The subterranean termite Globitermus sulphureus is an important Southeast Asian pest with limited genomic resources that causes damages to agriculture crops and building structures. Therefore, the main goal of this study was to survey the G. sulphureus transcriptome composition. Here, we performed de novo transcriptome for G. sulphureus workers' heads using Illumina HiSeq paired-end sequencing technology. A total of 88, 639, 408 clean reads were collected and assembled into 243, 057 transcripts and 193, 344 putative genes. The transcripts were annotated with the Trinotate pipeline. In total, 27, 061 transcripts were successfully annotated using BLASTX against the SwissProt database and 17, 816 genes were assigned to 47, 598 GO terms. We classified 14, 223 transcripts into COG classification, resulting in 25 groups of functional annotations. Next, a total of 12, 194 genes were matched in the KEGG pathway and 392 metabolic pathways were predicted based on the annotation. Moreover, we detected two endogenous cellulases in the sequences. The RT-qPCR analysis showed that there were significant differences in the expression levels of two genes β-glucosidase and endo-β-1,4-glucanase between worker and soldier heads of G. sulphureus. This is the first study to characterize the complete head transcriptome of a higher termite G. sulphureus using a high-throughput sequencing. Our study may provide an overview and comprehensive molecular resource for comparative studies of the transcriptomics and genomics of termites.
Improper use of urea may cause environmental pollution through NH3 volatilization and NO3 (-) leaching from urea. Clinoptilolite zeolite and compost could be used to control N loss from urea by controlling NH4 (+) and NO3 (-) release from urea. Soil incubation and leaching experiments were conducted to determine the effects of clinoptilolite zeolite and compost on controlling NH4 (+) and NO3 (-) losses from urea. Bekenu Series soil (Typic Paleudults) was incubated for 30, 60, and 90 days. A soil leaching experiment was conducted for 30 days. Urea amended with clinoptilolite zeolite and compost significantly reduced NH4 (+) and NO3 (-) release from urea (soil incubation study) compared with urea alone, thus reducing leaching of these ions. Ammonium and NO3 (-) leaching losses during the 30 days of the leaching experiment were highest in urea alone compared with urea with clinoptilolite zeolite and compost treatments. At 30 days of the leaching experiment, NH4 (+) retention in soil with urea amended with clinoptilolite zeolite and compost was better than that with urea alone. These observations were because of the high pH, CEC, and other chemical properties of clinoptilolite zeolite and compost. Urea can be amended with clinoptilolite zeolite and compost to improve NH4 (+) and NO3 (-) release from urea.
Efficient management of P fertilizers ensures good yield of crops and adequate food supply. In the acid soil of the tropics, soluble P is fixed by Al and Fe. Exploitation of the high CEC and pH of Clinoptilolite zeolite (CZ) could mitigate low soil pH and P fixation in acid soils. This study was undertaken to determine the effects of amending a weathered acid soil with CZ on: (i) soil P availability and other related soil chemical properties, and (ii) nutrient concentration, nutrient uptake, above-ground biomass, agronomic efficiency, and yield of Zea mays L. on a tropical acidic soil. Triple superphosphate (TSP), Egypt Rock phosphate (ERP), and Christmas Island Rock phosphate (CIRP) were used as P sources. The treatments evaluated were: (i) soil alone, (ii) 100% recommended fertilizer rate (NPK), and (iii) 75% fertilizer rate + Clinoptilolite zeolite. Selected soil chemical properties and P availability were determined before and after field trials. Zea mays L. above-ground biomass, nutrient concentration, nutrient uptake, agronomic efficiency, and fresh cob yield were also determined. Results revealed that the effects of treatments with and without CZ treatments on soil pH, P fractions, soil acidity, dry matter production, yield of maize, nutrient uptake, and agronomic efficiency were similar. Hence, suggesting CZ inclusion in the fertilization program of Zea mays L is beneficial in terms of reducing excessive or unbalanced use of chemical fertilizers due to reduction of fertilizers usage by 25%.
Drought is one of the commonly occurring environmental stresses, limiting crop production in many countries. Selection
of cultivar is the most effective and economical means for alleviating the adverse effects of drought stress on crops. The
present study aimed to investigate the growth, some physiological processes, yield and quality of some newly-developed
wheat cultivars (AARI-2011, AAS-2011, Faisalabad-2008, Millat-2011 and Punjab-2011) under field drought stress
conditions. The cultivars were sown in a field under normal irrigation and drought-induced conditions. Maximum net
photosynthetic rate was recorded in cv. AAS-2011 at growth stage of 67 days after wheat emergence under normal irrigation
and cv. Faisalabad-2008 at 67 days after wheat emergence under drought condition. Leaf stomatal conductance and
transpiration rate were maximum in cv. Faisalabad-2008 under drought conditions. The adverse effects of drought stress
were observed more on cv. Millat-2011 than Faisalabad-2008, with respect to net photosynthetic rate and transpiration.
Drought exerted a significant adverse effect on leaf stomatal conductance at 74 days after wheat emergence which was
recorded as 230 mmol m-2 s-1. Among the cultivars, AAS-2011 recorded maximum yield traits and grain yield under normal
irrigation condition and Faisalabad-2008 under drought condition. Cultivar Millat-2011 was the most susceptible to
drought and Faisalabad-2008 the most resistant to drought. Faisalabad-2008 maintained the quality at the most under
drought stress conditions. It is concluded that Fasialabad-2008 should be grown under field drought conditions to achieve
maximal yield and quality of wheat.
The objective of this research is to examine the impact of bioenergy usage on health outcomes, especially adult mortality in both developed and underdeveloped countries in the European Union, where the use of solid biomass is growing to generate bioheat, biocool, and biopower. Over the period studied, findings indicate that increased consumption of bioenergy has increased mortality rates in developed and underdeveloped EU28 countries during the period 1990-2018. This feedback proposes, using generalized least squares (GLS), that the resulting death rate from burning biomass-related cases is higher in the EU15 developed countries compared to EU13 underdeveloped countries. There is a need to lower burning biomass in the entire EU15 countries, more importantly its developed region, by critically evaluating the bioenergy production life cycle before it is available for final consumption. However, there is a continuous need to intensify stringent production procedures in the bioenergy industry in EU15 countries, more importantly the imported biomass crops for energy use. There is also a need to be consistent with the campaign on the usage of bioenergy products, i.e., bioheat, bioelectricity, and biofuels, particularly in the rural areas where the use of wood fuels for cooking, heating, and cooling are significant in EU15 developed countries in comparison to EU13 developing countries.
Clustered regularly interspaced short palindromic repeat (CRISPR) and Cas9-associated protein systems provide a powerful genetic manipulation tool that can drive plant research forward. Nuclease-dead Cas9 (dCas9) is an enzymatically inactive mutant of Cas9 in which its endonuclease activity is non-functional. The applications of CRISPR/dCas9 have expanded and diversified in recent years. Originally, dCas9 was used as a CRISPR/Cas9 re-engineering tool that enables targeted expression of any gene or multiple genes through recruitment of transcriptional effector domains without introducing irreversible DNA-damaging mutations. Subsequent applications have made use of its ability to recruit modifying enzymes and reporter proteins to DNA target sites. In this paper, the most recent progress in the applications of CRISPR/dCas9 in plants, which include gene activation and repression, epigenome editing, modulation of chromatin topology, live-cell chromatin imaging and DNA-free genetic modification, will be reviewed. The associated strategies for exploiting the CRISPR/dCas9 system for crop improvement with a dimer of the future of the CRISPR/dCas9 system in the functional genomics of crops and the development of traits will be briefly discussed.
Banana (Musaceae) is one of the world's most important fruit crops that is widely cultivated in tropical countries for its valuable applications in food industry. Its enormous by-products are an excellent source of highly valuable raw materials for other industries by recycling agricultural waste. This prevents an ultimate loss of huge amount of untapped biomass and environmental issues. This review discusses extensively the breakthrough in the utilization of banana by-products such as peels, leaves, pseudostem, stalk and inflorescence in various food and non-food applications serving as thickening agent, coloring and flavor, alternative source for macro and micronutrients, nutraceuticals, livestock feed, natural fibers, and sources of natural bioactive compounds and bio-fertilizers. Future prospects and challenges are the important key factors discussed in association to the sustainability and feasibility of utilizing these by-products. It is important that all available by-products be turned into highly commercial outputs in order to sustain this renewable resource and provide additional income to small scale farming industries without compromising its quality and safety in competing with other commercial products.
While droughts and floods have intensified in recent years, only a handful of studies have assessed their impacts on croplands and production in Southeast Asia. Here, we used the Google Earth Engine to assess the droughts and floods and their impacts on croplands and crop production over 40 years from 1980 to 2019. Using the Palmer Drought Severity Index (PDSI) as the basis for determining the drought and flood levels, and crop damage levels, crop production loss in both the Monsoon Climate Region (MCR) and the Equatorial Climate Region (ECR) of Southeast Asia was assessed over 47,192 grid points with 10 × 10-kilometer resolution. We found that rainfed crops were severely affected by droughts in the MCR and floods in the ECR. About 9.42 million ha and 3.72 million ha of cropland was damaged by droughts and floods, respectively. We estimated a total loss of 20.64 million tons of crop production between 2015 and 2019. Rainfed crops in Thailand, Cambodia, and Myanmar were strongly affected by droughts, whereas Indonesia, the Philippines, and Malaysia were more affected by floods over the same period. Accordingly, four levels of policy interventions were prioritized by considering the geolocated crop damage levels.
Identification of plant variety and cultivar is pivotal in the agricultural sector due to the abundance of plant varieties and cultivars developed in many crop species. However, plant variety and cultivar identification via basic morphological features is problematic and challenging when differentiating closely related species not only due to their limited differences but also due to technical limitations of the process being time-consuming, labour-intensive and costly, and statistically imprecise information being available due to phenotypic plasticity. Therefore, it is imperative to have rapid and highly efficient techniques to mitigate these limitations. This review provides an overview and summarization of the development and application of molecular markers such as Random Amplified Polymorphic DNA (RAPD), Restriction Fragment Length Polymorphism (RFLP), Simple Sequence Repeats (SSR), Inter-simple sequence repeats (ISSR), Amplified Fragment Length Polymorphism (AFLP), Single nucleotide polymorphism (SNP) and DNA barcoding, High-resolution melting (HRM) and biosensor technology as potential tools in the identification of plant variety and cultivar.
Pesticides are widely employed in rice crops since the ecosystem and surroundings of paddy promote insects, weeds, and fungal and bacterial pathogens. Each commonly utilised pesticide possesses different uses. For instance, fungicides control fungal issues, herbicides curb weed growth, and insecticides destroy and repel insects. Although several ways to categorise them exist, pesticides are typically classified according to their chemical compositions. Rice production remains one of the most dominant crops grown in most Southeast Asian countries as it is a staple food. Nonetheless, the crop is highly dependent on pesticides, leading to growing concerns over the potential adverse effects of pesticides on the environment and human health. Despite the availability of numerous studies on the subject, a comprehensive understanding of the specific effects of pesticides on paddy fields in Southeast Asia is still lacking. Consequently, reviewing existing knowledge is necessary for synthesising and identifying research gaps to better inform policymakers, farmers, and other stakeholders in the agricultural sector. The objectives of the present review paper were to review the interactions between pesticides and the environment by understanding the physical and chemical properties of the chemicals, compare pesticide transportation modes in air, water, and soil and how they affect the environment, and evaluate and discuss the effects of pesticides on non-targeted organisms. This study assessed pesticide innovation reported between 1945 and 2021 for a better understanding of the utilisation of the chemicals over time. The pesticides assessed in this study were classified based on their chemical compounds, such as organochlorines, organophosphates, carbamates, and pyrethroid. This review could provide a comprehensive understanding of the interactions between pesticides and the environment and their impacts on non-targeted organisms.
Nitrogen (N) fertilizer is an important yield limiting factor for sunflower production. The correlation between yield components and growth parameters of three sunflower hybrids (Hysun-33, Hysun-38, Pioneer-64A93) were studied with five N rates (0, 60, 120, 180, 240 kg ha(-1)) at three different experimental sites during the two consecutive growing seasons 2008 and 2009. The results revealed that total dry matter (TDM) production and grain yield were positively and linearly associated with leaf area index (LAI), leaf area duration (LAD), and crop growth rate (CGR) at all three sites of the experiments. The significant association of yield with growth components indicated that the humid climate was most suitable for sunflower production. Furthermore, the association of these components can be successfully used to predict the grain yield under diverse climatic conditions. The application of N at increased rate of 180 kg ha(-1) resulted in maximum yield as compared to standard rate (120 kg ha(-1)) at all the experimental sites. In this way, N application rate was significantly correlated with growth and development of sunflower under a variety of climatic conditions. Keeping in view such relationship, the N dose can be optimized for sunflower crop in a particular region to maximize the productivity. Multilocation trails help to predict the input rates precisely while taking climatic variations into account also. In the long run, results of this study provides basis for sustainable sunflower production under changing climate.
Agricultural development in the tropics lags behind development in the
temperate latitudes due to the lack of advanced technology, and various biotic and abiotic
factors. To cope with the increasing demand for food and other plant-based products,
improved crop varieties have to be developed. To breed improved varieties, a better
understanding of crop genetics is necessary. With the advent of next-generation DNA
sequencing technologies, many important crop genomes have been sequenced. Primary
importance has been given to food crops, including cereals, tuber crops, vegetables, and
fruits. The DNA sequence information is extremely valuable for identifying key genes
controlling important agronomic traits and for identifying genetic variability among the
cultivars. However, massive DNA re-sequencing and gene expression studies have to be
performed to substantially improve our understanding of crop genetics. Application of the
knowledge obtained from the genomes, transcriptomes, expression studies, and
epigenetic studies would enable the development of improved varieties and may lead to a
second green revolution. The applications of next generation DNA sequencing
technologies in crop improvement, its limitations, future prospects, and the features of
important crop genome projects are reviewed herein.
Climate change is likely to worsen the food security situation through its impact on food production, which may indirectly affect fertility behaviour. This study examines the direct and indirect effects of climate change (e.g., temperature and precipitation) via the production of major crops, as well as their short- and long-term effects on the total fertility rate (TFR) in Bangladesh. We used structural equation modelling (SEM) to perform path analysis and distinguish the direct influence of climate change on fertility and its indirect influence on fertility through food security. We also applied the error correction model (ECM) to analyze the time-series data on temperature and precipitation, crop production and fertility rate of Bangladesh from 1966 to 2015. The results show that maximum temperature has a direct effect and indirect negative effect-via crop production-on TFR, while crop production has a direct positive effect and indirect negative effect-via infant mortality-on TFR. In the short term, TFR responds negatively to the maximum temperature but positively in the long term. The effect of rainfall on TFR is found to be direct, positive, but mainly short-term. Although indicators of economic development play an important part in the fertility decline in Bangladesh, some climate change parameters and crop production are non-negligible factors.
Matched MeSH terms: Crops, Agricultural/growth & development
Banana is one of the most important food crops after rice, wheat and corn around the world. It is susceptible to a wide spectrum of non-infectious problems such as abiotic stresses resulting in restricting growth and production. Studies were conducted to determine the effects of four salinity levels (0.17 (control), 3.0, 6.0, and 9.0 dS m-1) on morphological characteristics of four banana cultivars at vegetative growth stage. Banana cultivars from the Cavendish group (Williams, Malindi) and plantains group (FHIA18 and Diwan) were grown in 61 x 76 cm polyethylene bags filled with soil mixture comprising of top soil, sand and peat moss (3:1:2 v/v), with pH ranging from 6 - 6.5 and EC 0.02 mScm-1. The experiment was carried out under a rain-shelter in split-plot design with three replicates. Plants were irrigated manually. Data were collected at 3, 6 and 9 months after transplanting. The results revealed that, the number of leaves, stem height, stem girth and total leaf area were significantly affected by salinity, variety and plant age. Significant interaction was also found between salinity and variety, salinity and plant age, as well as variety and plant age. The morphological characteristics of banana were negatively affected by higher salinity levels (6.0 and 9.0 dS m-1). Under similar salinity level, cultivar Malindi had higher number of leaves, stem height, stem girth and total leaf area as compared to cultivar Williams. Among plantains banana, cultivar FHIA18 was more tolerance to high salinity levels than Diwan cultivar, while Malindi from Cavendish group shows high salt tolerant than Williams. Therefore cultivars Malindi and FHIA18 could be grown in arid and semiarid environment depend on their tolerance to high salinity level above 1.0 dS m-1.
This study accounts for the Hicks neutral technical change in a calibrated model of climate analysis, to identify the optimum level of technical change for addressing climate changes. It demonstrates the reduction to crop damages, the costs to technical change, and the net gains for the adoption of technical change for a climate-sensitive Pakistan economy. The calibrated model assesses the net gains of technical change for the overall economy and at the agriculture-specific level. The study finds that the gains of technical change are overwhelmingly higher than the costs across the agriculture subsectors. The gains and costs following technical change differ substantially for different crops. More importantly, the study finds a cost-effective optimal level of technical change that potentially reduces crop damages to a minimum possible level. The study therefore contends that the climate policy for Pakistan should consider the role of technical change in addressing climate impacts on the agriculture sector.
This paper gives a projection of the possible damage of climate change on the agriculture sector of Pakistan for the period 2012-2037, based on a dynamic approach, using an environment-related applied computable general equilibrium model (CGE). Climate damage projections depict an upward trend for the period of review and are found to be higher than the global average. Further, the damage to the agricultural sector exceeds that for the overall economy. By sector, climatic damage disproportionately affects the major and minor crops, livestock and fisheries. The largest losses following climate change, relative to the other agricultural sectors, are expected for livestock. The reason for this is the orthodox system of production for livestock, with a low adaptability to negative shocks of climate change. Overall, the findings reveal the high exposure of the agriculture sector to climate damage. In this regard, policymakers in Pakistan should take seriously the effects of climate change on agriculture and consider suitable technology to mitigate those damages.
Growing plants in the gulf region can be challenging as it is mostly desert, and the climate is dry. A few species of plants have the capability to grow in such a climate. However, those plants are not suitable as a food source. The aim of this work is to design and construct an indoor automatic vertical hydroponic system that does not depend on the outside climate. The designed system is capable to grow common type of crops that can be used as a food source inside homes without the need of large space. The design of the system was made after studying different types of vertical hydroponic systems in terms of price, power consumption and suitability to be built as an indoor automated system. A microcontroller was working as a brain of the system, which communicates with different types of sensors to control all the system parameters and to minimize the human intervention. An open internet of things (IoT) platform was used to store and display the system parameters and graphical interface for remote access. The designed system is capable of maintaining healthy growing parameters for the plants with minimal input from the user. The functionality of the overall system was confirmed by evaluating the response from individual system components and monitoring them in the IoT platform. The system was consuming 120.59 and 230.59 kWh respectively without and with air conditioning control during peak summer, which is equivalent to the system running cost of 13.26 and 25.36 Qatari Riyal (QAR) respectively. This system was circulating around 104 k gallons of nutrient solution monthly however, only 8-10 L water was consumed by the system. This system offers real-time notifications to alert the hydroponic system user when the conditions are not favorable. So, the user can monitor several parameters without using laboratory instruments, which will allow to control the entire system remotely. Moreover, the system also provides a wide range of information, which could be essential for plant researchers and provides a greater understanding of how the key parameters of hydroponic system correlate with plant growth. The proposed platform can be used both for quantitatively optimizing the setup of the indoor farming and for automating some of the most labor-intensive maintenance activities. Moreover, such a monitoring system can also potentially be used for high-level decision making, once enough data will be collected. This work presents significant opportunities for the people who live in the gulf region to produce food as per their requirements.
Combining ability analysis provides useful information for the selection of parents, also information regarding the nature and magnitude of involved gene actions. Crops improvement involves strategies for enhancing yield potentiality and quality components. Targeting the improvement of respective characters in bitter gourd, combining ability and genetic parameters for 19 characters were estimated from a 6×6 full diallel analysis technique. The results revealed that the variances due to general combining ability (GCA) and specific combining ability (SCA) were highly significant for most of the important characters. It indicated the importance of both additive and non-additive gene actions. GCA variances were higher in magnitude than SCA variances for all the characters studied indicating the predominance of the additive gene effects in their inheritance. The parent P2 (BG 009) appeared as the best general combiner for earliness; P1 (BG 006) for number of fruits, average single fruit weight and fruit yield; P4 (BG 027) for node number of first female flower and days to seed fruit maturity; P3 (BG 011) for fruit length and thickness of the fruit flesh; P5 (BG 033) for 100-seed weight; and P6 for number of nodes per main vine. The SCA effect as well as reciprocal effect was also significant for most of the important characters in different crosses.
Deep learning (DL) represents the golden era in the machine learning (ML) domain, and it has gradually become the leading approach in many fields. It is currently playing a vital role in the early detection and classification of plant diseases. The use of ML techniques in this field is viewed as having brought considerable improvement in cultivation productivity sectors, particularly with the recent emergence of DL, which seems to have increased accuracy levels. Recently, many DL architectures have been implemented accompanying visualisation techniques that are essential for determining symptoms and classifying plant diseases. This review investigates and analyses the most recent methods, developed over three years leading up to 2020, for training, augmentation, feature fusion and extraction, recognising and counting crops, and detecting plant diseases, including how these methods can be harnessed to feed deep classifiers and their effects on classifier accuracy.
The inexorable exposure of plants to the combinations of abiotic stresses has affected the worldwide food supply. The crop improvement against these abiotic stresses has been captivating approach to increase the yield and enhance the stress tolerance. By using traditional and modern breeding methods, the characters that confer tolerance to these stresses were accomplished. No doubt genetic engineering and molecular breeding have helped in comprehending the intricate nature of stress response. Understanding of abiotic stress-involved cellular pathways provides vital information on such responses. On the other hand, genomic research for crop improvement has raised new assessments in breeding new varieties against abiotic stresses. Interpretation of responses of the crop plants under stress is of great significance by studying the main role of crops in food and biofuel production. This review presents genomic-based approaches revealing the complex networks controlling the mechanisms of abiotic stress tolerance, and the possible modes of assimilating information attained by genomic-based approaches due to the advancement in isolation and functional analysis of genes controlling the yield and abiotic stress tolerance are discussed.