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We studied bacterial blomass and production in 3 t~d a l creeks (Isaro, Gharo and Ph~ttl Creeks) in the mangrove forests in the Indus R~ver delta, Pakistan, to assess the signif~cance of bacteria-mediated carbon fluxes in the creek ecosystem. Bacterial biomass, bacterial carbon production (BCP) and primary productivity (PP) were measured periodically for over a year during 1991-92. BCP was high, generally 50 to 300 pg C 1-' d-l. Despite such high BCP, bacterial abundance remained between 1 X 106 ml-' and 4 X 106 ml-' (20 to 80 p g C I-') indicating tight coupling between bacter~al production and removal. Specific growth rates generally ranged from 1 to 7 d.' but the rate reached 24 d.' during a phytoplankton bloom, apparently a red tide, and this was an unprecedented growth rate for a natural assemblage The abundance of attached bacteria exhlblted a large variation, ranglng from 4 to 9 2 % (mean 35 2 21 ",,, n = 41) in Isaro Creek and from 14 to 84 "L. (mean 37 -t 28%,, n = 10) in Gharo Creek Bacterial production due to attached bacteria was 73 to 96'Y" of the total Thus, a major fract~on of BCP may have been directly ava~lablc to m.etazoan grazers. BCP was generally much higher than net PP, the yearly integrated average BCP/13P for all sites was 2.0. Thus, the growth of bacteria, attached and free, probably represented the major pathway of the production of high quality (low C:N) biomass potentially available to the grazers. Average yearly integrated bacterial carbon demand (BCD), estimated conservatively by assuming a 30-0 growth efficiency for all sites, was 6.9 times net PP. Thus, the creek water columns were strongly and persistently net heterotrophic. Data integrated over the entire study period show that even if all phytoplankton production was utilized by bacteria it would satisfy only 7 to 20':0 of the BC:D; the remaining 80 to 93% of BCD would be met by reduced carbon from other sources. Phytoplankton production was l~g h t limited due to high turbidity and, apparently, the majority of BCP could be supported by the input of mangrove detritus. Estimates of utilizable dissolved organic carbon (UDOC) in selected samples were 97 to 656 pg C I-', indicating that In order to sustain the measured BCD (643 + 671 pg C I-' d-') the UDOC pool would turnover in < l d to a few days. Limited data suggest that bacterial production was carbon rather than N or P limited. consistent w~t h sustained high levels of Inorganic N and P in the surface water. Since mangrove detr~tus provides most of the energy for bacterial production, which in turn is a significant source of high quality lood for grazers, particularly via ingestion of attached bacteria, w e predict that the ongoing destruction of mangrove forests in the Indus delta and elsewhere could have a major impact on mangrove ecosystem structure and functioning and the production of economically important flsh and shrimp in mangrove creeks.

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Machine learning (ML) offers new technologies in the precision agriculture domain with its intelligent algorithms and strong computation. Oil palm is one of the rich crops that is also emerging with modern technologies to meet global sustainability standards. This article presents a comprehensive review of research dedicated to the application of ML in the oil palm agricultural industry over the last decade (2011–2020). A systematic review was structured to answer seven predefined research questions by analysing 61 papers after applying exclusion criteria. The works analysed were categorized into two main groups: (1) regression analysis used to predict fruit yield, harvest time, oil yield, and seasonal impacts and (2) classification techniques to classify trees, fruit, disease levels, canopy, and land. Based on defined research questions, investigation of the reviewed literature included yearly distribution and geographical distribution of articles, highly adopted algorithms, input data, used features, and model performance evaluation criteria. Detailed quantitative–qualitative investigations have revealed that ML is still underutilised for predictive analysis of oil palm. However, smart systems integrated with machine vision and artificial intelligence are evolving to reform oil palm agri-business. This article offers an opportunity to understand the significance of ML in the oil palm agricultural industry and provides a roadmap for future research in this domain.

BackgroundMethylation at C-5 (5-mdC) of CpG base pairs, the most abundant epigenetic modification of DNA, is catalyzed by 3 essential DNA methyltransferases (Dnmt1, Dnmt3a and Dnmt3b). Aberrations in DNA methylation and Dnmts are linked to different diseases including cancer. However, their role in alcoholic liver disease (ALD) has not been elucidated.Methodology/Principal FindingsDnmt1 wild type (Dnmt1 +/+) and hypomorphic (Dnmt1 N/+) male mice that express reduced level of Dnmt1 were fed Lieber-DeCarli liquid diet containing ethanol for 6 weeks. Control mice were pair-fed calorie-matched alcohol-free liquid diet, and Dnmtase activity, 5-mdC content, gene expression profile and liver histopathology were evaluated. Ethanol feeding caused pronounced decrease in hepatic Dnmtase activity in Dnmt1 +/+ mice due to decrease in Dnmt1 and Dnmt3b protein levels and upregulation of miR-148 and miR-152 that target both Dnmt1 and Dnmt3b. Microarray and qPCR analysis showed that the genes involved in lipid, xenobiotic and glutathione metabolism, mitochondrial function and cell proliferation were dysregulated in the wild type mice fed alcohol. Surprisingly, Dnmt1 N/+ mice were less susceptible to alcoholic steatosis compared to Dnmt1 +/+ mice. Expression of several key genes involved in alcohol (Aldh3b1), lipid (Ppara, Lepr, Vldlr, Agpat9) and xenobiotic (Cyp39a1) metabolism, and oxidative stress (Mt-1, Fmo3) were significantly (P<0.05) altered in Dnmt1 N/+ mice relative to the wild type mice fed alcohol diet. However, CpG islands encompassing the promoter regions of Agpat9, Lepr, Mt1 and Ppara were methylation-free in both genotypes irrespective of the diet, suggesting that promoter methylation does not regulate their expression. Similarly, 5-mdC content of the liver genome, as measured by LC-MS/MS analysis, was not affected by alcohol diet in the wild type or hypomorphic mice.Conclusions/SignificanceAlthough feeding alcohol diet reduced Dnmtase activity, the loss of one copy of Dnmt1 protected mice from alcoholic hepatosteatosis by dysregulating genes involved in lipid metabolism and oxidative stress.

Pakistan is well known for its basmati rice with long grain and aroma, as well as for non-basmati indica varieties; however average yield is lower as compared with other countries. Besides, cultural practices, the main reason for low productivity in Pakistan is that, local varieties are susceptible to different biotic and abiotic factors like insect pests, diseases, drought, and salinity. Different approaches have been undertaken in Pakistan to tackle these problems through traditional breeding of selection and crossing, mutation breeding, somaclonal variation as well as plant transformation studies in recent past. For variety development, the most successful examples arose from traditional breeding that produced famous basmati varieties like Basmati 370, Basmati 385 and Super basmati, and nonbasmati varieties such as IRRI-6, DR-82, DR-83, DR-92, Swat-I and Swat-II, which earn a significant share of foreign exchange every year. Six varieties have also been developed through mutation breeding, and one through exploitation of somaclonal variation but their contribution to the national economy is not significant. On the other hand, no variety has been registered as commercial by plant transformation groups. This review discusses the problems and prospects of rice breeding with special emphasis on basmati rice in Pakistan particularly in Pakistani Punjab (a major producing area), as well as focuses on future research programs.

This study investigates the potential application of Stateflow (SF) to design an energy management strategy (EMS) for a renewable-based hybrid energy system (HES). The SF is an extended finite state machine; it provides a platform to design, model, and execute complex event-driven systems using an interactive graphical environment. The HES comprises photovoltaics (PV), energy storage units (ESU) and a diesel generator (Gen), integrated with the power grid that experiences a regular load shedding condition (scheduled power outages). The EMS optimizes the energy production and utilization during both modes of HES operation, i.e., grid-connected mode and the islanded mode. For islanded operation mode, a resilient power delivery is ensured when the system is subjected to intermittent renewable supply and grid vulnerability. The contributions of this paper are twofold: first is to propose an integrated framework of HES to address the problem of load shedding, and second is to design and implement a resilient EMS in the SF environment. The validation of the proposed EMS demonstrates its feasibility to serve the load for various operating scenarios. The latter include operations under seasonal variation, abnormal weather conditions, and different load shedding patterns. The simulation results reveal that the proposed EMS not only ensures uninterrupted power supply during load shedding but also reduces grid burden by maximizing the use of PV energy. In addition, the SF-based adopted methodology is envisaged to be a useful alternative to the popular design method using the conventional software tools, particularly for event-driven systems.

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