidant levels were elevated, while mitochondrial respiratory capacity was reduced, in patients with PCOS (P <0.05). An endometrial oxidative stress (OS) model revealed that the downregulation of SIRT3 impaired the growth and proliferation status of endometrial cells and reduced their receptivity to day 4 mouse embryos. The results suggested that SIRT3 might be crucial in maintaining normal cellular state by regulating antioxidants, cell proliferation, and apoptosis, thereby contributing to enhanced endometrial receptivity. Our findings proposed a significant role of SIRT3 in improving endometrial receptivity in patients with PCOS by alleviating OS and regulating the balance between cell proliferation and apoptosis. Therefore, SIRT3 could be a promising target for predicting and improving endometrial receptivity in this patient population.

Method for Monitoring Wheat Growth Status and Estimating Yield Based on UAV Multispectral Remote Sensing

An efficient and accurate estimation of wheat growth and yield is important for wheat assessment and field management. To improve the accuracy and stability of wheat growth and yield estimation, an estimation method based on a genetic algorithm-improved support vector regression (GA-SVR) algorithm was proposed in this study. The correlation analysis between vegetation indices calculated from spectral data and wheat growth phenotypes and yields was performed to obtain the optimal combination of vegetation indices with high correlation and good estimation performance. At the same time, the optimal model for wheat growth monitoring was screened and constructed in experiments with 12 wheat varieties and 3 gradient nitrogen fertilizer application levels. Then, the yield estimation model was established and its applicability was verified under different nitrogen fertilizer application levels. The results showed that the constructed models for the leaf area index, plant height, and yield estimation performed well, with coefficients of determination of 0.82, 0.71, and 0.70, and root mean square errors of 0.09, 2.7, and 68.5, respectively. This study provided an effective UAV remote sensing technique for monitoring wheat growth status and estimating yield. This study provides an effective unmanned aerial remote sensing technique for monitoring wheat growth and estimating yield, and provides technical support for wheat yield assessment and field management.

USP7 cardiomyocyte specific knockout causes disordered mitochondrial biogenesis and dynamics and early neonatal lethality in mice

BackgroundUbiquitination is an enzymatic modification involving ubiquitin chains, that can be reversed by deubiquitination (DUB) enzymes. Ubiquitin-specific protease 7 (USP7), which is also known as herpes virus-associated ubiquitin-specific protease (HAUSP), has been shown to play a vital role in cardiovascular diseases. However, the underlying molecular mechanism by which USP7 regulates cardiomyocyte function has not been reported. MethodsTo understand the physiological function of USP7 in the heart, we constructed cardiomyocyte-specific USP7 conditional knockout mice. ResultsWe found that homozygous knockout mice died approximately three weeks after birth, while heterozygous knockout mice grew normally into adulthood. Severe cardiac dysfunction, hypertrophy, fibrosis, and cell apoptosis were observed in cardiomyocyte-specific USP7 knockout mice, and these effects were accompanied by disordered mitochondrial dynamics and cardiometabolic-related proteins. ConclusionsIn summary, we investigated changes in the growth status and cardiac function of cardiomyocyte-specific USP7 knockout mice, and preliminarily explored the underlying mechanism.

Intra-annual dynamics of stem circumference variation and water status of four coniferous tree species (Pinus sylvestris, Picea abies, Larix decidua and Abies alba) under warmer and water-limited conditions

AbstractIn the paper, the intra-annual growth patterns and tree water balance of four different tree species (Pinus sylvestris, Picea abies, Larix decidua and Abies alba) were examined. Seasonal radial increment, tree water deficit (ΔW) and maximum daily shrinkage (MDS) were derived from the records obtained using high-resolution digital band dendrometers. The study area was located in Arboretum Borová hora (350 m a. s. l., Zvolen valley, Central Slovakia) characterised by a warmer climate (Picea abies) and warmer and drier climate (Abies alba, Larix decidua, Pinus sylvestris) compared to the sites of tree origins. Monitored species exhibited remarkably distinct growth and water balance patterns over the 2015 growing season characterised with the highly above normal temperature and uneven precipitation distribution. A. alba exhibited smooth continuous growth least affected by varying environmental conditions. Of all analysed species, only A. alba showed significant positive correlations of radial growth and ΔW with temperature and global radiation, despite environmental water limitations. The lowest cumulative growth, lower negative values of ΔW and greater MDS of L. decidua indicate a higher water limitation of this species. The results showed more pronounced sensitivity of P. sylvestris to increased temperature and drought. All monitored variables of environmental conditions, except precipitation, significantly influenced MDS values of all studied tree species. Based on 30 variables describing radial stem growth patterns and water status we identified large inter-species variability and discrete species-specific groups, while the indicators of growth and water status of L. decidua and P. sylvestris were similar and the most different patterns were observed between A. alba and L. decidua. The behaviour of P. abies was closer to A. alba than to the other two species.

Integrated phenotypic, transcriptomics and metabolomics: growth status and metabolite accumulation pattern of medicinal materials at different harvest periods of Astragalus Membranaceus Mongholicus

BackgroundAstragalus membranaceus var. mongholicus (Astragalus), acknowledged as a pivotal “One Root of Medicine and Food”, boasts dual applications in both culinary and medicinal domains. The growth and metabolite accumulation of medicinal roots during the harvest period is intricately regulated by a transcriptional regulatory network. One key challenge is to accurately pinpoint the harvest date during the transition from conventional yield content of medicinal materials to high and to identify the core regulators governing such a critical transition. To solve this problem, we performed a correlation analysis of phenotypic, transcriptome, and metabolome dynamics during the harvesting of Astragalus roots.ResultsFirst, our analysis identified stage-specific expression patterns for a significant proportion of the Astragalus root genes and unraveled the chronology of events that happen at the early and later stages of root harvest. Then, the results showed that different root developmental stages can be depicted by co-expressed genes of Astragalus. Moreover, we identified the key components and transcriptional regulation processes that determine root development during harvest. Furthermore, through correlating phenotypes, transcriptomes, and metabolomes at different harvesting periods, period D (Nov.6) was identified as the critical period of yield and flavonoid content increase, which is consistent with morphological and metabolic changes. In particular, we identified a flavonoid biosynthesis metabolite, isoliquiritigenin, as a core regulator of the synthesis of associated secondary metabolites in Astragalus. Further analyses and experiments showed that HMGCR, 4CL, CHS, and SQLE, along with its associated differentially expressed genes, induced conversion of metabolism processes, including the biosynthesis of isoflavones and triterpenoid saponins substances, thus leading to the transition to higher medicinal materials yield and active ingredient content.ConclusionsThe findings of this work will clarify the differences in the biosynthetic mechanism of astragaloside IV and calycosin 7-O-β-D-glucopyranoside accumulation between the four harvesting periods, which will guide the harvesting and production of Astragalus.

Phosphate solubilizing Pseudomonas and Bacillus combined with rock phosphates promoting tomato growth and reducing bacterial canker disease.

Nowadays, sustainable agriculture approaches are based on the use of biofertilizers and biopesticides. Tomato (Solanum lycopersicum L.) rhizosphere could provide rhizobacteria with biofertilizing and biopesticide properties. In this study, bacteria from the rhizosphere of tomato were evaluated in vitro for plant growth promotion (PGP) properties. Five Pseudomonas isolates (PsT-04c, PsT-94s, PsT-116, PsT-124, and PsT-130) and one Bacillus isolate (BaT-68s), with the highest ability to solubilize tricalcium phosphate (TCP) were selected for further molecular identification and characterization. Isolates showed phosphate solubilization up to 195.42 μg mL-1. All isolates showed phosphate solubilization by organic acid production. The six isolates improved seed germination and showed effective root colonization when tomato seeds were coated with isolates at 106 cfu g-1 in axenic soil conditions. Furthermore, the selected isolates were tested for beneficial effects on tomato growth and nutrient status in greenhouse experiments with natural rock phosphate (RP). The results showed that inoculated tomato plants in the presence of RP have a higher shoot and root lengths and weights compared with the control. After 60 days, significant increases in plant Ca, Na, P, protein, and sugar contents were also observed in inoculated seedlings. In addition, inoculated tomato seedlings showed an increase in foliar chlorophyll a and b and total chlorophyll, while no significant changes were observed in chlorophyll fluorescence. In greenhouse, two Pseudomonas isolates, PsT-04c and PsT-130, showed ability to trigger induced systemic resistance in inoculated tomato seedlings when subsequently challenged by Clavibacter michiganensis subsp. michiganensis, the causal agent of tomato bacterial canker. High protection rate (75%) was concomitant to an increase in the resistance indicators: total soluble phenolic compounds, phenylalanine-ammonia lyase, and H2O2. The results strongly demonstrated the effectiveness of phosphate-solubilizing bacteria adapted to rhizosphere as biofertilizers for tomato crops and biopesticides by inducing systemic resistance to the causal agent of tomato bacterial canker disease.

Automatic Shrimp Fry Counting Method Using Multi-Scale Attention Fusion.

Shrimp fry counting is an important task for biomass estimation in aquaculture. Accurate counting of the number of shrimp fry in tanks can not only assess the production of mature shrimp but also assess the density of shrimp fry in the tanks, which is very helpful for the subsequent growth status, transportation management, and yield assessment. However, traditional manual counting methods are often inefficient and prone to counting errors; a more efficient and accurate method for shrimp fry counting is urgently needed. In this paper, we first collected and labeled the images of shrimp fry in breeding tanks according to the constructed experimental environment and generated corresponding density maps using the Gaussian kernel function. Then, we proposed a multi-scale attention fusion-based shrimp fry counting network called the SFCNet. Experiments showed that our proposed SFCNet model reached the optimal performance in terms of shrimp fry counting compared to CNN-based baseline counting models, with MAEs and RMSEs of 3.96 and 4.682, respectively. This approach was able to effectively calculate the number of shrimp fry and provided a better solution for accurately calculating the number of shrimp fry.

Response of urban green space cooling effect to urbanization in the Three Ring Road area of Changsha City

The significance of urban green spaces (UGS) in alleviating the urban heat island effect has attracted increasing attention. The size, growth dynamics, and surroundings of UGS evolve with urbanization. However, the impact of these changes on the UGS cooling remains unknown, hindering the formulation of targeted greening policies at different urbanization stages. Focused on the Three Ring Road area in Changsha, comprehensive urbanization indexes from 2000 to 2020 were computed, identifying the periods characterized by high-speed growth, transition, and steady development. By calculating the cooling indicators of UGS, employing partial correlation analysis and geographic detectors, this study clarified the determinants of the cooling effect of UGS. Results revealed that urbanization significantly impacted the cooling effect of UGS, with the cooling gradient, intensity, range, and distance exhibiting a gradual increase. Meanwhile, cooling efficiency demonstrated an initial ascent followed by a subsequent decline. Notably, the pivotal factors influencing UGS cooling effect shifted from external factors (surrounding construction and ecological land) to internal factors (growth status), and eventually to the synergy of both internal and external factors. This research contributed valuable insights for delineating optimal UGS cooling strategies across diverse urbanization stages to improve urban climate adaptability.

Dietary administration impact of olive pulp on growth performance, metabolic profile, immune status, and antioxidant potential of gilthead seabream (Sparus aurata L.)

Dietary administration impact of olive pulp on growth performance, metabolic profile, immune status, and antioxidant potential of gilthead seabream (Sparus aurata L.)

Agricultural Environment and Intelligent Plant Protection Equipment

Intelligent plant protection equipment utilizes advanced sensor technology and data analysis algorithms to achieve real-time monitoring and precise management of crop growth status, pest and disease situations, and environmental parameters [...]

Inoculation of Erythrina brucei with plant-beneficial microbial consortia enhanced its growth and improved soil nitrogen and phosphorous status when applied as green manure

Erythrina brucei has been applied as a green manure to improve soil fertility in southern Ethiopia. It has been nodulated by indigenous rhizobia. The objectives of this study were to evaluate the effects of E. brucei inoculation with microbial consortia consisted of Bradyrhizobium shewense, Acinetobacter soli and arbuscular mycorrhizal fungi (AMF)on E.brucei growth, soil nitrogen and phosphorous status after application as a green manure.A field experiment was conducted by inoculating E. Brucei with different microbial consortia. E. brucei inoculated with the microbial consortia were grown for 150 days. Its shoot length was measured at 60, 90, 120 and 150 days after planting. Then, plants were uprooted and mulched as a green manure. The soil nitrogen, available phosphorous and soil organic matter analysis were done. The experimental design was completely randomized block design with eight treatments comprised of three replications. Inoculated treatments did not show a significant (p < 0.05) difference in shoot length in the first 60 days. However, shoot length was increased between 19.1 and 41.3 %, 10.5–43.4 % and 8.7–37.6 %, respectively at 90, 120 and 150 days. The soil organic matter was improved in both inoculated and un-inoculated treatments. The improvements in the soil organic matter of un-inoculated treatments may be due to the decomposition of un-inoculated plants biomass in the soil. The B. shewense inoculation improved the soil nitrogen by 17 %. The soil phosphorous was improved in 57 % of inoculated treatments. The inoculation of E. brucei with microbial consortia enhanced its growth and improved soil fertility when applied as a green manure. Inoculating the green manure legumes with symbiotically effective rhizobia and plant-beneficial microbes can enhance the growth of E. brucei and its nutrient uptake.

ABA-mediated stomatal response modulates the effects of drought, salinity and combined stress on tomato plants grown under elevated CO2

Plants are often exposed to drought and salinity stress concurrently but our knowledge about the effects of combined stress is limited, especially in a CO2-enriched environment. This study investigated how these three variables interacted and affected two tomato genotypes with contrasting endogenous abscisic acid (ABA) levels (wild-type AC, ABA-deficient mutant flacca). Plants were grown at ambient (400 μmol mol−1) (a[CO2]) or elevated (800 μmol mol−1) CO2 (e[CO2]), and exposed to progressive soil drying, salt and combined stress; and plant growth and physiological responses to the treatments were tested. The results showed that, under either CO2 growth environment, for both genotypes the individual and combined stress significantly decreased plant growth and water status, with the combined stress having the most pronounced effect on water status. Compared with plants grown at a[CO2], e[CO2] significantly enhanced plant aboveground biomass and attenuated the decrease of water status induced by drought and salt, but this only occurred in AC. In addition, salt stress increased the sensitivity of stomatal response to drought in both genotypes, yet it exacerbated the e[CO2]-induced depression of stomatal conductance (gs) only in the AC plants. On the other hand, drought increased Na+:K+ ratio in leaves for both genotypes while decreasing it in roots of AC plants under salt stress. In addition, e[CO2] favored ionic homeostasis in leaves of plants under salt and combined stresses by limiting leaf Na+ accumulation and enhancing K+ selective transport, but this was only evident for AC, suggesting that e[CO2]-induced plant responses were dependent on plant endogenous ABA levels. The results of this study improve our understanding on the interactive effects of drought and salt stress on tomato plants under e[CO2], which are helpful for improving crop resilience to a future drier, saltier and CO2-enriched environment.

Pirarucu requires taurine to maximize growth and antioxidant status when fed diets high in plant-based ingredients

Taurine (Tau) is a free conditionally essential amino acid for most fish species that plays a significant nutritional role, mainly in carnivorous fish species. However, limited studies are still available regarding the role of Tau on pirarucu nutrition, an important Amazonian fish species. Therefore, this study used diets high in plant-based ingredients to investigate the effect of taurine (Tau) supplementation on juvenile pirarucu's growth, metabolism, and health (n = 115, Weight = 504.12 ± 19 g). Fish were fed five diets containing increasing levels of Tau: 0.95, 5.1, 9.6, 12.9, and 17.2 g/kg in a completely randomized design with three replicates per treatment. After a 60-day feeding trial, growth, hematology, blood chemistry, Tau content in muscle, carcass, and liver, antioxidant status, and immunological parameters were evaluated. The control group (0.95 g/kg Tau) showed the lowest growth. According to the segmented regression model, the recommended Tau level for maximizing the development of juvenile pirarucu was 4.49 g/kg of feed. Additionally, fish fed the lowest dietary Tau level showed the highest ROS (reactive oxygen species) concentration. Dietary Tau levels did not affect hematological parameters and blood chemistry (p > 0.05). Fish fed 9.6 g/kg of Tau showed increased catalase activity, while the control group had the worst result in NBT (nitroblue tetrazolium reduction test). Fish fed with the highest dietary Tau levels (12.9 and 17.2 g/kg) showed increased total serum immunoglobulin concentration. These results suggest that the optimal inclusion level of Tau in diets for juvenile pirarucu is 4.49 g/kg of feed and that this amino acid acts as a mitigator of oxidative stress.

Estimating Corn Growth Parameters by Integrating Optical and Synthetic Aperture Radar Features into the Water Cloud Model

Crop growth parameters are the basis for evaluation of crop growth status and crop yield. The aim of this study was to develop a more accurate estimation model for corn growth parameters combined with multispectral vegetation indexes (VIopt) and the differential radar information (DRI) derived from SAR data. Targeting the estimation of corn plant height (H) and the BBCH (Biologische Bundesanstalt, Bundessortenamt and CHemical industry) phenological parameters, this study compared the estimation accuracies of various multispectral vegetation indexes (VIopt) and the corresponding VIDRI (vegetation index corrected by DRI) indexes in inverting the corn growth parameters. (1) When comparing the estimation accuracies of four multispectral vegetation indexes (NDVI, NDVIre1, NDVIre2, and S2REP), NDVI showed the lowest estimation accuracy, with a normalized root mean square error (nRMSE) of 20.84% for the plant height, while S2REP showed the highest estimation accuracy (nRMSE = 16.05%). In addition, NDVIre2 (nRMSE = 16.18%) and S2REP (16.05%) exhibited a higher accuracy than NDVIre1 (nRMSE = 19.27%). Similarly, for BBCH, the nRMSEs of the four indexes were 24.17%, 22.49%, 17.04% and 16.60%, respectively. This confirmed that the multispectral vegetation indexes based on the red-edge bands were more sensitive to the growth parameters, especially for the Sentinel-2 red-edge 2 band. (2) The constructed VIDRI indexes were more beneficial than the VIopt indexes in enhancing the estimation accuracy of corn growth parameters. Specifically, the nRMSEs of the four VIDRI indexes (NDVIDRI, NDVIre1DRI, NDVIre2DRI, and S2REPDRI) decreased to 19.64%, 18.11%, 15.00%, and 14.64% for plant height, and to 23.24%, 21.58%, 15.79%, and 15.91% for BBCH, indicating that even in cases of high vegetation coverage, the introduction of SAR DRI features can further improve the estimation accuracy of growth parameters. Our findings also demonstrated that the NDVIre2DRI and S2REPDRI indexes constructed using red-edge 2 band information of Sentinel-2 and SAR DRI features had more advantages in improving the estimation accuracy of corn growth parameters.