A characterization of community fish refuge typologies in rice field fisheries ecosystems

In rural Cambodia, fish is a source of food and income to millions of people. However, there has been a real threat to fish populations in natural wetlands due to the degradation of aquatic biodiversity and habitat, illegal fishing, increase of population and demand for fish, and the use of harmful pesticides for agriculture. The Rice Field Fisheries Enhancement Project (RFFEP) seeks to rebuild and protect the fish populations through innovative methods. The project works with communities to sustainably strengthen the rice field fisheries near their villages by improving protected habitats called "community fish refuges". This handbook characterizes rice field fisheries that are connected to community fish refuges. Community fish refuges are designated fish conservation areas promoted by the Fisheries Administration of the Royal Cambodian Government. It also examines the characteristics of rain-fed rice field ecosystems that are connected to community fish refuges in order to further refine descriptive criteria and better understand potential benefits and management strategies.

The potential of community fish refuges (CFRs) in rice field agro-ecosystems for improving food and nutrition security in the Tonle Sap region

The fisheries sector in Cambodia contributes 8%–12% to national GDP and 25% - 30% to agricultural GDP, with an estimated 4.5 million people involved in fishing and associated trades. Fish and other aquatic animals are important food sources, contributing an estimated national average of 60% - 70% of total animal protein intake. Of the 2013 total fish production, 550,000 metric tons were harvested from freshwater habitats, of which rice field fisheries and small-scale family fisheries contributed approximately 20%. The productivity and value of rice field fisheries to households in rural Cambodia has been highlighted in a number of previous studies. The Fisheries Administration of the Ministry of Agriculture, Forestry and Fisheries plans to increase productivity from rice field fisheries and aquaculture at an annual rate of 15% to maintain supply for a growing population. This report draws mainly on the baseline and monitoring data from the Rice Field Fisheries Enhancement Project (RFFEP) during its implementation between 2012 and 2014. Reference is also made to the Fish on Farms project to highlight the relative contribution of fish from small-scale aquaculture compared to wild-caught fish.

Use of drought response index for identification of drought tolerant genotypes in rainfed lowland rice

Drought is a major constraint for rice production in the rainfed lowlands in Southeast Asia and Eastern India. The breeding programs for tainted lowland rice in these regions focus on adaptation to a range of drought conditions. However, a method of selection of drought tolerant genotypes has not been established and is considered to be one of the constraints faced by rice breeders. Drought response index (DRI) is based on grain yield adjusted for variation in potential yield and flowering date, and has been used recently, but its consistency among drought environments and hence its usefulness is not certain. In order to establish a selection method and subsequently to identify donor parents for drought resistance breeding, a series of experiments with 15 contrasting genotypes was conducted under well-watered and managed drought conditions at two sites for 5 years in Cambodia. Water level in the field was recorded and used to estimate the relative water level (WLREL) around flowering as an index of the severity of water deficit at the time of flowering for each entry. This was used to determine if DRI or yield reduction was due to drought tolerance or related to the amount of available water at flowering, i.e. drought escape. Grain yield reduction due to drought ranged from 12 to 46%. The drought occurred mainly during the reproductive phase, while four experiments had water stress from the early vegetative stage. There was significant variation for water availability around flowering among the nine experiments and this was associated with variation in mean yield reduction. Genotypic variation in DRI was consistent among most experiments, and genotypic mean DRI ranged from -0.54 to 0.47 (LSD 5% = 0.47). Genotypic variation in DRI was not related to WLREL around flowering in the nine environments. It is concluded that selection for DRI under drought conditions would allow breeders to identify donor lines with high drought tolerance as an important component of breeding better adapted varieties for the rainfed lowlands; two genotypes were identified with high DRI and low yield reduction and were subsequently used in the breeding program in Cambodia. (c) 2006 Elsevier B.V. All rights reserved.

Grain yield of direct seeded and transplanted rice in rainfed lowlands of South East Asia

The mean grain yield of 81 direct seeded (DS) and 91 transplanted (TP) environments that were conducted as part of 3 ACIAR projects over 11 years, from 1992-2002, in Laos, Thailand and Cambodia were examined. The average yield of TP rice was 6% greater than DS rice. A subset of 27 pairs of DS and TP environments was examined and results indicated a significant positive correlation between the DS and TP establishment methods for mean grain yield with only a 3% difference in overall performance. The performance of 3 genotypes in 3 locations in Laos in 1996 was also examined. Results indicated a highly significant positive correlation between the performance of genotypes in DS and TP experiments in which TP rice had a 30% yield advantage over DS rice. This particular experiment highlights the need for good management practices when DS establishment methods are utilised. Results of this paper indicate that DS and TP rice will produce a similar yield for a given environment provided that they are grown utilising good management practices.

Rice-Infecting Pseudomonas Genomes Are Highly Accessorized and Harbor Multiple Putative Virulence Mechanisms to Cause Sheath Brown Rot

Sheath rot complex and seed discoloration in rice involve a number of pathogenic bacteria that cannot be associated with distinctive symptoms. These pathogens can easily travel on asymptomatic seeds and therefore represent a threat to rice cropping systems. Among the rice-infecting Pseudomonas, P. fuscovaginae has been associated with sheath brown rot disease in several rice growing areas around the world. The appearance of a similar Pseudomonas population, which here we named P. fuscovaginae-like, represents a perfect opportunity to understand common genomic features that can explain the infection mechanism in rice. We showed that the novel population is indeed closely related to P. fuscovaginae. A comparative genomics approach on eight rice-infecting Pseudomonas revealed heterogeneous genomes and a high number of strain-specific genes. The genomes of P. fuscovaginae-like harbor four secretion systems (Type I, II, III, and VI) and other important pathogenicity machinery that could probably facilitate rice colonization. We identified 123 core secreted proteins, most of which have strong signatures of positive selection suggesting functional adaptation. Transcript accumulation of putative pathogenicity-related genes during rice colonization revealed a concerted virulence mechanism. The study suggests that rice-infecting Pseudomonas causing sheath brown rot are intrinsically diverse and maintain a variable set of metabolic capabilities as a potential strategy to occupy a range of environments.

Intelligent prognostics of machinery health utilising suspended condition monitoring data

The ability to forecast machinery failure is vital to reducing maintenance costs, operation downtime and safety hazards. Recent advances in condition monitoring technologies have given rise to a number of prognostic models for forecasting machinery health based on condition data. Although these models have aided the advancement of the discipline, they have made only a limited contribution to developing an effective machinery health prognostic system. The literature review indicates that there is not yet a prognostic model that directly models and fully utilises suspended condition histories (which are very common in practice since organisations rarely allow their assets to run to failure); that effectively integrates population characteristics into prognostics for longer-range prediction in a probabilistic sense; which deduces the non-linear relationship between measured condition data and actual asset health; and which involves minimal assumptions and requirements. This work presents a novel approach to addressing the above-mentioned challenges. The proposed model consists of a feed-forward neural network, the training targets of which are asset survival probabilities estimated using a variation of the Kaplan-Meier estimator and a degradation-based failure probability density estimator. The adapted Kaplan-Meier estimator is able to model the actual survival status of individual failed units and estimate the survival probability of individual suspended units. The degradation-based failure probability density estimator, on the other hand, extracts population characteristics and computes conditional reliability from available condition histories instead of from reliability data. The estimated survival probability and the relevant condition histories are respectively presented as “training target” and “training input” to the neural network. The trained network is capable of estimating the future survival curve of a unit when a series of condition indices are inputted. Although the concept proposed may be applied to the prognosis of various machine components, rolling element bearings were chosen as the research object because rolling element bearing failure is one of the foremost causes of machinery breakdowns. Computer simulated and industry case study data were used to compare the prognostic performance of the proposed model and four control models, namely: two feed-forward neural networks with the same training function and structure as the proposed model, but neglected suspended histories; a time series prediction recurrent neural network; and a traditional Weibull distribution model. The results support the assertion that the proposed model performs better than the other four models and that it produces adaptive prediction outputs with useful representation of survival probabilities. This work presents a compelling concept for non-parametric data-driven prognosis, and for utilising available asset condition information more fully and accurately. It demonstrates that machinery health can indeed be forecasted. The proposed prognostic technique, together with ongoing advances in sensors and data-fusion techniques, and increasingly comprehensive databases of asset condition data, holds the promise for increased asset availability, maintenance cost effectiveness, operational safety and – ultimately – organisation competitiveness.

Genetic Analysis of Tolerance to Rice Tungro Bacilliform Virus in Rice (Oryza sativa L.) Through Agroinoculation

Balimau Putih [an Indonesian cultivar tolerant to rice tungro bacilliform virus (RTBV)] was crossed with IR64 (RTBV, susceptible variety) to produce the three filial generations F1, F2 and F3. Agroinoculation was used to introduce RTBV into the test plants. RTBV tolerance was based on the RTBV level in plants by analysis of coat protein using enzyme-linked immunosorbent assay. The level of RTBV in cv. Balimau Putih was significantly lower than that of IR64 and the susceptible control, Taichung Native 1. Mean RTBV levels of the F1, F2 and F3 populations were comparable with one another and with the average of the parents. Results indicate that there was no dominance and an additive gene action may control the expression of tolerance to RTBV. Tolerance based on the level of RTBV coat protein was highly heritable (0.67) as estimated using the mean values of F3 lines, suggesting that selection for tolerance to RTBV can be performed in the early selfing generations using the technique employed in this study. The RTBV level had a negative correlation with plant height, but positive relationship with disease index value

Changes in Level of Virus Accumulation and Incidence of Infection are Critical in the Characterization of Rice Tungro Bacilliform Virus (RTBV) Resistance in Rice

Analysis by enzyme-linked immunosorbent assay showed that Rice tungro bacilliform virus (RTBV) accumulated in a cyclic pattern from early to late stages of infection in tungro-susceptible variety, Taichung Native 1 (TN1), and resistant variety, Balimau Putih, singly infected with RTBV or co-infected with RTBV+Rice tungro spherical virus (RTSV). These changes in virus accumulation resulted in differences in RTBV levels and incidence of infection. The virus levels were expressed relative to those of the susceptible variety and the incidence of infection was assessed at different weeks after inoculation. At a particular time point, RTBV levels in TN1 or Balimau Putih singly infected with RTBV were not significantly different from the virus level in plants co-infected with RTBV+RTSV. The relative RTBV levels in Balimau Putih either singly infected with RTBV or co-infected with RTBV+RTSV were significantly lower than those in TN1. The incidence of RTBV infection varied at different times in Balimau Putih but not in TN1, and to determine the actual infection, the number of plants that became infected at least once anytime during the 4wk observation period was considered. Considering the changes in RTBV accumulation, new parameters for analyzing RTBV resistance were established. Based on these parameters, Balimau Putih was characterized having resistance to virus accumulation although the actual incidence of infection was >75%.