Drought Resistance Improvement in Rice: An Integrated Genetic and Resource Management Strategy

Abstract

Drought is the major constraint to rice production in rainfed areas across Asia and sub-Saharan Africa. In the context of current and predicted water scarcity, increasing irrigation is generally not a viable option for alleviating drought problems in rainfed rice-growing systems. It is therefore critical that genetic management strategies for drought focus on maximum extraction of available soil moisture and its efficient use in crop establishment and growth to maximize biomass and yield. Extensive genetic variation for drought resistance exists in rice germplasm. However, the current challenge is to decipher the complexities of drought resistance in rice and exploit all available genetic resources to produce rice varieties combining drought adaptation with high yield potential, quality, and resistance to biotic stresses. The strategy described here aims at developing a pipeline for elite breeding lines and hybrids that can be integrated with efficient management practices and delivered to rice farmers. This involves the development of high-throughput, high-precision phenotyping systems to allow genes for yield components under stress to be efficiently mapped and their effects assessed on a range of drought-related traits, and then moving the most promising genes into widely grown rice mega-varieties, while scaling up gene detection and delivery for use in marker-aided breeding.     

Photoperiodic effect on flowering and seed development in quinoa (Chenopodium quinoa Willd.)

Abstract

Sensitivity to photoperiod in quinoa (Chenopodium quinoa Willd.) was studied under controlled conditions to enhance crop adaptation to environments outside its centre of origin. Two varieties, a traditional variety from Bolivia (Real), which will not mature under Danish conditions, and an early maturing variety (Q52), developed for Danish climatic conditions, were used in this reciprocal transfer experiment. Plants were moved from a short daylength of 10 h (SD) to a long daylength of 18 h (LD) and vice versa at set intervals from sowing to 100 days after sowing (DAS). A reaction of LD in time to flowering was observed only in the Bolivian variety Real. Under SD both varieties flowered after 39 DAS. For Real the LD regime resulted in a moderate increase in time to flowering to 44 DAS. The non-sensitive, juvenile period in Real was estimated to be approximately 16 days. In Q52 a moderate increase in the number of leaves was formed on the main stem after flowering at LD, which indicates that some daylength sensitivity remains. The most striking difference occurred during seed filling, when going from SD to LD. In Q52 the time from the end of flowering to maturity increased from 39 to 52 days. Under SD, Real had a seed-filling period similar to Q52, but at LD Real remained with green leaves during seed filling. Hard seed was observed in the still green perigonium 57 days after end of flowering. At this moment re-shooting occurred from the inflorescence, and seed maturity was not reached at the termination of the experiment at 150 DAS. This study shows that flower induction is not a major problem for adaptation of quinoa to North European conditions but that a very strong, daylength sensitive, stay green reaction is the main cause of the late maturity of South American introductions.     

Impact analysis of climate data aggregation at different spatial scales on simulated net primary productivity for croplands

For spatial crop and agro-systems modelling, there is often a discrepancy between the scale of measured driving data and the target resolution. Spatial data aggregation is often necessary, which can introduce additional uncertainty into the simulation results. Previous studies have shown that climate data aggregation has little effect on simulation of phenological stages, but effects on net primary production (NPP) might still be expected through changing the length of the growing season and the period of grain filling. This study investigates the impact of spatial climate data aggregation on NPP simulation results, applying eleven different models for the same study region (∼34,000 km²), situated in Western Germany. To isolate effects of climate, soil data and management were assumed to be constant over the entire study area and over the entire study period of 29 years. Two crops, winter wheat and silage maize, were tested as monocultures. Compared to the impact of climate data aggregation on yield, the effect on NPP is in a similar range, but is slightly lower, with only small impacts on averages over the entire simulation period and study region. Maximum differences between the five scales in the range of 1–100 km grid cells show changes of 0.4–7.8% and 0.0–4.8% for wheat and maize, respectively, whereas the simulated potential NPP averages of the models show a wide range (1.9–4.2 g C m⁻² d⁻¹ and 2.7–6.1 g C m⁻² d⁻¹ for wheat and maize, respectively). The impact of the spatial aggregation was also tested for shorter time periods, to see if impacts over shorter periods attenuate over longer periods. The results show larger impacts for single years (up to 9.4% for wheat and up to 13.6% for maize). An analysis of extreme weather conditions shows an aggregation effect in vulnerability up to 12.8% and 15.5% between the different resolutions for wheat and maize, respectively. Simulations of NPP averages over larger areas (e.g. regional scale) and longer time periods (several years) are relatively insensitive to climate data aggregation. However, the scale of climate data is more relevant for impacts on annual averages of NPP or if the period is strongly affected or dominated by drought stress. There should be an awareness of the greater uncertainty for the NPP values in these situations if data are not available at high resolution. On the other hand, the results suggest that there is no need to simulate at high resolution for long term regional NPP averages based on the simplified assumptions (soil and management constant in time and space) used in this study.     

Reduced tillage in temperate organic farming: implications for crop management and forage production

To promote conservation tillage in organic farming systems, weed control and ley removal within arable-ley rotations need to be optimized. A long-term field trial was thus established in Frick, Switzerland in 2002 on a clayey soil and with a mean precipitation of 1000 mm/year. The tillage experiment distinguished between conventional tillage with mouldboard ploughing (CT, 15 cm depth) and reduced tillage (RT), including a chisel plough (15 cm) and a stubble cleaner (5 cm). Results of a 2-year grass-clover ley (2006/2007) and silage maize (2008) are presented. Due to dry conditions, mean grass-clover yields were 25% higher in RT than in CT, indicating better water retention of RT soils. Clover cover and mineral contents of the fodder mixture were also higher in RT. The ley was successfully removed in autumn 2007 in RT plots, and a winter pea catch crop was sown before maize. In CT, ploughing took place in spring 2008. Maize yields were 34% higher in RT than in CT, despite a two- to three-fold higher but still tolerable weed infestation. Maize in RT plots benefited from an additional 61.5 kg of easily decomposable organic N/ha incorporated into the soil via the pea mulch. Measurement of arbuscular mycorrhizal colonization of maize roots indicated a similar mechanical disturbance of the topsoil through the reduced ley removal system compared with ploughing. It is suggested that RT is applicable in organic farming, even in arable-ley rotations, but long-term effects need further assessment.     

The density dilemma: limitations on juvenile production in threatened salmon populations

Density‐dependent processes have repeatedly been shown to have a central role in salmonid population dynamics, but are often assumed to be negligible for populations at low abundances relative to historical records. Density dependence has been observed in overall spring/summer Snake River Chinook salmon Oncorhynchus tshawytscha production, but it is not clear how patterns observed at the aggregate level relate to individual populations within the basin. We used a Bayesian hierarchical modelling approach to explore the degree of density dependence in juvenile production for nine Idaho populations. Our results indicate that density dependence is ubiquitous, although its strength varies between populations. We also investigated the processes driving the population‐level pattern and found density‐dependent growth and mortality present for both common life‐history strategies, but no evidence of density‐dependent movement. Overwinter mortality, spatial clustering of redds and limited resource availability were identified as potentially important limiting factors contributing to density dependence. The ubiquity of density dependence for these threatened populations is alarming as stability at present low abundance levels suggests recovery may be difficult without major changes. We conclude that density dependence at the population level is common and must be considered in demographic analysis and management.     

2012年成县小麦歉收的成因分析及应对措施

从光、热、水等气候要素及耕作理念和田间管理等方面分析了2012年成县冬小麦歉收的气候成因和人为因素,并据此提出相应的应对措施,为今后小麦生产提供科学依据。     

变时相生长模型技术及其在小班数据更新中的应用

小班数据更新是地方森林资源监测和资源档案管理的需要，实现它的必要条件是建立小班动态数据库和建立小班数据更新模型。本文着重对后者的现实林分建模中每年变化的大量的部分，采伐的问题处理，根据微变化调整原理，提出变时相生长模型技术，从而消除了误差逐年积累和放大的问题，提高了小班数据更新的可靠性。     

Tracing Pb Pollution Penetration in Temperate Podzols

We combine high‐resolution soil sampling with lead (Pb) analyses (concentrations and stable isotopes) in two temperate podzols, together with previous data obtained with selective Al and Fe dissolution techniques. We aim to assess how atmospheric Pb is incorporated into the soils during pedogenesis. Partial least squares modelling for Pb concentrations shows that the podzolization process has the largest effect on Pb concentration (80·3% of the variance). The proportion of inorganic secondary compounds, the input of fresh organic matter from the soil surface and the relative abundance of Fe versus Al are responsible for a small part of the Pb concentration variance. Lead isotopic composition (²⁰⁶Pb/²⁰⁷Pb ratios) depends on soil organic matter content either fresh/poorly humified (57·3% of the variance) or humified (24·7% of the variance). The Pb linked to inorganic compounds and the overall podzolization process play a minor role in isotopic signature (5·3 and 3·7% of the variance respectively). Soil pH appears to be the controlling variable of the different transport and retention mechanisms. The relatively low isotopic ratios observed in spodic horizons result from geogenic Pb released through the preferential dissolution of the isotopically distinct most weatherable minerals of the parent material in the eluvial horizons, which undergoes downward mobilization. An accurate knowledge of soil reactive components and formation mechanisms is essential to a correct diagnose of the scope of Pb pollution and a more effective design of remediation strategies. Copyright © 2017 John Wiley & Sons, Ltd.     

Predictive models of weed population dynamics

Many of the challenges faced by weed ecologists can be met only by the capability to predict the responses of weed populations to changes in their environment or management. In spite of this, a review of papers published in Weed Research suggests that weed ecologists are remarkably reluctant to produce detailed, quantitative predictions. This may result from uncertainty in the accuracy of predictions and indeed, a variety of reasons have been put forward to suggest that the potential utility of weed models may be limited in this regard. In this study, we review the applications to which weed models have been put. Focusing on predictive population modelling, we highlight several limitations that can lead to failures of this approach and we discuss the likely prospects for weed population modelling. We make three points regarding the future of weed modelling. First, owing to prohibitive data requirements, the development of highly mechanistic models that attempt to make detailed predictions of weed population numbers is unlikely to be very successful. Second, data collection for developing weed models needs to be rethought. Weed models are most commonly compromised by a lack of spatial and temporal replication, preventing modellers from measuring parameter variability and error effectively and limiting assessments of model uncertainty. Finally, the utility of models needs to be better appreciated; models are key tools in making long range predictions of how management will affect weed populations, but, we estimate, they are used in only a small fraction of studies. Without the further development of models for weed population dynamics, our ability to predict long-term dynamics will be restricted.     

Modelling the introduction and transmission of Campylobacter in a North American chicken flock

Campylobacter is the second leading cause of foodborne illness in the United States. Although many food production animals carry Campylobacter as commensal bacteria, consumption of poultry is the main source of human infection. Previous research suggests that the biology of Campylobacter results in complete flock colonization within days. However, a recent systematic review found that the on-farm prevalence of Campylobacter varies widely, with some flocks reporting low prevalence. We hypothesized that the low prevalence of Campylobacter in some flocks may be driven by a delayed introduction of the pathogen. The objectives of this study were to (a) develop a deterministic compartmental model that represents the biology of Campylobacter, (b) identify the parameter values that best represent the natural history of the pathogen in poultry flocks and (c) examine the possibility that a delayed introduction of the pathogen is sufficient to replicate the observed low prevalence examples documented in the literature. A deterministic compartmental model was developed to examine the dynamics of Campylobacter in chicken flocks over a 56-day time period prior to movement to the abattoir. The model outcome of interest was the final population prevalence of Campylobacter at day 56. The resulting model that incorporated a high transmission rate (β = 1.04) was able to reproduce the wide range of prevalence estimates observed in the literature when pathogen introduction time is varied. Overall, we established that the on-farm transmission rate of Campylobacter in chickens is likely high and can result in complete colonization of a flock when introduced early. However, delaying the time at which the pathogen enters the flock can reduce the prevalence observed at 56 days. These results highlight the importance of enforcing strict biosecurity measures to prevent or delay the introduction of the bacteria to a flock.