Eggplant Production Research Articles

Determination of Antagonistic Effect Between Some Fusarium Species and Root Bacteria Isolated from Eggplant Roots

In this study, it was aimed to determine the antagonistic effect between and isolated from eggplant roots and some root bacteria conditions. 24 bacteria were isolated from soil samples taken from the rhizosphere regions of infected and non-infected plants in different eggplant production areas and 22 of them were evaluated as candidate biocontrol agents. According to the results of the research, 13 out of 22 bacteria were effective against, 14 against, and 9 against between 40% and 100%. The most effective bacteria against were 22B (100%) and 11B (74.4%). Among the bacteria tested for effectiveness against, 3B (100%), 10B (100%) and 18B (100%) completely inhibited fungal growth. These bacteria are followed by 11B (88.85%) and 13B (85.55%). 11B and 24B inhibited mycelial growth of 100%.

EFFECT OF AUTOMATED CONTROLLING SYSTEM USING RASPBERRY-PI MICROPROCESSOR ON GROWTH PARAMETERS OF EGGPLANT IN GREENHOUSE

To bridge up the quality gaps and excel in the production of eggplant there is a need to switch the conventional production system to smart greenhouse house monitoring system. The study was designed to evaluate the growth parameters using smart greenhouse monitoring system designed with Raspberry-Pi microprocessor and sensors to control the microclimate (temperature and humidity) of a prototype greenhouse. A set of experiment was designed, one in a smart greenhouse system and the 2nd in the conventional greenhouse system to evaluate the growth parameters of eggplant. In a microclimate of smart greenhouse the temperature and humidity was set controlled using two sensors and automation system to control the mist spray and heating/cooling system inside the prototype greenhouse. Standard production technology was adopted in both the experiments and the experiment was replicated thrice. It was observed that the smart greenhouse monitoring system maintained the microclimate inside the prototype greenhouse ultimately effect the growth and yield parameters. The results predicted a progressive increase in growth parameter upto 10-20% in plant height, flowers per plant, fruits per plant and weight of fruit in automated greenhouse using microcontroller. Similarly quality of fruit was significantly affected as maximum fruit diameter 35 mm and fruit firmness 6.9 libre was recorded that was significantly higher than the fruit in the conventional greenhouse. The over average yield of eggplant per plant was recorded 5.6 kg/plant in automated greenhouse while 4 kg/plant fruit yield was recorded in conventional greenhouse that was significantly higher. The findings of current study predicted that the overall yield of eggplant was significantly higher and the growth and quality parameters were also higher in automated greenhouse using microcontroller and can be used for the potential eggplant production in urban agriculture.

Macronutrient Applications and Irrigation Regimes Impact Weed Dynamics and Weed Seedbank Augmentation in Solanum melongena L. Fields

Weeds are a major yield-limiting factor bedeviling eggplant (Solanum melongena L.) production in Russia. This study aimed to determine the influence of macronutrient rates and drip irrigation regimes on weed flora composition and potential soil contamination by weed seedbanks in the eggplant field. Three field experiments were conducted during the 2019–2021 cropping calendar. Two-factorial field experiments were designed in four blocks whereby the composition of weed flora in eggplants was examined under the influence of different macronutrient rates (40 tons manure and N140P30, 40 tons manure and N320P120K210, and control without fertilization), and three thresholds of pre-irrigation soil moisture % least moisture capacity (LMC) (in particular, 70, 80 and 90% LMC). The results demonstrated that nutrient rates contributed to a significant increase in weed density of 27.1 to 37.6%, due to an increase in the number of annual weeds (annual winter weeds and annual early spring weeds), and an increase in soil moisture threshold from 70 to 90%. Nevertheless, low moisture availability between the rows as a result of drip irrigation utilization led to a decrease in weed populations by 10.8 to 15.9%. Potential contamination of the arable soil layer with weed seed was desirably decreased, ranging from 19.8 to 21.7% with the application of fertilizers, compared with the control. Furthermore, the soil weed seedbank was considerably reduced by an increase in the pre-irrigation threshold of soil moisture.

Rhizophagus irregularis and Azotobacter chroococcum Uphold Eggplant Production and Quality under Low Fertilization

Microorganisms are essential parts of soil and play an important role in mediating many processes and influencing plant health. Arbuscular mycorrhizal fungi (AMF) and nitrogen-fixing bacteria (NFB), the most common of such microorganisms, can benefit plants by enhancing the nutrient-absorbing ability of roots through bio-inoculation, also called biofertilization. Different methods have been tested and proven to be effective in the enhancement of soil nutrient availability. However, the effects of increased application of biological methods with minimal chemical fertilizers are still inconsistent. In this 2-year of fixed-point greenhouse test, we aimed to evaluate the impact of AMF (Rhizophagus irregularis) and/or NFB (Azotobacter) on growth, quality, and yield of eggplants under different N levels. Data showed that biofertilizer application with reduced chemical fertilizer had the highest impact on eggplant performance and yield. Indeed, low chemical fertilizers combined with adequate amounts of biofertilizers produced a higher plant height, length and width of leaves, dry matter, number of fruits per plant with better morphology, total yield per plant, and total soluble solids (TSS), suggesting that the use of Azotobacter and R. irregularis as biofertilizers could substantially reduce the use of chemical fertilizers without impairing the quality and yield of eggplant.

Effect of Boron Fertilizer and of Potassium Fertilizer on Growth and Production of Purple Eggplant (Solanum Melongena L.)

This study aims to determine the response of boron and potassium fertilizers on the growth and production of purple eggplant (Solanum melongena L.). The research was conducted in the village of Jiken, Kec. Tulang, Sidoarjo Regency and continued in the microbiology and biotechnology laboratory of the Muhammadiyah University of Sidoarjo. Starting from February to May 2020. The experiment was arranged factorially using a randomized block design followed by the 5% BNJ test consisting of 2 factors. The first factor is boron fertilizer with levels of 0 kg/ha, 6 kg/ha and 12 kg/ha. The second factor was potassium fertilizer which consisted of 3 treatment doses, namely 50 kg/ha, 100 kg/ha and 150 kg/ha. The variables observed were plant height, leaf area, number of leaves, number of fruits, fruit weight, fruit length, fruit sweetness,antioxidant levels. The results showed that there was no significant interaction in each treatment, this is because boron fertilizer decreased at the last observation in the study. While the antioxidan test in this study used free radical damping method with DPPH with wavelength of 517 nm using spectrophotometer.

Efficiency of Integrated Nutrient Management to Improve Eggplant Production in Intercropping Systems

Efficiency of Integrated Nutrient Management to Improve Eggplant Production in Intercropping Systems

Estimation of eggplant yield with machine learning methods using spectral vegetation indices

Estimation of crop yields included in the planning is an essential condition for accurate and timely agricultural planning. Remotely sensed products, such as the spectral vegetation index (VI), are widely used in estimation of crop yields. The integration of remotely sensed data into machine learning methods will have the potential to develop a real-time management system specific to the area of interest. The main aim of the study was to determine the eggplant yield in field conditions, based on VIs obtained from a handheld spectroradiometer, using five different machine learning methods (artificial neural networks (ANN), support vector machines (SVR), k nearest neighbor (kNN), random forests (RF), and Adaptive boosting (AB)), and compare the performances of the methods. The data used in the study were obtained in field experiments focusing on determining the most suitable irrigation program for eggplant production in a semi-humid climate region in northern Turkey during 2015, 2016 and 2017 growing seasons. Irrigation treatments consisted of a total of five applications, which were full water application (I1:100 %) and different deficit ration of full water application (I2:I1x 75 %, I3: I1x50%, I4:I1x25% and I5: rainfed based). Input variables used in yield estimation models were determined by correlation analysis and principal components analysis (PCA). The inputs in the models were different combinations of 10 different VIs, the number of days after planting (DAP) and water application coefficients. In addition, an alternative approach was proposed, in which PCA components were used as input for yield estimation. All machine learning models using PCA-based inputs were estimated with higher accuracy than other input combinations. The best results were obtained with the ANN model based on PCA-based inputs; therefore, this model was chosen for eggplant yield estimation (coefficient of determination (R2) = 0.973, mean absolute error (MAE) = 274.816 kg ha−1, root mean square error (RMSE) = 352.787 kg ha−1 and Nash–Sutcliffe efficiency (NSE) = 0.951). The lowest accuracy for yield estimation was recorded in RF model. The prediction accuracy of the models using a single VI as input was low. Green index (GI) and green vegetation index (GVI) had the highest impact on eggplant yield, and eggplant yield was estimated with higher accuracy with these indices, which are sensitive to chlorophyll absorption. The findings of the current study demonstrate the benefits of using remotely sensed data and PCA together in machine learning models to more reliably and accurately estimate eggplant yield at regional scale.

Sequential application of bio-pesticides suppresses eggplant shoot and fruit borer, Leucinodes orbonalis Guenee infestation

Different bio-pesticides were evaluated against eggplant shoot and fruit borer, Leucinodes orbonalis G. in combination. All combination of bio-pesticides were effective against eggplant shoot and fruit borer but Lycomax + Biotin M + Antario and Lycomax + Biotin M + Fytomax 3% found most potent and control 88.43 and 84.06 percent shoot infestation; 69.67 and 66.44 percent fruit infestation by count; 72.70 and 70.49 percent fruit infestation by weight, respectively. Lycomax + Biotin M + Antario and Lycomax + Fytomax 0.1% + Biomax increased 32.90 and 28.66 percent gross yield; 120.19 and 87.5 percent marketable yield, respectively over control. Individual fruit weight found maximum from Lycomax + Fytomax 0.1% + Biomax and Biotin M + Antario where it was 51.74 g and 48.13 g for marketable fruit while 44.05 g and 44.61 g for infested fruit. The present study revealed that Lycomax + Biotin M + Antario and Lycomax + Biotin M + Fytomax 3% effectively control ESFB while Lycomax + Biotin M + Antario and Lycomax + Fytomax 0.1% + Biomax increases the yield. Therefore, application of Lycomax + Biotin M + Antario might be recommended for successful production of eggplant to get maximum yield with minimum infestation.

PENGARUH PEMBERIAN KOMPOS AMPAS TAHU DAN PUPUK NPK TERHADAP PERTUMBUHAN DAN PRODUKSI TANAMAN TERUNG UNGU (Solanum melongena L.)

This research aimed to examine the effective interaction of tofu waste compost and NPK fertilizer to determine the best doses which give the growth and highest production of purple eggplant. The research was conducted at Experimental Farm, Faculty of Agriculture, Riau University, Pekanbaru. The research was conducted for 5 months, from February to June 2020. The research was experimentally arranged in a 3x3 factorial using a completely randomized design (CRD). The first factor was the tofu waste compost consisting of 3 levels (0, 10, and 20 tons.ha-1). The second factor was the NPK fertilizer (0, 100, and 150 kg.ha-1) which consists of nine treatments combination. The observed parameters were the height of the plant, the days of flowering, the days of harvesting, the fruit length, the fruit diameter, the number of fruits per plant, the fruit weight per fruit, the fruit weight per plant, and the fruit weight with the plot. The data in this research was analyzed using variance and followed by Duncan's multiple distance test at a 5% level. The results showed that tofu waste compost and NPK fertilizer increased the growth of eggplant such as the height of the plant, the days of flowering, the days of harvesting, the number of fruits per plant, the fruit length, the fruit weight per fruit, the fruit weight per plant and the fruit weight with plot and does not increase fruit diameter. The giving tofu waste compost at a dose of 20 tons.ha-1 and NPK fertilizer 150 kg.ha-1 gave the best eggplant growth and production until the plants were 90 DAP.

The Differential Effects of Tuta absoluta Infestations on the Physiological Processes and Growth of Tomato, Potato, and Eggplant.

Simple SummaryOur study aimed to assess how Tuta absoluta affects different Solanaceae plant species. It was observed that susceptible plants experience diminished growth and reproduction rates, which may be a result of a physiological malfunction. Infestation by T. absoluta caused 100% crop loss to tomato plants, whereas significant yield reduction was observed for potato plants, and no significant feeding effect was observed for eggplant. The affected plants also experienced physiological impairments. This study is essential in that it demonstrates the differential risk of T. absoluta infestations on the production of the tested Solanaceae plant species.Tuta absoluta (Meyrick, 1917) (Lepidoptera: Gelechiidae) is a destructive insect pest toward crops and belongs to the Solanaceae family. Since it was first recorded in South Africa in 2016, the pest has spread extensively and caused tremendous damage to field and tunnel-grown tomato crops. This study aimed to investigate how T. absoluta affects the growth and physiology of three Solanaceae plant species: tomato, potato, and eggplant. These three crops were infested with L1 instar larvae, and their growth and physiology were assessed during insect feeding. The damage to the infested tomato host plant was severe, with T. absoluta destroying 100% of the plants. The tomato plants were distorted 15 days after infestation, that is, before the fruit set. For potato, the defoliation was moderate, but the infested plants produced fewer tubers compared to the uninfested host plants. Eggplant had fewer visible signs of feeding, resulting in no significant difference between the infested and uninfested host plants in terms of growth and physiological functions. Infested tomato and potato plants had stagnant growth, fewer and damaged leaves, a reduced chlorophyll content, a reduced photosynthesis rate, a poor transpiration rate, poor water conductance, and poor intercellular carbon dioxide concentrations. This study closes the knowledge gap on the morphological (growth) and physiological responses of different Solanaceae species to T. absoluta infestation, and it also demonstrates the differential risk of T. absoluta infestations in the production of tomato, potato, and eggplant.

Using amendment derived from vermicompost combined with calcium and magnesium mineral to achieve safe production of eggplant and its microbial ecological effect in Cd-contaminated soil

Using amendment derived from vermicompost combined with calcium and magnesium mineral to achieve safe production of eggplant and its microbial ecological effect in Cd-contaminated soil

First report of Anthracnose on 'Purple Dream' Solanum melongena in Malaysia Caused by Colletotrichum siamense.

'Purple Dream' eggplant (Solanum melongena) is widely grown for its edible fruits in Malaysia. In July 2021, anthracnose symptoms were observed on fruit with a disease severity of approximately 80% and an incidence of 10% in a field (14.6 m2) (5°56'50.9"N, 116°04'31.9"E) located in the Penampang district of Sabah province. The symptoms initially appeared as irregular light brown spots. As the disease progressed, the spots enlarged and merged into extensive lesion patches that appeared in concentric circles. The symptomatic fruit tissues (5 x 5 mm) were surface sterilized based on Khoo et al. (2022), and plated onto potato dextrose agar (PDA), and incubated at 25°C in the dark. Colonies with gray-white fluffy mycelia developed after 7 days, and the reverse of the colonies was dark brown. A representative isolate named Penampang was characterized morphologically and molecularly. The conidia were one-celled, cylindrical, blunt at the ends, hyaline, smooth, and measured 13.3 to 16.1 x 3.9 to 6.0 µm (n= 20). Appressoria ranged in size from 7.6 to 9.3 m x 5.5 to 6.6 µm (n= 20) and were spherical to irregular in shape and dark brown in colour. Genomic DNA was extracted from fresh mycelia of isolate Penampang based on Khoo et al. (2021) and Khoo et al. (2022). ITS1/ITS4, CL1C/CL2C, ACT-512F/ACT-783R, CHS-79F/CHS-354R, and GDF1/GDR1 primer pairs were used to amplify the isolate's internal transcribed spacer region (ITS), and partial calmodulin (CAL), actin (ACT), chitin synthase (CHS-1), and glyceraldehyde-3-phosphate dehydrogenase genes (GAPDH) (Weir et al. 2012). PCR products were sequenced by Apical Scientific Sdn. Bhd. (Selangor, Malaysia). Sequences were deposited in GenBank under the accession numbers OL957466 (ITS), OL953035 (CAL), OL953032 (ACT), OL953038 (CHS-1), and OL953041 (GAPDH). They were 99% to 100% identical to the Colletotrichum ti ITS (NR_120143) (515 bp out of 519 bp), and C. siamense CAL (JX009714) (729 bp out of 731 bp), ACT (JX009518) (282 bp out of 282 bp), CHS-1 (JX009865) (299 bp out of 299 bp), and GAPDH (JX009924) (276 bp out of 277 bp) sequences. ITS sequences do not reliably resolve relationships within the C. gloeosporioides complex (Weir et al. 2012). The phylogenetic maximum likelihood analysis using the combined ITS, CAL, ACT, CHS-1, and GAPDH sequences indicated that the isolate was part of the C. siamense clade (100% bootstrap value) that also contained the type isolate ICMP 18578 of this species. Morphological and molecular characterization matched the description of C. siamense (Huang et al. 2021; Ismail et al. 2021). Koch's postulates were performed similarly as described by Chai et al. (2017) but using spray-inoculation (108 spores/ml) of three healthy 'Purple Dream' eggplant fruit with isolate Penampang. Water was sprayed on three additional fruits that served as controls. All the fruits were incubated at 25°C and less than 90% relative humidity. Symptoms similar to those observed in the field developed 5 days after inoculation. No symptoms occurred on controls. The experiment was repeated two more times. The reisolated fungi were identical to the pathogen morphologically and molecularly. To our knowledge, this is the first report of C. siamense causing anthracnose on fruit of 'Purple Dream' S. melongena in Malaysia as well as worldwide. Our findings expand the host range of C. siamense and indicate that the pathogen could potentially limit 'Purple Dream' eggplant production in Malaysia.

Diversified crop rotation improves continuous monocropping eggplant production by altering the soil microbial community and biochemical properties

Diversified crop rotation improves continuous monocropping eggplant production by altering the soil microbial community and biochemical properties

PENGARUH DOSIS PUPUK KCI TERHADAP PERTUMBUHAN DAN PRODUKSI TANAMAN TERUNG (Solanum melongena L.)

The use of KCl fertilizer in plant cultivation can improve soil fertility. KCl fertilizer can increase the growth and production of eggplant, both in quality and quantity. The purpose of this study was to determine the effect of the dose of KCl fertilizer on the growth and production of eggplant. This study is a one-factor trial using a completely randomized design (CRD). The factor tested was the dose of KCl fertilizer which consisted of 6 levels, namely: without KCl fertilizer (D0), 25 grams/plant (D1), 50 grams/plant (D2), 75 grams/plant (D3), 100 grams/plant (D4), 125 grams/plant (D5). Each treatment was replicated 4 times, and each replication consisted of 2 plants. The observation variables in this study were plant height, number of leaves, leaf area, number of fruits per plant, fruit length per plant, wet weight, and dry weight of the plant. Observations of plant height and number of leaves were carried out when the eggplant plants were 14 DAP with an interval of 7 days until the vegetative growth ended. The treatment dose of KCl fertilizer had a significant effect on the growth and production of eggplant plants. Dosage of KCl 125 gr/plant resulted in the best growth seen in plant height and a higher number of leaves, respectively 88.00 cm and 37.00 fruit. The highest eggplant production at the dose treatment KCl fertilizer 125 g/plant seen in the number of fruit, fruit length, wet weight, and dry weight of fruit per plant each of 7 pieces; 19.92 cm; 1,152.97 grams and 228.04 grams.

Influence of Arbuscular Mycorrhizal Fungi on Physiology and Yield of Eggplant in Organic Soilless Production System

Recent studies suggest that arbuscular mycorrhizal fungi (AMF) have the potential to improve the growth and yield of eggplant (Solanum melongena L.) under soil-based organic production systems. However, the application of AMF in organic soilless vegetable production in a greenhouse has not been well studied, creating an important knowledge gap. Therefore, two greenhouse experiments [Experiment 1 (E1) and Experiment 2 (E2)] were conducted to investigate the effect of AMF (Glomus spp.) on the growth, gaseous exchange, and yield of eggplant fertilized with various liquid organic fertilizers (OFs) and inorganic fertilizers (IFs) in a soilless greenhouse production system. The experiment was conducted in a split-plot design with four replications in which liquid OFs [OF1 (5N–1P–1K), OF2 (0N–5P–5K and 3N–3P–3K), OF3 (3N–1P–1K), OF4 (5N–1P–2K), OF5 (3.7N–2.7P–3.7K), and OF6 (3N–3P–5K)], and IFs [IF1 (6N–4P–4K) and IF2 (4N–0P–1K and 1N–3P–5K)] were randomized as main plot factor, and AMF [inoculated and uninoculated (control)] as a subplot factor. Results indicate that AMF inoculation had no significant effect on the growth, gaseous exchange, and yield parameters of eggplant. Among different OFs, the eggplant fertilized with OF6 resulted in a 4.3% and 3% reduction of leaf area compared with top-performing IF1 treatment in E1 and E2, respectively. Further, the OF6 treatment resulted in a 12% and 15% reduction in total yield per plant compared with IF1 in E1 and E2, respectively. The differences in plant gaseous exchange parameters were also nonsignificant for eggplants fertilized with different OF and IF treatments in both E1 and E2. These results conclude that Glomus spp. were not associated with a significant increase in the yield of eggplant in the soilless production system. However, OFs were performing similar to IFs in terms of growth and yield, which could be due to a higher nutrient availability of these OFs, which are highly useful for the production of eggplant in greenhouse soilless production systems.

Molecular characters of parasitic nematode (Hemicycliophora typica) associated with eggplant (Solanum melongena) using 28S rDNA from regions of South Africa

Solanum melongena is the sixth most important vegetable worldwide. In recent years, eggplant production has been increasing. Therefore, study about plant diseases in this plant is important. One of the most important diseases in eggplant is plant-parasitic nematodes. Therefore, this molecular study was conducted in 2021 at the University of Limpopo to identify the plant-parasitic nematodes identified from South African soil causing yield loss in eggplant. The recovered nematode was extracted using the tray method, and then its DNA was extracted using the Chelex method. Afterward, 28S rDNA was amplified using specific primers to identify the nematode. The Nblast analysis based on the large subunit ribosomal DNA showed 99% similarity with a population of Hemicycliophora typica (KF430515) from South Africa. In addition, phylogenetic analysis using the maximum likelihood method as implemented in mega x software was done. The phylogenetic analysis put the South African populations of H. typica together with other H. typica with a 100-bootstrap value. In conclusion, the results showed that 28S could detect the H. typica, and therefore the species is verified by the molecular method. Also, the ecological behavior of the H. typica in terms of the economic impact on the eggplant needs to be investigated.

Characterization of Corynespora cassiicola causing leaf spot and fruit rot in eggplant (Solanum melongena L.)

Diseases are important limiting factors in profitable eggplant production. Identifying correctly the causative agent of disease and reporting new emerging pathogens are critical steps in a successful disease management program. The study was conducted to identify the causative agents of a leaf spot and fruit rot in eggplant using combined morphological, cultural, pathogenicity and molecular approaches. Three fungal isolates were obtained from diseased leaf and fruit samples. All three isolates were pathogenic to detached fruits and leaves and on leaves of potted plants at seven days post-inoculation. The same fungi were re-isolated from the inoculated leaves and fruits and thus, establishing Koch’s postulates. The DNA sequence of the partial sequence of the internal transcribed spacer regions of the three isolates showed 100% similarity to Corynespora cassiicola. This is the first record of C. cassiicola as an eggplant leafspot pathogen in the Philippines and a new record for the fungus as a fruit rot pathogen. With limited knowledge available, fruit rot caused by C. cassiicola may negatively affect potential fruit yield in the field and the quality of marketable fruits. Screening for disease resistance would be worthwhile.

Safety assessment and sustainability of consuming eggplant (Solanum melongena L.) grown in wastewater-contaminated agricultural soils

Vegetables cultivated on contaminated agricultural soils are being consumed by the public, and consequently cause serious health concerns due to contaminants' dietary intake. The current study examines the safety and sustainability of eating eggplant (Solanum melongena) by looking into the possibility of heavy metals translocation from polluted soils to the edible sections, as well as the health hazards that come with it. Soil and eggplant samples were taken from three contaminated and other three uncontaminated farms to estimate their chemical constituents and plant growth properties. Based on the pollution load index data, the contaminated soils were highly polluted with Fe, Cu, Pb, and Zn; and relatively polluted with Cr, Mn, Cd, Mn, Co, and V. Under contamination stress, the fresh biomass, dry biomass, and production of eggplant were significantly reduced by 41.2, 44.6, and 52.1%, respectively. Likewise, chlorophyll a and b were significantly reduced from 1.51 to 0.69 mg g−1 and 1.36 to 0.64 mg g−1, respectively. The uncontaminated plant shoots had the highest quantities of N, P, and proteins (1.98, 2.08, and 12.40%, respectively), while the roots of the same plants had the highest K content (44.70 mg kg−1). Because eggplant maintained most tested heavy elements (excluding Zn and Pb) in the root, it is a good candidate for these metals' phytostabilization. However, it had the potential to translocate Mn and Zn to its shoot and Pb, Cr, Mn, and Zn to the edible fruits indicating its possibility to be a phytoextractor and accumulator of these metals. Cd, Cu, Ni, Pb, Mn, and Co quantity in the edible sections of eggplant grown in contaminated soils exceeded the permissible level for normal plants, posing health hazards to adults and children. For safety issues and food sustainability, our investigation strongly recommends avoiding, possibly, the cultivation of eggplant in contaminated agricultural lands due to their toxic effects even in the long run.

Synergism of Industrial and Agricultural Waste as a Suitable Carrier Material for Developing Potential Biofertilizer for Sustainable Agricultural Production of Eggplant

The study investigates biochar from agriculture waste and flyash from coal power station as possible carrier materials for two plant growth-promoting (PGP) bacterial strains Burkholderia sp. L2 and Bacillus sp. A30 for enhanced eggplant growth and yield. Biochar-based biofertilizers with/without flyash showed higher viability up to 270 days of storage period. The maximum percentage of seed germination was observed in L2-based biochar and flyash + biochar (1:1) bifertilizer. Moreover, the L2 + biochar+flyash produced a maximum percentage increase in fruit yield with significant (p < 0.05) improvement in plant growth parameters. Post-harvest soil status also showed enhanced physical (water holding capacity, moisture content), chemical (pH, electrical conductivity, NPK), and dehydrogenase activity. The study suggests that biofertilizer of L2 strain with agriculture waste generated biochar and flyash as carrier materials can tremendously enhance the productivity of eggplant and could act as a substitute for chemical fertilizer thus solving their disposal problem by sustainable waste management.

The complete chloroplast genome of Solanum sisymbriifolium (Solanaceae), the wild eggplant

Solanum sisymbriifolium is a critical wild eggplant resource with resistance to many serious diseases that affect eggplant production. In this study, the chloroplast genome of S. sisymbriifolium was successfully sequenced using Illumina high-throughput sequencing technology. The length of the complete chloroplast genome is 155,771 bp, and its GC content is 37.76%. There is a large single-copy region (86,404 bp), a small single-copy region (18,525 bp), and a pair of inverted repeat regions (25,421 bp) in the chloroplast genome. A total of 128 coding genes were annotated in the entire chloroplast genome, including 83 protein-coding genes, 37 transfer RNA genes and eight ribosomal RNA genes. The phylogenetic tree of 17 complete chloroplast genomes shows that S. sisymbriifolium is closely related to Solanum wrightii.