Search
Submit Manuscript
Advanced Search
MAP  >  Technology in Horticulture
2024 Volume 4
Article Contents
Abstract
Introduction
Materials and methods
Plant materials, growth conditions, and stress treatment
Vector construction
Chlorophyll and anthocyanin content determination
Physiological analysis
RNA isolation and qRT-PCR analysis
Results
Screening and characterization of lncRNAs
Generation of lncRNA overexpression lines
Effect of lncRNA overexpression on heat tolerance in Arabidopsis
Effect of lncRNA overexpression on the expression quantity of genes related to high-temperature response in Arabidopsis
Effect of lncRNA overexpression on drought tolerance in Arabidopsis
Discussion
Conclusions
Author contributions
Data availability
Acknowledgments
Conflict of interest
Rights and permissions
References
About this article
Next Previous
ARTICLE   Open Access    

Optimization of a new organic approach to natural biostimulant (Jeevamrutha) for yield and quality management in Senna (Cassia angustifolia Vahl.): an agriculturally highly export-oriented crop

  • 1.

    Crop Production & Protection Divisional Unit, CSIR-Central Institute of Medicinal and Aromatic Plants, Research Centre, Boduppal, Hyderabad, Telangana State, 500092, India

  • 2.

    CSIR-Central Institute of Medicinal and Aromatic Plants, Lucknow, U.P. State, 226015, India

More Information
  • Senna is a leguminous and industrial crop that produces high-quality glycosides (sennosides) in its leaves and pods, which have substantial therapeutic effects for alleviating constipation worldwide. However, further research on employing Jeevamrutha in Senna is required. As a result, the experiment was carried out at CSIR-CIMAP in Hyderabad for two consecutive years, in the years 2020–2021 and 2021–2022. The main aim is to identify the optimum dose of Jeevamrutha for higher growth, yield, and quality in Senna. The study used a randomized complete block design (RCBD) with seven treatments repeated three times. From the obtained result, it was observed that the application of 150 L of Jeevamrutha per acre observed significantly high leaf yields (1,085.2 kg·ha−1) and pod (318.7 kg·ha−1) equivalent to T2 in comparison to other treatments, i.e., application of 125 L of Jeevamrutha per acre (1,022.5 kg·ha−1, 312.1 kg·ha−1), and was succeeded by T3, i.e., application of 100 L of Jeevamrutha per acre (998.5 kg·ha−1, 288.5 kg·ha−1, respectively). Lower leaf yield (700.2 kg·ha−1) and pod yield (487 kg·ha−1) were observed in the control (T7). Similarly, the application of 150 L of Jeevamrutha per acre recorded significantly higher sennoside content in leaves (2.01%) and pods (3.11%), in comparison to other treatments, and was followed by T2 (1.98%, 3.09%) and T3 (1.89%, 2.97%). A similar trend was noticed in returns, i.e., the application of 150 L of Jeevamrutha per acre recorded significantly higher gross returns (USD$1,495 ha−1) and net returns (USD$1,066.4 ha−1).

  • Introduction

    Plants are continuously subjected to unpredictable environmental conditions and encounter a multitude of stressors throughout their growth and development, posing a significant challenge to global crop production and food security[1]. Heat and drought are undoubtedly the two most important stresses that have a huge impact on crops. Both elicit a wide array of biochemical, molecular, and physiological alterations and responses, impacting diverse cellular processes and ultimately influencing crop yield and quality[2].

    A primary physiological consequence of both stresses is the diminished photosynthetic capacity, partially resulting from the degradation of chlorophyll due to leaf senescence under stress conditions. Chlorophyll accumulation was diminished in numerous plants subjected to drought or heat stress conditions[3,4]. Various environmental stresses prompt excessive generation of reactive oxygen species (ROS), initiating oxidative damage that compromises lipids, and proteins, and poses a serious threat to cellular functions[2]. To mitigate oxidative stress and minimize damage, plants have developed various protective mechanisms to neutralize ROS. Several antioxidant enzymes, such as SOD, POD, and CAT, are integral to cellular antioxidative defense mechanisms. Additionally, antioxidants such as anthocyanins and proline serve as crucial ROS scavengers[5,6]. The elevation in temperature typically induces the transient synthesis of heat shock proteins (Hsps), which function as molecular chaperones in protecting proteins from denaturation and aggregation, with their activity primarily regulated at the transcriptional level by heat shock factors (Hsfs)[7]. The significance of Hsps and Hsfs in all organisms, including plants, has been assessed in various stress conditions that could disrupt cellular homeostasis and result in protein dysfunction[7]. Drought stress can also trigger the transcription of a suite of marker genes, including RD29A, RD29B, NCED3, AREB1, Rab18, etc., which assist plants in mitigating cellular damage during dehydration and bolstering their resilience to stress[8−10].

    Previous research efforts focusing on the regulatory control of stress-related genes have largely centered around protein-coding genes. In recent years, non-protein-coding transcripts have emerged as important regulatory factors in gene expression. Among them, long non-coding RNAs (lncRNAs) lncRNAs have been identified as implicated in various abiotic stresses[11,12]. LncRNAs are a class of non-coding RNAs (ncRNAs) exceeding 200 nucleotides in length. They possess minimal or no protein-coding potential[13]. In plants, lncRNAs are specifically transcribed by RNA polymerases Pol IV, Pol V, Pol II, and Pol III[14,15]. LncRNAs exhibit low abundance and display strong tissue and cellular expression specificity relative to mRNAs. Moreover, sequence conservation of lncRNAs is was very poor across different plant species[13,16,17]. The widespread adoption of high-throughput RNA sequencing technology has revealed lncRNAs as potential regulators of plant development and environmental responses. In cucumber, RNA-seq analysis has predicted 2,085 lncRNAs to be heat-responsive, with some potentially acting as competitive endogenous RNAs (ceRNAs) to execute their functions[18]. In radish, a strand-specific RNA-seq (ssRNA-seq) technique identified 169 lncRNAs that were differentially expressed following heat treatment[19]. In Arabidopsis, asHSFB2a, the natural antisense transcript of HSFB2a was massively induced upon heat stress and exhibited a counteracted expression trend relative to HSFB2a. Overexpression of asHSFB2a entirely suppressed the expression of HSFB2a and impacted the plant's response to heat stress[20]. For drought stress resistance, 244 lncRNAs were predicted in tomatoes to be drought responsive probably by interacting with miRNAs and mRNAs[21]. Under drought stress and rehydration, 477 and 706 lncRNAs were differentially expressed in drought-tolerant Brassica napus Q2 compared to drought-sensitive B. napus, respectively[22]. In foxtail millet and maize, 19 and 644 lncRNAs, respectively, were identified as drought-responsive[23,24]. Despite the identification of numerous lncRNAs by high-throughput sequencing, which suggests their potential involvement in various abiotic stress processes, only a minority have been experimentally validated for function.

    In our previous study, we characterized 1,229 differentially expressed (DE) lncRNAs in Chinese cabbage as heat-responsive, and subsequent bioinformatics analysis reduced this number to 81, which are more likely associated with heat resistance[25]. lnc000283 and lnc012465 were selected from among them for further functional investigation. The findings indicated that both lnc000283 and lnc012465 could be promptly induced by heat shock (HS). Overexpression of either lnc000283 or lnc012465 in Arabidopsis plants enhanced their capacity to tolerate heat stress. Additionally, both lnc000283 and lnc012465 conferred drought tolerance to transgenic Arabidopsis.

    Materials and methods

    Plant materials, growth conditions, and stress treatment

    The lncRNA sequences examined in this study were from Chiifu-401-42 Chinese cabbage and all Arabidopsis plants were of the Col-0 background. Transgenic plants expressing lnc000283 and lnc012465 were generated using the Agrobacterium tumefaciens-mediated floral dip method[26]. Single-copy and homozygous T3 plants were identified through genetic segregation on an agar medium supplemented with kanamycin. The T3 generation plants, or their homozygous progeny, were utilized in the experiments.

    For phenotypic assessment, Arabidopsis seeds were initially sown on filter paper moistened with ddH2O and placed in a 4 °C freezer for 2 d. Subsequently, they were evenly planted in nutrient-rich soil and transferred to a growth chamber operating a 16-h day/8-h night cycle, with day/night temperatures of 22 °C/18 °C and a light intensity of 250 μmol·m−2·s−1. After 10 d of growth, Arabidopsis plants with uniform growth were transferred to 50-hole plates. Arabidopsis plants grown in Petri dishes were firstly seed-sterilized and then sown on 1/2 MS medium supplemented with 10 g·L−1 sucrose. The seeds were then placed in a 4 °C refrigerator for 2 d in the dark before transferring them to a light incubator. The day/night duration was set to 16 h/8 h, the day/night temperature to 21 °C/18 °C, and the light intensity to 100 μmol·m−2·s−1.

    For heat treatment, 3-week-old seedlings were subjected to 38 °C for 4 d within a light incubator, subsequently transferred to their original growth conditions under the same light/dark cycles. For drought treatment, 3-week-old Arabidopsis seedlings were deprived of water for 10 d, followed by rehydration to facilitate a 2-d recovery period. Plants were photographed and surveyed both before and after treatment.

    Vector construction

    The lncRNA sequences (lnc000283 and lnc012465) were chemically synthesized based on RNA-seq data, with restriction sites for BamH1 and Kpn1 engineered upstream and downstream. The resultant lncRNA constructs were subcloned into the pCambia2301 binary vector, incorporating a cauliflower mosaic virus (CaMV) 35S promoter. The recombinant vectors were transformed into Escherichia coli TOP10 competent cells (Clontech), incubated at 37 °C overnight, after which single clones were selected for PCR verification, and the confirmed positive colonies were submitted for sequencing. Following verification, the correct plasmids were introduced into A. tumefaciens strain GV3101 using the freeze-thaw method and subsequently transformed into Arabidopsis wild-type (Col) plants.

    Chlorophyll and anthocyanin content determination

    To quantify the chlorophyll content, the aerial portions of wild-type and transgenic Arabidopsis plants, grown in Petri dishes were weighed, minced, and then subjected to boiling in 95% ethanol until fully decolorized. Aliquots of 200 μL from the extract were transferred to a 96-well plate and the absorbance at 663 nm and 645 nm was measured via spectrophotometry by a microplate reader (Multiskan GO, Thermo Scientific, Waltham, MA, USA). Three biological replicates were analyzed for WT and each transgenic line. Chlorophyll content was determined according to the formula of the Arnon method[27]: Chlorophyll a = (12.72A663 − 2.59A645) v/w, Chlorophyll b = (22.88A645 − 4.67A663) v/w, Total chlorophyll = (20.29A645 + 8.05A663) v/w.

    The quantification of anthocyanin was performed as follows: aerial parts of wild-type and transgenic Arabidopsis plants, cultivated in Petri dishes, were weighed and ground to powder in liquid nitrogen. Subsequently, the samples were incubated in 600 μL of acidified methanol (containing 1% HCl) at 70 °C for 1 h. Following this, 1 mL of chloroform was added, and the mixture was vigorously shaken to remove chlorophyll. The mixture was then centrifuged at 12,000 rpm for 5 min, after which the absorbance of the aqueous phase was determined at 535 nm using a spectrophotometer (Shimadzu, Kyoto, Japan). Three biological replicates were analyzed for WT and each transgenic line. The relative anthocyanin content was calculated according to anthocyanin concentration and extraction solution volume. One anthocyanin unit is defined as an absorption unit at a wavelength of 535 nm in 1 mL of extract solution. In the end, the quantity was normalized to the fresh weight of each sample.

    Physiological analysis

    Three-week-old transgenic and WT A. thaliana plants, subjected to normal conditions or varying durations of heat or drought stress, were utilized for subsequent physiological assessments. All assays were performed in accordance with the method described by Chen & Zhang[28]. In brief, 0.1 g of fresh leaf tissue was homogenized in 500 μL of 100 mM PBS (pH 7.8) while chilled on ice. The homogenate was then centrifuged at 4 °C, and the resultant supernatant was employed for further analysis. For the determination of MDA content, 100 μL of the supernatant was combined with 500 μL of a 0.25% thiobarbituric acid (TBA) solution (which was prepared by dissolving 0.125 g of TBA in 5 mL of 1 mol·L−1 NaOH before being added to 45 mL of 10% TCA) and boiled for 15 min. Following a 5 min cooling period on ice, the absorbance was measured at 532 nm and 600 nm. The activity of POD was determined as follows: initially, 28 μL of 0.2% guaiacol and 19 μL of 30% H2O2 were sequentially added to 50 mL of 10mM PBS (pH 7.0), after thorough heating and mixing, 1 mL was transferred into a cuvette, then 50 μL of the supernatant was added to the cuvette and the absorbance at 470 nm was monitored every 15 s for 1 min. To determine the proline content, a reaction solution was prepared by mixing 3% sulfosalicylic acid, acetic acid, and 2.5% acidic ninhydrin in a ratio of 1:1:2, then 50 μL of the supernatant was added to 1 mL of the reaction solution, which was then subjected to a boiling water bath for 15 min (the solution turned red after the boiling water bath). Following cooling on ice, the absorbance at 520 nm was recorded. For the quantification of proline, an L-proline standard curve was prepared by dissolving 0, 5, 10, 15, 20, 25, and 30 μg of L-proline in 0.5 mL of ddH2O, followed by the addition of 1 mL of the reaction solution and measuring the absorbance at 520 nm. The proline content in the samples was then determined based on the L-proline standard curve.

    RNA isolation and qRT-PCR analysis

    Total RNA was isolated from the aerial parts of Arabidopsis using the TaKaRa MiniBEST Plant RNA Extraction Kit, followed by purification and reverse transcription using the PrimeScript RT reagent Kit with gDNA Eraser (Takara). The cDNA product was diluted 10 times and real-time PCR was conducted in triplicate for each biological replicate using SYBR PCR Master Mix (Applied Biosystems) on the ABI 7500 system under the following conditions: 98 °C for 3 min, followed by 40 cycles of 98 °C for 2 s and 60 °C for 30 s. The relative expression levels of each gene were normalized against the transcript abundance of the endogenous control UBC30 (At5g56150) and calculated using the 2−ΔCᴛ method. The specific primers employed for qRT-PCR are detailed in Supplemental Table S1.

    Results

    Screening and characterization of lncRNAs

    In our prior investigation, dozens of lncRNAs associated with the heat stress response in Chinese cabbage were identified through informatics analysis. Two lncRNAs (lnc000283 and lnc012465) were chosen for genetic transformation in Arabidopsis to elucidate their functions comprehensively. Transcriptome data analysis indicated that the expression of lnc000283 and lnc012465 in Chinese cabbage were both induced by HS. To verify the accuracy, the expression patterns of lnc000283 and lnc012465 were confirmed through quantitative real-time PCR (qRT-PCR), and the results from qRT-PCR were consistent with those obtained from RNA-seq (Fig. 1a). The corresponding homologous genes in Arabidopsis were identified as CNT2088434 and CNT2088742, exhibiting sequence similarities of 88% and 87%, respectively (Supplemental Fig. S1). Subcellular localization predictions using the lnclocator database (www.csbio.sjtu.edu.cn/bioinf/lncLocator) suggested that both lncRNAs are localized within the nucleus (Supplemental Table S2). Bioinformatics analysis was conducted using the CPC tool (http://cpc.cbi.pku.edu.cn/) indicated that lnc000283 and lnc012465 are noncoding sequences, with coding probabilities of 0.0466805 and 0.0432148, respectively comparable to the well-characterized lncRNAs COLDAIR and Xist, but significantly lower than those of the protein-coding genes UBC10 and ACT2 (Fig. 1b).

    Figure 1.  Characteristics of lnc000283 and lnc012465. (a) Expression level of lnc000283 and lnc012465 in Chinese cabbage leaves treated at 38 °C at different time points, as determined by qRT-PCR and RNA-seq. CK is a representative plant before heating, and T1, T4, T8, and T12 denote plants that were subjected to 38 °C for 1, 4, 8, and 12 h, respectively. The expression levels were normalized to the expression level of Actin. (b) Analysis of coding potential for lnc000283 and lnc012465. The coding potential scores were calculated using the CPC program. UBC10 (At5g53300) and ACT2 (At3g18780) are positive controls that encode proteins. COLDAIR (HG975388) and Xist (L04961) serve as negative controls, exhibiting minimal protein-coding potential.
    DownLoad: Full-Size Img PowerPoint

    Generation of lncRNA overexpression lines

    To elucidate the role of lnc000283 and lnc012465 in response to abiotic stress, overexpression vectors were constructed for these lncRNAs, driven by the CaMV 35S promoter, and they were introduced into Arabidopsis thaliana (Col-0 ecotype). Through PCR identification and generational antibiotic screening, two homozygous positive lines for lnc012465 and lnc000283 were obtained. The relative expression levels of these lncRNAs were assessed using qRT-PCR (Fig. 2a). When plants were grown in 1/2 MS medium, with the consumption of nutrients, and reduction of water, the leaves of WT began to turn yellow, but the lnc000283 and lnc012465 overexpression lines developed a deep purple color of leaf veins (Fig. 2b). Examination of chlorophyll and anthocyanin contents in the plants revealed that both overexpression lines had higher levels of chlorophyll and anthocyanin compared to the WT, suggesting that the transgenic plants might possess enhanced resistance to nutritional or water stress (Fig. 2c, d).

    Figure 2.  Arabidopsis plants overexpressing lnc000283 and lnc012465 had higher anthocyanins and chlorophyll content. (a) The relative expression level of lnc000283 and lnc012465 in WT and different transgenic lines. UBC10 (At5g53300) was used as an internal control. Each value is mean ± sd (n = 3). (b) The phenotype of WT and Arabidopsis overexpressing lnc000283 or lnc012465 grown on 1/2 MS medium 50 d after sowing. The (c) anthocyanin and (d) chlorophyll content of WT and transgenic Arabidopsis overexpressing lnc000283 or lnc012465. The asterisks above the bars indicate statistical significance using Student's t-test (*, p < 0.05; **, p < 0.01).
    DownLoad: Full-Size Img PowerPoint

    Effect of lncRNA overexpression on heat tolerance in Arabidopsis

    Given that lnc000283 and lnc012465 were highly induced by heat, the thermotolerance of the overexpressing (OE) plants were compared to that of the wild type. Arabidopsis plants were initially exposed to a an HS treatment at 38 °C for 4 d, followed by recovery at room temperature. The death caused by HS was processive. Post-severe HS challenge for 4 d, OE plants initially appeared similar to WT, but upon recovery, their leaves started to fold or curl, followed by a transition to yellow, white, and eventually drying out (Fig. 3a). OE lnc000283 and OE lnc012465 plants exhibited enhanced thermotolerance compared to WT, with lnc012465 showing particularly strong tolerance (Fig. 3a; Supplemental Fig. S2a). After 5 d of recovery, leaf coloration indicated that transgenic plants maintained a significantly higher percentage of green leaves and a lower percentage of bleached leaves compared to WT (Fig. 3b; Supplemental Fig. S2b). Under non-heat-stress conditions, WT and OE plants possessed comparable water content. However, following heat stress, the fresh-to-dry weight ratio of OE lnc000283 and lnc012465 lines was significantly greater than that of WT (Fig. 3c; Supplemental Fig. S2c). Abiotic stresses frequently trigger the production of excessive reactive oxygen species (ROS), which are believed to cause lipid peroxidation of membrane lipids, leading to damage to macromolecules. Leaf MDA content is commonly used as an indicator of lipid peroxidation under stress conditions; therefore, the MDA content in both transgenic and WT plants was assessed. Figure 3d shows that the MDA content in WT plants progressively increased after heat treatment, whereas in the two lines overexpressing lnc012465, the MDA content increased only slightly and remained significantly lower than that in WT at all time points. In plants overexpressing lnc000283, the MDA content did not significantly differ from that of WT before heat stress. However, after 4 d of heat treatment, the MDA content was significantly lower compared to WT (Supplemental Fig. S2d). The results suggested that the expression of both lnc012465 and lnc000283 can mitigate injury caused by membrane lipid peroxidation under heat-stress conditions. Peroxidase (POD) is a crucial antioxidant enzyme involved in ROS scavenging. Figure 3e and Supplemental Fig. S2e demonstrate that POD activity increased in both transgenic and WT plants after heat treatment. However, the increase in WT plants was modest, whereas OE lnc000283 and OE lnc012465 plants exhibited consistently higher POD activity. As anticipated, proline levels were induced in response to stress in all studied plants (Fig. 3f; Supplemental Fig. S2f). However, under normal conditions and 2 d post-heat stress treatment, the proline content in OE lnc000283 and OE lnc012465 plants did not exhibit significant changes compared to WT (Fig. 3f; Supplemental Fig. S2f). Moreover, after 4 d of heat stress, the proline content in OE lnc012465 lines was significantly lower than in WT, and the OE lnc000283 transgenic line 12-6 also showed a marked decrease in proline content compared to WT (Fig. 3f; Supplemental Fig. S2f). The results indicated that the thermotolerance of plants overexpressing either lnc000283 or lnc012465 was independent of proline accumulation.

    Figure 3.  Overexpressing lnc012465 lines are more tolerant to heat stress. (a) Phenotypes of WT and OE lnc012465 plants were assessed before and after exposure to heat stress. The heat treatment was applied to 25-day-old Arabidopsis plants. (b) The percentage of leaves with different colors in Arabidopsis after heat treatment and recovery for 5 d. (c) The fresh-to-dry weight ratio of Arabidopsis leaves was measured before and after 38 °C heat treatment. (d)−(f) depict the MDA content, POD activity, and proline content in Arabidopsis leaves at varying durations of heat stress. The asterisks above the bars indicate statistical significance using Student's t-test (*, p < 0.05; **, p < 0.01; ***, p < 0.001).
    DownLoad: Full-Size Img PowerPoint

    Effect of lncRNA overexpression on the expression quantity of genes related to high-temperature response in Arabidopsis

    To elucidate the molecular mechanisms by which lncRNAs enhance thermotolerance in Arabidopsis, the expression of the Hsf gene HsfA7a and three Hsps (Hsp25.3, Hsa32, and Hsp18.1-CI) in OE lnc000283, OE lnc012465, and WT Arabidopsis plants were investigated at various time points following heat treatment. As shown in Fig. 4 and Supplemental Fig. S3, both Hsf and Hsps exhibited a rapid response to heat stress with strong induction. Notably, the transcripts of HsfA7a and Hsp25.3 were significantly upregulated at 1 h after heat exposure, then experienced a sharp decrease. Hsa32 and Hsp18.1-CI were highly induced at 1 h and, unlike the other proteins, sustained high expression levels at 3 h (Fig. 4; Supplemental Fig. S3). At 1 h post-heat treatment, the transcript levels of Hsa32 and HsfA7a in OE lnc000283 did not significantly differ from those in WT. However, by 3 h, Hsa32 expression was roughly 50% of the WT level, while HsfA7a expression was approximately double that of WT (Supplemental Fig. S3). The overexpression of lnc000283 did not significantly affect the transcript level of Hsp25.3 at any of the tested time points. Notably, Hsp18.1-CI expression in both lines overexpressing lnc000283 was significantly induced at all three detection points post-heat treatment, reaching approximately 4-9-fold higher levels than in the WT (Supplemental Fig. S3). In Arabidopsis plants with elevated expression of lnc012465, the expression patterns of all Hsp and Hsf genes were similar to those in plants overexpressing lnc000283, with the notable exception of Hsa32. Unlike the WT, Hsa32 did not show a trend of down-regulation at 3 h post-heat treatment (Fig. 4). The findings suggest that the substantial induction of Hsp18.1-CI may play a role in enhancing the thermotolerance of Arabidopsis plants overexpressing lnc000283 and lnc012465.

    Figure 4.  The expression of HSF and HSP genes in lnc012465 overexpressing lines before and after different heat treatment times. Gene expression levels were quantified using RT-qPCR and normalized to UBC10 (At5g53300). Each value represents the mean ± standard deviation (n = 3). The asterisks above the bars indicate statistical significance using Student's t-test (*, p < 0.05; **, p < 0.01; ***, p < 0.001).
    DownLoad: Full-Size Img PowerPoint

    Effect of lncRNA overexpression on drought tolerance in Arabidopsis

    Prior research has implicated a significant proportion of genes in conferring resistance to various abiotic stresses. To elucidate the functions of lnc000283 and lnc012465 more thoroughly, WT and transgenic plants were subjected to drought stress by depriving them of water for 9 d. It was noted that the majority of leaves in WT plants withered and dried, whereas the OE lnc000283 and OE lnc012465 plants exhibited reduced withering, with only a minority displaying dryness (Fig. 5a; Supplemental Fig. S4a). Eight days post-rewatering, a negligible fraction of WT seedlings exhibited recovery, whereas the overwhelming majority of transgenic plants regained vigorous growth (Fig. 5a; Supplemental Fig. S4a). The transgenic plants demonstrated a significantly higher survival rate compared to the WT plants. Following 9 d of water deficit treatment, less than 40% of the WT plants survived, whereas the OE 012465 lines 8-7 and 9-1 exhibited survival rates of 100% and 95%, respectively, and the OE 000283 lines 11-10 and 12-6 had survival rates of 87% each. (Fig. 5b; Supplemental Fig. S4b). Water loss serves as a critical metric for assessing plant drought tolerance, hence the fresh-to-dry weight ratio of excised leaves was assessed via desiccation analysis. Following 4 d of drought treatment, the fresh-to-dry weight ratio for WT plants was reduced to 43%, whereas for OE lnc000283 lines 11-10 and 12-6, it was reduced to 73% and 75%, respectively. For OE 012465 lines 8-7 and 9-1, the ratios were reduced to 67% and 62%, respectively (Fig. 5c; Supplemental Fig. S4c). The findings indicated that lnc000283 and lnc012465 endow the transgenic plants with drought tolerance.

    Figure 5.  Overexpressing lnc012465 lines are more tolerant to drought stress. (a) Phenotype of WT and OE lnc012465 plants before and after subjecting to drought stress. Drought treatment was carried out on 20-day-old Arabidopsis plants. (b) The percentage of leaves with different colors in Arabidopsis after heat treatment and recovery for 5 d. (c) The fresh weight to dry weight ratio of Arabidopsis leaves before and after undergoing 38 °C heat treatment. (d)−(f) MDA content, POD activity, and proline content in Arabidopsis leaves under different times of heat stress. The asterisks above the bars indicate statistical significance using Student's t-test (*, p < 0.05; **, p < 0.01; ***, p < 0.001)
    DownLoad: Full-Size Img PowerPoint

    MDA content in leaves is a standard biomarker for assessing the extent of drought stress-induced damage. Prior to drought stress exposure, MDA levels in WT and transgenic plants were comparable. However, following 7 and 9 d of water deficit, the MDA content in the transgenic plants was markedly reduced compared to the WT, suggesting a less severe degree of membrane lipid peroxidation in the transgenic plants (Fig. 5d; Supplemental Fig. S4d). Oxidative stress frequently coincides with drought stress, hence the activity of POD was assessed to evaluate the ROS scavenging ability. The findings indicated that as the duration of drought treatment increased, POD activity progressively rose. Before drought exposure, the POD activity in lines 11-10 and 12-6 of OE 000283 was 2.4-fold and 2.2-fold higher than that of the WT, respectively (refer to Supplemental Fig. S4e). Following drought treatment, the POD activity in the transgenic lines remained significantly elevated compared to the wild type, although the enhancement was less pronounced than before the treatment (Supplemental Fig. S4e). In the OE 012465 plants, the POD activity in lines 8-7 and 9-1 significantly surpassed that of the wild type, with the discrepancy being more pronounced during drought stress (Fig. 5e). The proline content in WT and OE 000283 plants exhibited no significant differences before and after 7 d of treatment. However, after 9 d of drought, the proline content in OE 000283 plants was significantly lower compared to that in the WT (Supplemental Fig. S4f). OE 000465 plants showed no significant difference from the wild type before and after drought treatment (Fig. 5f). The findings were consistent with those under heat stress, indicating that the enhanced stress resistance due to the overexpression of lnc000283 and lnc012465 in Arabidopsis is not reliant on proline accumulation.

    Following drought stress treatment, the expression levels of drought-related genes such as RD29A, RD29B, NCED3, AREB1, and Rab18 were significantly elevated in plants overexpressing lnc000283 and lnc012465 compared to WT plants. These findings suggest that lnc000283 and lnc012465 modulate Arabidopsis drought tolerance by regulating the expression of genes associated with the drought stress response (Fig. 6; Supplemental Fig. S5).

    Figure 6.  The expression of drought-responsive genes in lnc012465 overexpressing lines before and after different drought treatment time. Gene expression levels were determined by qRT-PCR normalized against UBC10 (At5g53300). Each value is mean ± sd (n = 3). The asterisks above the bars indicate statistical significance using Student's t-test (*, p < 0.05; **, p < 0.01; ***, p < 0.001).
    DownLoad: Full-Size Img PowerPoint

    Discussion

    The integrity of global food security is under threat due to the confluence of rapid population expansion and profound climatic shifts[29]. Amidst the shifting climatic landscape, heat and drought stress have emerged as primary limitations to crop yield and global food security. Understanding how plants detect stress cues and acclimate to challenging conditions is a pivotal biological inquiry. Moreover, enhancing plant resilience to stress is essential for maintaining agricultural productivity and fostering environmental sustainability[2]. Concurrently, the advancement of next-generation sequencing (NGS) technology has led to the identification of a substantial number of lncRNAs that participate in diverse stress responses, with functional analyses having been conducted on several of these molecules.[30] For instance, in the case of potatoes, the lncRNA StFLORE has been identified to modulate water loss through its interaction with the homologous gene StCDF1[31]. LncRNA TCONS_00021861 can activate the IAA biosynthetic pathway, thereby endowing rice with resistance to drought stress[32]. In wheat, the expression of TalnRNA27 and TalnRNA5 was upregulated in response to heat stress[33]. Our prior investigation identified a total of 81 lncRNAs in Chinese cabbage that engage in intricate interactions with their respective mRNA targets across various phases of heat treatment[25]. Two lncRNAs, lnc000283 and lnc012465, were chosen for subsequent functional analysis. Findings confirmed that these lncRNAs endow transgenic Arabidopsis plants with enhanced tolerance to both heat and drought, thereby offering novel resources for enhancing stress resistance through genetic engineering.

    Abiotic stresses frequently trigger the synthesis of anthocyanins, serving as natural antioxidants that mitigate oxidative damage by neutralizing surplus reactive oxygen species (ROS), thereby protecting plants from growth inhibition and cell death, allowing plants to adapt to abiotic stresses[34,35]. For instance, during chilling stress, the accumulation of anthocyanins within leaves can mitigate oxidative damage, thereby enhancing the photosynthetic rate[36]. Consequently, the level of abiotic stress tolerance can be inferred from the concentration of anthocyanins. The reduction of photosynthetic ability is one of the key physiological phenomena of stresses, which is partly due to the degradation of chlorophyll caused by leaf senescence during stress. The reduced accumulation of chlorophyll in the plants was seen in many plants when exposed to drought or heat stress conditions. The current investigation revealed that lncRNA-overexpressing plants cultivated in Petri dishes exhibited increased accumulation of both chlorophyll and anthocyanins in advanced growth phases, indicating that these transgenic plants, overexpressing lnc000283 and lnc012465, demonstrated enhanced stress tolerance and superior growth performance relative to WT (Fig. 2c, d).

    Upon exposure to heat stress, there is a marked induction of transcription for numerous genes that encode molecular chaperones in plants, with the vast majority of these genes contributing to the prevention of protein denaturation-related damage and the augmentation of thermotolerance[37−39]. The present investigation identified multiple heat-inducible genes in plants overexpressing lnc000283 and lnc012465, as well as in WT (Fig. 4; Supplemental Fig. S3). The findings indicated that of the four HSP or HSF genes examined, Hsp18.1-CI exhibited a significantly greater abundance in both OE lnc000283 and OE lnc012465 plants compared to the WT following heat treatment for several days. Hsp18.1-CI, formerly referred to as Hsp18.2 has been the subject of investigation since 1989.[40] Following the fusion of the 5' region of Hsp18.2 in frame with the uidA gene of Escherichia coli, the activity of GUS, serving as the driver gene was observed to increase upon exposure to HS[40]. The Arabidopsis hsfA2 mutant exhibited diminished thermotolerance after heat acclimation, with the transcript levels of Hsp18.1-CI being substantially reduced compared to those in wild-type plants following a 4-h recovery period[41]. The findings revealed that the upregulation of Hsp18.1-CI protein is a critical mechanism by which plants achieve enhanced protection against heat stress in adverse environmental conditions, thereby bolstering their thermotolerance.

    Plants cultivated in natural settings are often subjected to concurrent multiple abiotic stresses, which can exacerbate threats to their routine physiological functions, growth, and developmental processes[42,43]. Elucidating the molecular mechanisms underlying plant responses to abiotic stress is crucial for the development of new crop varieties with enhanced tolerance to multiple abiotic stresses. Previous research has indicated that the overexpression of certain protein-coding genes can endow plants with resistance to a variety of abiotic stresses. For instance, tomatoes with robust expression of ShCML44 demonstrated significantly enhanced tolerance to drought, cold, and salinity stresses[44]. Overexpression of PeCBF4a in poplar plants confers enhanced tolerance to a range of abiotic stresses[45]. With respect to lncRNAs, transgenic Arabidopsis plants that overexpress lncRNA-DRIR displayed marked increased tolerance to salt and drought stresses compared to the wild-type[46]. In the present study, both overexpression lines of lnc000283 and lnc012465 exhibited resistance to heat and drought stresses, thereby contributing to the enhancement of plant resilience against multiple stresses (Figs 3, 5; Supplemental Figs S2, S4).

    The number of genes implicated in plant drought resistance is regulated by both ABA-dependent and ABA-independent pathways[47,48]. It is well established that the expression of RD29A exhibits a high level of responsiveness to drought stress, operating through both ABA-dependent and ABA-independent mechanisms[49]. RD29B, AREB1, and RAB18 are governed by an ABA-dependent regulatory pathway[10,49,50]. NCED3 is involved in ABA biosynthesis[51]. In the present study, the transcript levels of RD29A, RD29B, NCED3, AREB1, and RAB18 were significantly elevated in OE lnc000283 and OE lnc012465 plants compared to those in the WT plants (Fig. 6; Supplemental Fig. S5). The findings indicated that the drought tolerance imparted by OE lnc000283 and OE lnc012465 plants is contingent upon an ABA-dependent mechanism.

    Prior research has indicated that certain long non-coding RNAs (lncRNAs) can assume analogous roles across diverse biological contexts. For example, the lncRNA bra-miR156HG has been shown to modulate leaf morphology and flowering time in both B. campestris and Arabidopsis[52]. Heterogeneous expression of MSL-lncRNAs in Arabidopsis has been associated with the promotion of maleness, and similarly, it is implicated in the sexual lability observed in female poplars[53]. In the present study, lnc000283 and lnc012465 were induced by heat in Chinese cabbage, and their heterologous expression was found to confer heat tolerance in Arabidopsis. Additionally, sequences homologous to lnc000283 and lnc012465 were identified in Arabidopsis (Supplemental Fig. S1). The data suggest that these sequences may share a comparable function to that of heat-inducible sequences, potentially accounting for the conservation of lnc000283 and lnc012465'os functionality across various species.

    Conclusions

    In conclusion, the functions of two heat-inducible lncRNAs, lnc000283 and lnc012465 have been elucidated. Transgenic Arabidopsis lines overexpressing these lncRNAs accumulated higher levels of anthocyanins and chlorophyll at a later stage of growth compared to the WT when grown on Petri dishes. Furthermore, under heat and drought stress conditions, these OE plants exhibited enhanced stress tolerance, with several genes related to the stress resistance pathway being significantly upregulated. Collectively, these findings offer novel insights for the development of new varieties with tolerance to multiple stresses.

    Author contributions

    The authors confirm contribution to the paper as follows: study conception and supervision: Li N, Song X; experiment performing: Wang Y, Sun S; manuscript preparation and revision: Wang Y, Feng X, Li N. All authors reviewed the results and approved the final version of the manuscript.

    Data availability

    All data generated or analyzed during this study are included in this published article and its supplementary information files.

    Acknowledgments

    This work was supported by the National Natural Science Foundation of China (32172583), the Natural Science Foundation of Hebei (C2021209019), the Natural Science Foundation for Distinguished Young Scholars of Hebei (C2022209010), and the Basic Research Program of Tangshan (22130231H).

  • The authors declare that they have no conflict of interest.

  • [1]

    Lal RK, Chanotiya CS, Kumar A. 2023. The prospects and potential of the horticultural and pharmacological medicinal herb senna (Cassia angustifolia Vahl.): a review. Technology in Horticulture 3:20

    doi: 10.48130/TIH-2023-0020

    CrossRef   Google Scholar

    [2]

    Lal RK, Gupta P, Chanotiya CS, Mishra A, Kumar A. 2023. The nature and extent of heterosis, combining ability under the influence of character associations, and path analysis in Basil (Ocimum basilicum L.). Industrial Crops and Products 195:116421

    doi: 10.1016/j.indcrop.2023.116421

    CrossRef   Google Scholar

    [3]

    Patel SP, Malve SH, Chavda MH, Vala YB. 2021. Effect of Panchagavya and Jeevamrut on growth, yield attributes, and yield of summer pearl millet. The Pharma Innovation Journal SP-10:105−09

    Google Scholar

    [4]

    Kumar A, Gupta AK, Siddiqui S, Siddiqui MH, Jnanesha AC, et al. 2022. An assessment, prospects, and obstacles of industrially important medicinal crop Indian Senna (Cassia angustifolia Vahl.): a review. Industrial Crops and Products 187:115472

    doi: 10.1016/j.indcrop.2022.115472

    CrossRef   Google Scholar

    [5]

    Shubha S, Devakumar N, Rao GGE, Gowda SB. 2014. Effect of seed treatment, panchagavya application and organic farming systems on soil microbial population, growth and yield of maize, eds Rahmann G, Aksoy U. Proceedings of the 4th ISOFAR Scientific Conference. 'Building Organic Bridges', at the Organic World Congress 2014, Istanbul, Turkey. pp. 631−34.
    [6]

    Kumar A, Jnanesha AC. 2017. Enhancing the income of the farmer by cultivating senna in low rainfall area. Popular Kheti 5:14−17

    Google Scholar

    [7]

    Kumar A, Jnanesha AC, Bharath Kumar TP. 2018. Effect of different proportions of fly ash and vermicompost on growth and yield of Senna in Semi-arid regions of India. Journal of Pharmacology and Phytochemistry 7:69−72

    Google Scholar

    [8]

    Kumar A, Jnanesha AC, Verma RK, Kumar D, Lal RK. 2022. Phytoremediation, eco-restoration, and adaptive response of lemongrass (C. flexuosus Wats) grown on fly ash and vermicompost improved quality essential oil yield. Biochemical Systematics and Ecology 104:104457

    doi: 10.1016/j.bse.2022.104457

    CrossRef   Google Scholar

    [9]

    TNSMPB. 2006. Tamil Nadu State Medicinal Plants Board, Senna. Chennai, India: Tamil Nadu State Medicinal Plants Board, Government of India.
    [10]

    Guhra T, Stolze K, Totsche KU. 2022. Pathways of biogenically excreted organic matter into soil aggregates. Soil Biology and Biochemistry. 164:108483

    doi: 10.1016/j.soilbio.2021.108483

    CrossRef   Google Scholar

    [11]

    Gore NS, Sreenivasa MN. 2011. Influence of liquid organic manures on growth, nutrient content, and yield of tomato (Lycopersicon esculentum Mill.) in the sterilized soil. Karnataka Journal of Agriculture Science 24:153−57

    Google Scholar

    [12]

    Malligawad LH, Parameshwarappa KG. 2006. Effect of organics on the productivity of Spanish bunch groundnut under rainfed farming situations. In Symposia of 18th World Congress of Soil Science (Frontiers of Soil Science-Technology and the Information Age), 2006. Philadelphia, Pennsylvania, USA. 607 pp.
    [13]

    Duraivadivel P, Bhani K, Santosh S, Hariprasad P. 2022. Untangling microbial diversity and functional properties of Jeevamrutha. Journal of Cleaner Production 369:133218

    doi: 10.1016/j.jclepro.2022.133218

    CrossRef   Google Scholar

    [14]

    Palekar S. 2006. Shoonya bandovalada naisargika krushi. Swamy Anand, Agri Prakashana, Bangalore, India. pp. 1−270.
    [15]

    Rama Reddy NR, Mehta RH, Soni PH, Makasana J, Gajbhiye NA, et al. 2015. Next-generation sequencing and transcriptome analysis predict the biosynthetic pathway of sennosides from Senna (Cassia angustifolia Vahl.), a non-model plant with potent laxative properties. PLoS ONE 10:e0129422

    doi: 10.1371/journal.pone.0129422

    CrossRef   Google Scholar

    [16]

    Waksman SA. 1917. Is there any fungus flora in the soil? Soil Science 3:565−90

    doi: 10.1097/00010694-191706000-00009

    CrossRef   Google Scholar

    [17]

    Aneja KR. 2003. Cultivation techniques for isolation and enumeration of microorganisms. In Experiments in microbiology, plant pathology, and biotechnology, IV Edition. New Age International (P) Ltd., Delhi. pp. 157–88.
    [18]

    Santosha Gowda GB, Sudhir Kamath KV, Lakshmana. 2021. Shelflife study of jeevamrutha prepared from cow dung and cow urine of different desi breeds. The Pharma Innovation Journal SP-10:236−39

    Google Scholar

    [19]

    Casida LE Jr, Klein DA, Santoro T. 1964. Soil dehydrogenase activity. Soil Science 98:371−76

    doi: 10.1097/00010694-196412000-00004

    CrossRef   Google Scholar

    [20]

    Tabatabai MA, Bremner JM. 1972. Assay of urease activity in soils. Soil Biology and Biochemistry 4:479−87

    doi: 10.1016/0038-0717(72)90064-8

    CrossRef   Google Scholar

    [21]

    Hayano K. 1973. A method for the determination of β-glucosidase activity in soil. Soil Science and Plant Nutrition 19:103−08

    doi: 10.1080/00380768.1973.10432524

    CrossRef   Google Scholar

    [22]

    Panse VG, Sukhatme PV. 1956. Statistical methods for agricultural workers. Agronomy Journal 48:323

    doi: 10.2134/agronj1956.00021962004800070014x

    CrossRef   Google Scholar

    [23]

    Somasundaram E, Sankaran N, Meena S, Thiyagarajan TM, Chandragiri KK, et al. 2007. Response of green gram to varied concentrations of Panchakavya (organic nutrition) foliar application. Madras Agriculture Journal 90:169−72

    Google Scholar

    [24]

    Chongre S, Mondal R, Biswas S, Munshi A, Mondal R, et al. 2019. Effect of liquid manure on growth and yield of summer green gram (Vigna radiata L. Wilczek). Current Journal of Applied Science and Technology 38:1−7

    doi: 10.9734/CJAST/2019/v38i630460

    CrossRef   Google Scholar

    [25]

    Manjunatha GS, Upperi SN, Pujari BT, Yeledahalli NA, Kuligod VB. 2009. Effect of farm yard manure treated with jeevamrutha on yield attributes, yield and economics of sunflower (Helianthus annuus L.). Karnataka Journal of Agriculture Science 22:198−99

    Google Scholar

    [26]

    Siddappa MK, Devakumar N. 2016. Organically grown field bean (Lablab purpureus Var. lignosus) using jeevamrutha and farm yard manure. National Conference on Sustain Self-Sufficient Production of Pulses through an Integrated Approach. Bengaluru, India. pp. 105.
    [27]

    Brajeshwar, Joshi AK, Dey S. 2007. Effect of Kunapajala and Fertilizers on Senna (Cassia angustifolia Vahl.). Indian Forester 133:1235−40

    doi: 10.36808/if/2007/v133i9/1199

    CrossRef   Google Scholar

    [28]

    Aruw K, Bapi D, Reddy GS. 2011. Effect of organic manures, biofertilizers, and inorganic fertilizers on growth and yield of Senna (Cassia angustifolia Vahl.). The Asian Journal of Horticulture 7:144−47

    Google Scholar

    [29]

    Bhattacharjee U, Uppaluri RVS. 2023. Production and optimization of Jeevamrutha bio-fertilizer formulations for soil fertility and its role in waste minimization. Sustainable Chemistry for Climate Action 2:1000025

    doi: 10.1016/j.scca.2023.100025

    CrossRef   Google Scholar

    [30]

    Upperi SN, Lokesh BK, Maraddi GN, Agnal MB. 2009. Jeevamrutha, a new organic approach for disease management and crop production in pomegranate and groundnut. Environment and Ecology 27:202−04

    Google Scholar

    [31]

    Ramesh Babu TI. 1996. Nutritional studies in ashwagandha. Thesis. Tamil Nadu Agricultural University, Coimbatore
    [32]

    Hemalatha P, Suresh T, Saraswathi T, Vadivel E. 2008. Studies on nutrient content, herbage yield and alkaloid content of kalmegh under integrated nutrient management system. Advances in Plant Science 21:447−51

    Google Scholar

    [33]

    Kalyanasundaram B, Kumar TS, Kumar S, Swaminathan V. 2008. Effect of N, P, with biofertilizers and vermicompost on growth and physiological characteristics of sweet flag (Acorus calamus L.). Advances in Plant Science 21:277−80

    Google Scholar

    [34]

    Anuja S, Jayasri P. 2011. Effect of organic nutrients on flowering and herbage yield of sweet basil (Ocimum basilicum L.). Advances in Plant Sciences 24:601−03

    Google Scholar

    [35]

    Senthilkumar B, Vasundhara M, Farooqi AA. 2003. Studies on dry matter production, nutrient uptake and quality in Tagetes minuta L. Indian Perfumer 47:375−81

    Google Scholar

    [36]

    Malligawad LH. 2010. Effect of organics on the productivity of groundnut and its residual effects on succeeding safflower under rainfed farming situations. In 19th World Congress of Soil Science, Soil Solutions for a Changing World, 2010, Brisbane, Australia. pp. 128–31
    [37]

    Kumar A, Husain D, Lal RK, Singh S, Singh V, et al. 2023. Genetic diversity and future prospects in Withania somnifera (L.) Dunal: an assessment based on quantitative traits in different accessions of Ashwagandha. The Nucleus 66:151−59

    doi: 10.1007/s13237-023-00423-9

    CrossRef   Google Scholar

    [38]

    Kumar A, Jnanesha AC, Lal RK, Chanotiya CS, Venugopal S, et al. 2023. Precision agriculture innovation focuses on sustainability using GGE biplot and AMMI analysis to evaluate GE interaction for quality essential oil yield in Eucalyptus citriodora Hook. Biochemical Systematics and Ecology 107:104603

    doi: 10.1016/j.bse.2023.104603

    CrossRef   Google Scholar

    [39]

    Bilia AR, Cioni P, Morelli I, Coppi C, Lippi A, et al. 1992. Essential oil of Satureja montana, L. ssp. montana. composition and yields of plants grown under different environmental conditions. Journal of Essential Oil Research 4:563−68

    doi: 10.1080/10412905.1992.9698136

    CrossRef   Google Scholar

    [40]

    Devakumar N, Rao GGE, Shubha S, Imrankhan N, Gowda SB. 2008. Activities of organic farming research centre. Navile, Shivamogga, University of Agricultural Sciences, Bangalore. 12 pp.
    [41]

    Lal RK, Chanotiya CS, Gupta P, Mishra A, Bisht D, Maurya R, Srivastava S, Pant Y. 2021. Multi-years/environmental evaluation for high photosynthetic, bio-efficient, and essential oil genotypes selection in the breeding of vetiver (Chrysopogon zizanioides (L.) Roberty) crop. Journal of Essential Oil Research 33:471−87

    doi: 10.1080/10412905.2021.1917459

    CrossRef   Google Scholar

    [42]

    Lal RK. 2022. The opium poppy (Papaver somniferum L.): historical perspectives recapitulate and induced mutation towards latex less, low alkaloids in capsule husk mutant: a review. Journal of Medicinal Plants Studies 10:19−29

    Google Scholar

    [43]

    Lal RK, Chanotiya CS, Gupta P, Mishra A. 2022. Influences of traits associations for essential oil yield stability in multi-environment trials of vetiver (Chrysopogon zizanioides L. Roberty). Biochemical Systematics and Ecology 103:104448

    doi: 10.1016/j.bse.2022.104448

    CrossRef   Google Scholar

    [44]

    Boraiah B, Devakumar N, Shubha S, Palanna KB. 2017. Effect of Panchagavya, Jeevamrutha and cow urine on beneficial microorganisms and yield of capsicum (Capsicum annuum L. var. grossum). International Journal of Current Microbiology and Applied Sciences 6:3226−34

    doi: 10.20546/ijcmas.2017.609.397

    CrossRef   Google Scholar

    [45]

    Mallikarjun M, Maity SK. 2018. Effect of integrated nutrient management on soil biological properties in Kharif rice. International Journal of Current Microbiology and Applied Sciences 7:1531−37

    doi: 10.20546/ijcmas.2018.711.176

    CrossRef   Google Scholar

    [46]

    Kulkarni SS, Gargelwar AP. 2019. Production and microbial analysis of Jeevamrutham for nitrogen fixers and phosphate solubilizers in the rural area of Maharashtra. IOSR Journal of Agriculture and Veterinary Science 12:85−92

    Google Scholar

    [47]

    Kumar A, Lal RK, Chanotiya CS. 2023. Geraniol-rich aromatic grasses (Cymbopogon spreng) can adapt to the environment by modifying harvest dates over the ecosystems in southern India on the Deccan plateau utilizing participatory management modeling and agronomic practices. Industrial Crops and Products 193:116196

    doi: 10.1016/j.indcrop.2022.116196

    CrossRef   Google Scholar

  • Cite this article

    Jnanesha AC, Venugopal S, Kumar SR, Kumar A, Bisht D, et al. 2024. Optimization of a new organic approach to natural biostimulant (Jeevamrutha) for yield and quality management in Senna (Cassia angustifolia Vahl.): an agriculturally highly export-oriented crop. Technology in Horticulture 4: e009 doi: 10.48130/tihort-0024-0006
    Jnanesha AC, Venugopal S, Kumar SR, Kumar A, Bisht D, et al. 2024. Optimization of a new organic approach to natural biostimulant (Jeevamrutha) for yield and quality management in Senna (Cassia angustifolia Vahl.): an agriculturally highly export-oriented crop. Technology in Horticulture 4: e009 doi: 10.48130/tihort-0024-0006
    shu

Figures(4)  /  Tables(7)

Download PDF

Article Metrics

Article views(3320) PDF downloads(814)

Other Articles By Authors

ARTICLE   Open Access    

Optimization of a new organic approach to natural biostimulant (Jeevamrutha) for yield and quality management in Senna (Cassia angustifolia Vahl.): an agriculturally highly export-oriented crop

  • 1.

    Crop Production & Protection Divisional Unit, CSIR-Central Institute of Medicinal and Aromatic Plants, Research Centre, Boduppal, Hyderabad, Telangana State, 500092, India

  • 2.

    CSIR-Central Institute of Medicinal and Aromatic Plants, Lucknow, U.P. State, 226015, India

  • Received: 20 June 2023
  • Revised: 25 December 2023
  • Accepted: 01 March 2024
  • Published online: 02 April 2024
Technology in Horticulture  4,  Article number: e009  (2024)  |  Cite this article

Abstract: Senna is a leguminous and industrial crop that produces high-quality glycosides (sennosides) in its leaves and pods, which have substantial therapeutic effects for alleviating constipation worldwide. However, further research on employing Jeevamrutha in Senna is required. As a result, the experiment was carried out at CSIR-CIMAP in Hyderabad for two consecutive years, in the years 2020–2021 and 2021–2022. The main aim is to identify the optimum dose of Jeevamrutha for higher growth, yield, and quality in Senna. The study used a randomized complete block design (RCBD) with seven treatments repeated three times. From the obtained result, it was observed that the application of 150 L of Jeevamrutha per acre observed significantly high leaf yields (1,085.2 kg·ha−1) and pod (318.7 kg·ha−1) equivalent to T2 in comparison to other treatments, i.e., application of 125 L of Jeevamrutha per acre (1,022.5 kg·ha−1, 312.1 kg·ha−1), and was succeeded by T3, i.e., application of 100 L of Jeevamrutha per acre (998.5 kg·ha−1, 288.5 kg·ha−1, respectively). Lower leaf yield (700.2 kg·ha−1) and pod yield (487 kg·ha−1) were observed in the control (T7). Similarly, the application of 150 L of Jeevamrutha per acre recorded significantly higher sennoside content in leaves (2.01%) and pods (3.11%), in comparison to other treatments, and was followed by T2 (1.98%, 3.09%) and T3 (1.89%, 2.97%). A similar trend was noticed in returns, i.e., the application of 150 L of Jeevamrutha per acre recorded significantly higher gross returns (USD$1,495 ha−1) and net returns (USD$1,066.4 ha−1).

    HTML

    Introduction

    • Cassia angustifolia (Caesalpinaceae), known as Tinnevelly or Indian Senna, is cultivated for its leaves and immature pods. Dianthrone glucosides and sennosides A and B in the leaves and pods have potent laxative properties[1,2]. Sennosides primarily operate on the lower colon and are notably beneficial in cases of chronic constipation[1,3]. The glycosides are absorbed from the intestinal system; they stimulate the peristaltic movements of the colon, causing it to move. Long-term usage of the leaves may induce colon problems and produce grip if not paired with carminatives. The National Medicinal Plant Board (NMPB) of India has identified 32 plants for scaling up, and Senna is one of them. Senna is the second-largest earner of foreign exchange through exports. Its leaves and pods are regarded as reliable sennoside sources in global trade[4]. However, Indian Senna should compete with Alexandrian Senna regarding cost-effectiveness and quality. Alexandrian senna natural collections cannot supply the growing demand for Senna commodities. India has a tremendous opportunity to expand its manufacturing, commerce, and export opportunities. Tinnevelly Senna (C. angustifolia) is grown in India's southern and central parts[5]. Senna herbage production is estimated to be around 7,500 tonnes per year. The pods and leaves of a few other senna species, the most important of which is Alexandrian Senna, have laxative properties similar to those of Cassia angustifolia. Alexandrian Senna grows naturally in North African countries such as Ethiopia and Sudan[1,2].

      The swiftly increasing global population and continuously expanding geographical boundaries of the global agricultural system are extending agricultural activities on marginal soils unsuited for growing. On such terrain, crop options are limited, especially in an arid macroregion. Senna is a tropical medicinal plant that could be a dry-land crop for barren land. Areas with inadequate irrigation facilities (arid or semi-arid) are ideal for Senna cultivation, while regions with heavy rainfall, high humidity, and poor drainage are not perfect[6−8]. Senna grows as a perennial shrub in dry areas of Africa and neighboring countries. The Senna crop is commercially grown in all sub-tropical regions of India and spread in semi-arid parts of southern India; it is marketed under the brand name 'Tirunelveli Senna' (C. angustifolia)[3,9,10]. Tuticorin has many exporters, shipping 7,500 to 9,000 tonnes of Senna leaves each year and earning Rs 35 to 60 crore in forex 'depending on the current market price'[9].

      Modern agriculture relies heavily on chemical fertilizers to cope with the demands of a growing population. The continued use of inorganic fertilizers endangers soil health. The beneficial microorganisms decline, and natural nutrition restoration in the soil ceases, causing the soil to become unfertile[9,10]. As a result, the use of organic manure and proportionate inorganic fertilizers needs to be reduced to improve the quality and productivity of the crop's food grain, oilseed, or medicinal crop. This gradually results in a significant need for integrated nutrient management (INM), which will boost soil productivity continuously over time through the appropriate use of fertilizers and liquid organic manure[11,12].

      Organic farming has recently risen in popularity because of its inherent benefits. It contributes to crop production sustainability, complex soil nutrient status, and a clean environment[11,12]. Using fermented liquid organic manure or bio-enhancers like Jeevamrutha is a less expensive and eco-friendly preparation made from cow products. A natural biostimulant (Jeevamrutha) is a plant growth stimulant that increases crop biological efficiency[13]. It aids in accelerating soil, protects plants from diseases, and enhances the nutritional content of fruits and vegetables. It has been utilized in seedling treatment, soil application with irrigation water, foliar spraying, and much more.

      The application of liquid manure boosts microbial activity and biomass in the soil. The use of liquid organic inputs like Jeevamrutha boosts the population of beneficial bacteria and has a substantial impact on soil enzyme activity. As a result, they promote crop growth and help to maintain a safe environment and production of crops. Given the foregoing, the experiment was conducted at CSIR-CIMAP, RC, Hyderabad, with the aim of establishing the optimal doses of Jeevamrutha for increasing Senna quality and production.

    Materials and methods

      Experimental field and statistical design

    • A trial was undertaken in the CSIR-CIMAP R.C. in Hyderabad, India, for two consecutive years, 2020−2021 and 2021−2022 in the Rabi season (September to January). The experimental site's latitude, longitude, and altitude were 17°25' N, 78°33' E, and 582 m above mean sea level. Table 1 lists further information, including the climatic conditions. The experiment was laid out in a randomized complete block design (RCBD) with three replications on well-drained, red sandy soil (Table 1).

      Table 1.  Location, climate and soil of CSIR-CIMAP R.C. at Boduppal, Hyderabad, Telangana State, PIN: 500 092, India and chemical composition of bio stimulant.

      GPS coordinates, soil and climateEstimated parameters of bio stimulant (Jeevamrutha)
      Latitude17°25' N
      Longitudes78º33' EpH7.08
      Mean sea level582 m aboveEC (dS·m−1)2.98
      ClimateSemi-arid tropicalTotal nitrogen (ppm)67
      Average annual rainfall764 mmTotal phosphorus (ppm)154
      SoilRed sandy soil (79.2% sand, 9.8% silt, 6.8% clay)
      		Total potassium (ppm)112
      pH7.7Total zinc (ppm)3.52
      EC0.77 dS·m−1Total copper1.32
      Organic carbon0.29%Total iron (ppm)12.4
      Available N162.4kg·ha−1Total manganese (ppm)7.4
      Available P9.2 kg·ha−1IAA (ppm)5.9
      Available K272.6 kg−1GA3 (ppm)3.1

      Preparation of biostimulant/ Jeevamrutha

    • The method of Palekar was used to prepare the organic liquid formulation Jeevamrutha[14]. The following were the ingredients: 10 kg cow dung, 10 L of cow urine of Gir cow breeds, 2 kg jaggery, 2 kg gram/chickpea (pulse) flour, a handful of rhizospheric soil, and 200 L of water were well combined in a stainless steel container with the help of a wooden stick. The cow dung and urine source was a local dairy farm located at Boduppal, Hyderabad, Telangana State, 500092, India. The mixture was mixed twice daily and fermented for 5–7 d. The prepared liquid formulation was used for soil application by applying irrigation water. In the Department of Soil Chemistry Laboratory at the Council of Scientific Research-Central Institute of Medicinal and Aromatic Plants, Boduppal, Hyderabad, Telangana State, 500092, India, the chemical composition of the biostimulant (Jeevamrutha) was determined. The results are presented in Table 1.

      Treatments

    • The treatments were comprised of seven treatments with three replications, viz., T1: application of 150 L of Jeevamrutha per acre, T2: application of 125 L of Jeevamrutha per acre, T3: application of 100 L of Jeevamrutha per acre, T4: application of 75 L of Jeevamrutha per acre, T5: application of 50 L of Jeevamrutha per acre, T6: application of 25 L of Jeevamrutha per acre, and T7: control (treated with water).

      Recommended cultivation practices

    • Senna (C. Angustifolia) var: Sona seeds were soaked in water for a whole night and treated with Trichoderma to minimize the seeds' correlation with diseases before dibbling in the field at 45 cm × 30 cm spacing. The field was irrigated for the first few weeks; one weeding was performed 30 d after seeding, and N:P:K (kg·ha−1) was applied at the seeding time.

      Quantitative and qualitative traits evaluated

    • Growth and yield contributing attributes were recorded at regular intervals at various phases of plant growth. The sennoside content of leaves and pods was determined using the HPLC method developed by Rama Reddy et al.[15] at the pod formation stage. Finely ground samples of dry leaves and pods (300 mg) were extracted three times with sonication (25 °C) in 30 ml of 70% methanol in water. Before being fed into the chromatographic equipment, the materials were filtered through a 0.45 m membrane. The HPLC study was conducted on a Waters HPLC system outfitted with an SPD-M20 photodiode array detector.

      The dilution plate technique determined each treatment's fungal, bacterial, and actinomycete populations[10,13,16]. For each treatment, a composite of 10 g of soil samples was extracted, and 1 g of each sample was suspended in 1 mL sterile saline (1g NaCl in 100 mL distilled H2O) in a sterile test tube and carefully vortexed. Different treatment tubes were employed to count fungi, bacteria, and actinomycetes as part of the inoculation. Soil samples were taken from the rhizosphere of plants for counting microbial load at harvest for N-fixers and P-solubilizers. Ten grams of soil was serially diluted up to 10−6 by using sterilized distilled water, and cell count per gram of rhizosphere soil was enumerated for P-solubilizers and free-living N-fixer by Pikovaskaya's media (Himedia) and Waksman No.77[13,17,18], respectively, by following the serial dilution plate count technique.

      Soil dehydrogenase activity was determined by reducing 2,3,5-triphenyl tetrazolium chloride[2,10,19]. Protease activity was measured by measuring the amount of tyrosine produced after incubating 1 g of the oven-dry equivalent of a field-moist soil sample in 5 ml of 50 mM Tri's buffer (pH 8.1) and 5 ml of 2% Na-caseinate for 2 h at 50 + 1 °C. The aromatic amino acids were removed, and the residual substrate was precipitated with 0.92 M trichloroacetic acid and calorimetrically quantified at 700 nm using the Folin-Ciocalteu reagent. Protease activity was quantified as mg tyrosine generated g−1·soil·h−1.

      Acid and alkaline phosphatase activities were determined using a standard approach[20]. In a 50 ml flask, 1 g of soil was mixed with 0.2 mL toluene, 4 mL of modified universal buffer (MUB) (pH 6.5 and 11, respectively, for acid and alkaline phosphatase), and 1 mL of p-nitrophenyl phosphate solution. After an hour of incubation, 1 mL of 0.5 M CaCl2 and 4 mL of 0.5 M NaOH were added. After the suspension was filtered, the filtrate's absorbance at 420 nm was measured using a UV-visible spectrophotometer. Controls were prepared by repeating the phosphatase activity assay technique but adding 1 mL of p-nitrophenol solution after adding 0.5 M CaCl2 and 4 mL of 0.5 M NaOH. Determination of β-glucosidase enzyme involves colorimetric estimation of P-nitrophenol released by β-glucosidase activity when soil is incubated in Mcilvaine buffer (pH 4.8) with P-nitrophenyl β-D-glucoside and toluene at 30 °C for 1 h[21] (Fig. 1).

      Figure 1. 

      Field view of the experimental plot of Senna crop.

      Economics

    • The benefit of gross returns was determined by multiplying the total yield by the present cost of each kilogram. The cost of cultivation for each treatment was calculated by summing up the seed cost, land preparation, labour, cultural operations, pesticides, and manure costs. Net returns were computed by subtracting manufacturing costs from gross returns. The benefit-cost ratio was determined by calculating the ratio between cultivation costs and gross returns. It is obtained by dividing the gross returns by the cost of cultivation in USD$·ha−1.

      Statistical analysis

    • The analysis of variance (ANOVA) was performed on the pooled data for the experimental years 2020−2021 and 2021−2022 using CSIR-CIMAP statistical software Ver. 4.0[22].

    Results and discussion

      Influence of biostimulant/Jeevamrutha on growth parameters

    • The obtained results reveal that Jeevamrutha application had a significant influence on all of the characteristics of Senna (C. angustifolia). Amid the various doses of Jeevamrutha, the application of 150 L of Jeevamrutha recorded significantly higher plant height (T1; 43.7 cm) compared to another dose of application and was comparable to the applications of 125 L of Jeevamrutha per acre (T2; 40.2 cm) and 100 L of Jeevamrutha per acre (T3; 39.2 cm). Significantly, lower plant height was noticed in control (T7; 26.9 cm) and was on par with applying Jeevamrutha at 25 L per acre (T6; 29.9 cm). The number of branches and plant leaves per plant, and total dry matter production all followed a similar pattern. Applying 150 L (T1) of biostimulant/Jeevamrutha per acre recorded a substantially higher branch per plant, leaves per plant, and total dry matter production (19.9, 180.3, and 35.9 g·plant−1). It was on par with (T2) 125 L of Jeevamrutha (17.2, 177.2, and 34.2 g·plant−1), and the application of 100 L (T3) of Jeevamrutha (16.8, 176.4 and 33.1 g·plant−1). Senna's plant height and dry matter content may have improved substantially due to the availability of micronutrients and a big beneficial microbial population in Jeevamrutha[1−3,23]; thus, when applied to the crop as a foliar spray and through the soil, they stimulate the necessary plant growth, which encourages vegetative growth and finally increases plant height and metabolic and photosynthetic activity for improving the biological efficiency of the plant, allowing the roots to spread into deeper layers of soil and uptake more nutrients from the soil, resulting in the accumulation of more carbohydrates and higher dry matter. Our results are consistent with those of other researchers[3,16,24−26]. Whereas, chlorophyll content, leaf area, and index also differed significantly with the use of a varied dose of Jeevamrutha, with the application of 150 L (T1) of Jeevamrutha per acre recording significantly higher chlorophyll content (13.2), leaf area (66.2 cm2) and LAI (4.89) comparison with the other treatments and was succeeded with T2 (12.1, 64.2 cm2, 4.76) and T3 (10.2, 63.9 cm2, 4.73) (Fig. 2). The use of Jeevamrutha resulted in faster synthesis, translocation, and accumulation of photosynthates from sources to sinks, ultimately contributing to higher growth and yield metrics (Tables 1 & 2, Fig. 2). These findings are consistent with those of other studies[27,28] in Senna.

      Figure 2. 

      Influence of different doses of biostimulant/Jeevamrutha on leaf yield (kg·ha−1) and pod yield (kg·ha−1) of Senna.

      Table 2.  Microbial population in bio stimulant.

      OrganismsBio stimulant (Jeevamrutha)
      Bacteria (cfu·mL−1)15.42 × 105
      Fungi (cfu·mL−1)12.12 × 103
      Actinomycetes (cfu·mL−1)2.92 × 103
      Free-living nitrogen fixers (cfu·mL−1)5.20 × 102
      Phosphate solubilizing organisms (cfu·mL−1)3.20 × 102

      Effect of biostimulant/Jeevamrutha on the pods per plant

    • The pods/plant produced significantly depended on the dose of Jeevamrutha used. Among the various Jeevamrutha dosages, the application of Jeevamrutha at 150 L per acre recorded significantly higher pods per plant (T1; 726) compared to other treatments and was on par with (T2; 720) and (T3; 689). The significantly lower pods per plant were noticed in control (T7; 700.8) and were followed by T6 (T6; 758.9) (Table 3). The increase in pods per plant might be due to Jeevamrutha, which increases the production of growth hormones, viz., IAA, GA, and dehydrozeatin, resulting in good pod characteristics[1,29,30]. These phytohormones increased cell proliferation, elongation, and nutrient uptake, increasing pods per plant. Ramesh Babu[31] found similar results in Ashwagandha (Table 3).

      Table 3.  Effect of different doses of bio stimulant (Jeevamrutha) on growth and yield parameters of Senna in semi-arid regions of India.

      TreatmentsPlant height (cm)No. of branches per plantNo. of leaves per plantTotal dry matter production (g·plant−1)Chlorophyll contentLeaf areaLAINo of pods
      per plant
      T143.719.9180.335.9113.2566.024.89726
      T240.217.2177.234.2512.1364.214.76720
      T339.216.8176.433.1210.2463.924.73689
      T434.214.2165.229.749.2359.214.39654
      T531.513.8154.725.159.0156.274.17598
      T629.910.2144.323.218.7855.324.10546
      T726.98.5135.221.588.0349.133.64487
      S.Em±1.820.912.81.340.521.40.1118.2
      CD (P = 0.05)5.412.748.44.021.564.20.3454.7
      T1: 150 L of bio stimulant per acre, T2: 125 L of bio stimulant per acre, T3: 100 L of bio stimulant per acre, T4: 75 L of bio stimulant per acre, T5: 50 L of bio stimulant per acre, T6: 25 L of bio stimulant per acre, T7: Control.

      Effect of Jeevamrutha on leaf and pod yield

    • Leaf and pod yield of C. angustifolia differ significantly with a varied dose of Jeevamrutha. Among the varied treatments, the application of 150 L (T1) of Jeevamrutha per acre recorded significantly higher leaf yield (1,085.2 kg·ha−1) and pod yield (318.7kg·ha−1) in comparison to the rest of the treatments. It was on par with T2 i.e., applying 125 L of Jeevamrutha per acre (1,022.5 kg·ha−1, 312.1 kg·ha−1) followed by T3, i.e., application of 100 L of Jeevamrutha per acre (998.5 kg·ha−1, 288.5 kg·ha−1, respectively). Significantly, lower leaf (700.2 kg·ha−1) and pod yield (487 kg·ha−1) were noticed in the control (T7) (Fig. 3). Raised nutrient availability, enhanced soil health, and an appropriate supply of macro and micronutrients might all have contributed to the rise in leaf and pod yield, which raised seed yield. Furthermore, Jeevamrutha may have created a favorable environment in the soil for nitrogen buildup in addition to boosting nutrient availability (Fig. 3). Hemalatha et al.[32] found similar results in kalmegh[13,32], and Kalyanasundaram et al.[33] in the sweet flag, and Anuja & Jayasri[34] in sweet basil[30,34]. The sustained availability of nutrients by applying Jeevamrutha throughout the cropping period increased soil microbial activity, and the photosynthetic rate might have increased the leaf and pod yield[4,8,35−38].

      Figure 3. 

      Influence of biostimulant/Jeevamrutha on gross and net return in Senna.

      Effect of biostimulant/Jeevamrutha on sennoside content

    • Despite the Jeevamrutha dose, the sennoside concentration of Senna (C. angustifolia) pods is always higher than that of the leaves. Sennoside content in both leaf and pod altered drastically following Jeevamrutha treatment, as seen in (Table 2). Among the different treatments, T1, i.e., application of 150 l of Jeevamrutha per acre, recorded significantly higher sennoside content in leaves (2.01%) and pods (3.11%) in comparison to the rest of the treatment and was followed by T2 (1.98%, 3.09%) and T3 (1.89%, 2.97%). This feature could be related to an increase in enzyme activity associated with the sennoside biosynthesis pathway, as well as a shift from primary to secondary metabolite synthesis[39−43]. Lower sennoside content in leaves and pods is recorded in control (T7; 1.52%, 2.42%). A similar trend was noticed in sennoside yield with T1, i.e., application of Jeevamrutha at 150 L per acre recorded significantly higher sennoside yield (31.7 kg−1) compared to other treatments. It was followed by T2 (29.9 kg·ha−1) and T3 (27.4 kg·ha−1). Lower sennoside yield was noticed in control (T7; 15.2 kg·ha−1) (Table 4). This attribute might be owing to increased yield and sennoside content in the leaf and pod, which in turn, increase the sennoside yield in T1 and T2 treatments, i.e., application of Jeevamrutha at 150 and 125 L per acre, respectively (Tables 4 & 5).

      Table 4.  Effect of bio stimulant (Jeevamrutha) on sennoside content in leaves and pod and sennoside yield.

      TreatmentsSennoside content (%)Sennoside yield
      (kg·ha−1)
      LeavesPod
      T12.013.1131.7
      T21.983.0929.9
      T31.892.9727.4
      T41.932.6922.8
      T51.872.6620.5
      T61.692.5917.9
      T71.522.4215.2
      S.Em±0.030.061.2
      CD (P = 0.05)0.090.123.7
      T1: 150 L of bio stimulant per acre, T2: 125 L of bio stimulant per acre, T3: 100 L of bio stimulant per acre, T4: 75 L of bio stimulant per acre, T5: 50 L of bio stimulant per acre, T6: 25 L of bio stimulant per acre, T7: Control.

      Table 5.  Effect of different doses of bio stimulant (Jeevamrutha) on beneficial microorganisms in the soil.

      TreatmentsBacteria
      (cfu·g−1)      		Fungi
      (cfu·g−1)      		Actinomycetes
      (cfu·g−1)      		Nitrogen fixer
      (cfu·g−1)      		P solubilizers
      (cfu·g−1)
      T18.2 × 1057.3 × 1044.1 × 1031.9 × 1033.9 × 103
      T27.6 × 1056.8 × 1044.0 × 1032.1 × 1033.2 × 103
      T37.1 × 1056.2 × 1043.7 × 1031.7 × 1032.7 × 103
      T46.7 × 1055.8 × 1043.6 × 1031.8 × 1032.5 × 103
      T56.0 × 1055.1 × 1043.4 × 1031.2 × 1031.9 × 103
      T66.2 × 1054.9 × 1042.8 × 1031.4 × 1031.7 × 103
      T75.7 × 1054.2 × 1042.2 × 1031.3 × 1031.6 × 103
      S.Em±0.3 × 1050.4 × 1040.23 × 1030.3 × 1030.1 × 103
      CD
      (P = 0.05)      		0.9 × 1051.2 × 1040.55 × 103NS0.3 × 103
      T1: 150 L of bio stimulant per acre, T2: 125 L of bio stimulant per acre, T3: 100 L of bio stimulant per acre, T4: 75 L of bio stimulant per acre, T5: 50 L of bio stimulant per acre, T6: 25 L of bio stimulant per acre, T7: Control.

      Effect of biostimulant/Jeevamrutha on beneficial microorganisms and enzyme activity

    • Beneficial microorganisms in soil differ significantly with the application of different doses of Jeevamrutha in Senna; with an application of 150 L of Jeevamrutha per acre recorded significantly higher bacteria (8.2 × 105 cfu·g−1), fungi (7.3 × 104 cfu·g−1), actinomycetes (4.1 × 103 cfu·g−1) and P solubilizers (3.9 × 103 cfu·g−1) compared to rest of the treatment and was on par with the application of 150 L of Jeevamrutha per acre (7.6 × 105 cfu·g−1, 6.8 × 104 cfu·g−1, 3.7 × 103 cfu·g−1, and 2.7 × 103 cfu·g−1, respectively).

      Nonetheless, the greater dose of Jeevamrutha resulted in a more substantial microbial population, which might be ascribed to Jeevamrutha acting as a source of carbon and energy for microorganisms, boosting the number of microorganisms in the soil. However, a significantly lower microbial population was noticed in control, i.e., bacteria (5.7 × 105 cfu·g−1), fungi (4.2 × 104 cfu·g−1), actinomycetes (2.2 × 103 cfu·g−1), and P solubilizers (1.6 × 103 cfu·g−1). The low microbial population counts in control could be attributed to a lack of substrate to sustain microbial biomass. The acquired results are consistent with the findings of Boraiah et al.[44]. Similarly, enzyme activity in soil differs dramatically when Jeevamrutha is applied to Senna. Among the different doses of Jeevamrutha, the application of 150 L of Jeevamrutha per acre recorded significantly higher dehydrogenase activity (1.33 µg·TPF−1·g−1·h−1), alkaline phosphatase (412 µg·TPF−1·g−1·h−1), acid phosphatase (367 µg·TPF−1·g−1·h−1), β-Glucosidase (120 µg·TPF−1·g−1·h−1) and protease (154 µg·TPF−1·g−1·h−1) compared to rest of the treatment and was followed by application of 125 L of Jeevamrutha per acre (1.17 µg·TPF−1·g−1·h−1, 374 µg·TPF−1·g−1·h−1, 355 µg·TPF−1·g−1·h−1, 99 µg·TPF−1·g−1·h−1 and 123 µg·TPF−1·g−1·h−1). Enzymatic activity was considerably lower in the control group.

      Nonetheless, the increased enzymatic activity in the soil can be attributed to the important function of the microbial population as a result of the addition of Jeevamrutha, which acted as a tonic for enhanced microbial development[1,2,4,29]. Enzymatic activity in the soil may have increased due to favorable bacterial environments (Tables 5 & 6). The higher enzymatic activity in the Jeevamrutha plot could be explained by enhanced microbial activity[44−47].

      Table 6.  Effect of different doses of bio stimulant (Jeevamrutha) on enzyme activity in the soil.

      TreatmentsDehydrogenase activity (µg·TPF−1·g−1·h−1)Alkaline phosphatase (µg·TPF−1·g−1·h−1)Acid phosphatase (µg·TPF−1·g−1·h−1)β-Glucosidase
      (µg·TPF−1·g−1·h−1)      		Protease
      (µg·TPF−1·g−1·h−1)
      T11.33412367120154
      T21.1737435599123
      T30.9038224884120
      T40.7529120175100
      T50.542771556585
      T60.481321125059
      T70.4188552922
      SEm±0.1512.87.13.94.8
      CD (P = 0.05)0.4538.221.411.714.1
      T1: 150 L of bio stimulant per acre, T2: 125 L of bio stimulant per acre, T3: 100 L of bio stimulant per acre, T4: 75 L of bio stimulant per acre, T5: 50 L of bio stimulant per acre, T6: 25 L of bio stimulant per acre, T7: Control.

      Effect of biostimulant/ Jeevamrutha on economics

    • Economics of Senna (C. angustifolia) may differ significantly about the varied application of Jeevamrutha, with the application of 150 L (T1) of Jeevamrutha per acre recorded substantially higher gross return per ha (USD$1,495) and Net return (USD$1,066.4 compared to other treatments and was on par with the application of 125 L (T2) of Jeevamrutha per acre (USD$1,423.8 and 995.2 respectively) and was followed by T3 (USD$1,369.4 and 940.9). Significantly lower gross return (USD$942.9) and net returns (USD$585.8) were noticed in control (T7) (Fig. 4). Similarly, the benefit-cost ratio differed significantly from T1, i.e., the application of 150 L of Jeevamrutha per acre recorded a higher benefit-cost ratio (3.49) than other treatments. T2 applied 125 L of Jeevamrutha per acre (3.32) (Tables 5−7). In contrast, a lower benefit-cost ratio was noticed in control (T7; 2.64) and was followed by T6 (2.72) (Table 7, Fig. 4).

      Figure 4. 

      Application of 150 L (T1) of Jeevamrutha to Senna crop.

      Table 7.  Effect of different doses of bio stimulant (Jeevamrutha) on gross and net return of Senna.

      TreatmentsGross return
      (USD$·ha−1)      		Net return
      (USD$·ha−1)      		Benefit-cost ratio
      T11,495.01,066.43.49
      T21,423.8995.23.32
      T31,369.4940.93.20
      T41,154.9726.32.99
      T51,067.9689.32.82
      T61,009.4637.92.72
      T7942.9585.82.64
      S.Em±21.821.8
      CD (P = 0.05)64.564.5
      T1: 150 L of bio stimulant per acre, T2: 125 L of bio stimulant per acre, T3: 100 L of bio stimulant per acre, T4: 75 L of bio stimulant per acre, T5: 50 L of bio stimulant per acre, T6: 25 L of bio stimulant per acre, T7: Control.

      Finally, Jeevamrutha is a natural fertilizer that can be used in place of chemical fertilizers. It is a type of organic liquid fertilizer used in organic farming and gardening. It is made from natural ingredients and is believed to be a sustainable and eco-friendly alternative to synthetic fertilizers. While it can be a valuable addition to organic farming practices, it's important to note that its nutrient content, including NPK (Nitrogen, Phosphorus, and Potassium), varies depending on how it's prepared. In general, Jeevamrutha is not typically formulated to have specific NPK values like synthetic fertilizers. Instead, its primary focus is on improving soil health and promoting microbial activity in the soil, which can lead to better nutrient availability for plants over time. It is rich in beneficial microorganisms, such as beneficial bacteria, fungi, and other soil organisms, which help break down organic matter and release nutrients in a form that plants can absorb. Jeevamrutha is more of a soil conditioner and biofertilizer that enhances soil fertility and overall plant health rather than directly providing specific nutrient values like NPK ratios. It is used to improve the structure and fertility of the soil and is often considered a holistic approach to sustainable agriculture. If farmers are looking for specific NPK values in fertilizer, they may need to consider synthetic fertilizers or other organic fertilizers that provide more precise nutrient content. However, many organic and sustainable farmers prefer using Jeevamrutha and similar products to support long-term soil health and reduce their reliance on chemical fertilizers. It is high in macronutrients and micronutrients, which are necessary for plant growth and development. Jeevamrutha promotes microbial activity, which enhances soil fertility. When compared to previous Jeevamrutha doses, using Jeevamrutha at 150 (T1) or 125 (T2) L per acre resulted in significantly higher leaf, pod, and sennoside yields. Meanwhile, increased leaf and pod production from a higher Jeevamrutha dose boosts Senna's gross and net returns, as well as the benefit-cost ratio.

    Conclusions

    • Jeevamrutha is a natural fertilizer that can replace chemical fertilizers. It is an excellent source of macro and micro nutrients for plant growth and development. Jeevamrutha improves soil fertility by stimulating microbial activity. The current study found that applying Jeevamrutha at 150 (T1)/125 (T2) L per acre resulted in significantly higher leaf, pod, and sennoside yields when compared to other Jeevamrutha doses. Meanwhile, increased leaf and pod production from a higher dose of biostimulant/Jeevamrutha raises Senna's gross and net returns and the benefit-cost ratio.

    Author contributions

    • The authors confirm contribution to the paper as follows: study planning, actual experimentation: Jnanesha AC; experimentation: Venugopal S, Kumar SR; Kumar A; data collection: Bisht D; Chemical analysis: Chanotiya CS; statistical analyses, and manuscript preparation: Lal RK. All authors reviewed the results and approved the final version of the manuscript.

    Data availability

    • The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

      Acknowledgments

      • This work was supported by the Council of Scientific and Industrial Research, India, under HCP 010; the last author is related to an emeritus scientist, CIMAP Publication No. CIMAP/PUB/2021/118. The authors are thankful to the director of CSIR-CIMAP Lucknow, India, for providing facilities and encouragement throughout the work. Thanks also to the Scientist-in-Charge at CRC Hyderabad for the necessary facilities during this investigation.

      Conflict of interest

      • The authors declare that they have no conflict of interest.

      Rights and permissions
      • Copyright: © 2024 by the author(s). Published by Maximum Academic Press, Fayetteville, GA. This article is an open access article distributed under Creative Commons Attribution License (CC BY 4.0), visit https://creativecommons.org/licenses/by/4.0/.
    Figure (4)  Table (7) References (47)
  • About this article
    Cite this article
    Jnanesha AC, Venugopal S, Kumar SR, Kumar A, Bisht D, et al. 2024. Optimization of a new organic approach to natural biostimulant (Jeevamrutha) for yield and quality management in Senna (Cassia angustifolia Vahl.): an agriculturally highly export-oriented crop. Technology in Horticulture 4: e009 doi: 10.48130/tihort-0024-0006
    Jnanesha AC, Venugopal S, Kumar SR, Kumar A, Bisht D, et al. 2024. Optimization of a new organic approach to natural biostimulant (Jeevamrutha) for yield and quality management in Senna (Cassia angustifolia Vahl.): an agriculturally highly export-oriented crop. Technology in Horticulture 4: e009 doi: 10.48130/tihort-0024-0006
    shu

Catalog

  • HTML

  • Introduction
  • Materials and methods

  • Experimental field and statistical design

  • Preparation of biostimulant/ Jeevamrutha

  • Treatments

  • Recommended cultivation practices

  • Quantitative and qualitative traits evaluated

  • Economics

  • Statistical analysis

  • Results and discussion

  • Influence of biostimulant/Jeevamrutha on growth parameters

  • Effect of biostimulant/Jeevamrutha on the pods per plant

  • Effect of Jeevamrutha on leaf and pod yield

  • Effect of biostimulant/Jeevamrutha on sennoside content

  • Effect of biostimulant/Jeevamrutha on beneficial microorganisms and enzyme activity

  • Effect of biostimulant/ Jeevamrutha on economics

  • Conclusions
  • Author contributions
  • Data availability
  • Acknowledgments
  • Conflict of interest
  • Rights and permissions
  • About this article
logo

Contents

Policies

Services

Partnerships

© 2025 Maximum Academic Press, except Open Access articles. MAP is a member of ALPSP, COPE, CrossRef, cOAlition S, OASPA and STM.

Privacy Policy  |  Site Map  |  Terms and Conditions

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return