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Weed presence altered biotic stress and light signaling in maize even when weeds were removed early in the critical weed-free period.
ABSTRACT: Weed presence early in the life cycle of maize (typically, from emergence through the 8 to 12 leaf growth stage) can reduce crop growth and yield and is known as the critical weed-free period (CWFP). Even if weeds are removed during or just after the CWFP, crop growth and yield often are not recoverable. We compared transcriptome responses of field-grown hybrid maize at V8 in two consecutive years among plants grown under weed-free and two weed-stressed conditions (weeds removed at V4 or present through V8) using RNAseq analysis techniques. Compared with weed-free plant responses, physiological differences at V8 were identified in all weed-stressed plants and were most often associated with altered photosynthetic processes, hormone signaling, nitrogen use and transport, and biotic stress responses. Even when weeds were removed at V4 and tissues sampled at V8, carbon: nitrogen supply imbalance, salicylic acid signals, and growth responses differed between the weed-stressed and weed-free plants. These underlying processes and a small number of developmentally important genes are potential targets for decreasing the maize response to weed pressure. Expression differences of several novel, long noncoding RNAs resulting from exposure of maize to weeds during the CWFP were also observed and could open new avenues for investigation into the function of these transcription units.
Project description:Purpose: This study is designed to identify genes and processes that are differentially regulated in corn when it is grown with or without weeds through the entire critical weed free period (to V8) or when weeds were removed early in the critical weed free period (at V4) and the plants were allowed to recover until V8. Methods: Corn was grown as described above in field plots near Brookings SD in 2007 and 2008 and RNA was extracted from the top-most leaf tips from four plants per treatment plot. Unidirectional cDNA illumina sequencing libraries were constructed for each sample (pooled leaf tips from the given plot), and were sequenced (some samples were paired end sequenced and some were single end sequenced - all 100 bases for PE and SE reads), quality trimmed, and analyzed using the Tuxedo suite of programs for SE reads of the forward read libraries for each sample. Results: We identified a small number of genes that were differentially expressed in both years. More importantly, gene set enrichment analysis of the data determined that weeds, when present through the critical weed free period impacted phytochrome signaling, defense responses, photosynthetic processes, oxidative stress responses, and various hormone signaling processes. When weeds were removed at V4 and the plants allowed to recover until V8, the weeds still imprinted impacts on phytochrome signaling, oxidative stress, and defense responses. Thus, it appears that weeds presence through the early portion of the critical weed free period, even after removal, induced processes that reduce corn growth and yield that lasted at least through V8. Conclusions: This study represents the first investigation of the impact of the lasting effects of weeds during the early critical weed free period on the transcriptome of corn, and provides additional data on the impact of weeds through the critical weed free period that augments and confirms much of what was observed in similar microarray studies. Overall design: Experimental Design: Samples all collected at the same developmental stage (V8) from three treatments (control, weedy, and weeds removed followed by recovery), in each of two years (2007 and 2008), with two to three biological replicates of each treatment in each year.
Project description:This study was designed to identify changes in gene expression when corn was placed under various related stresses including being grown with a competing weed (canola) to the V4 or V8 stage, or when 40% shade cloth was present to the V4 or V8 stage, or under low nitrogen (no added nitrogen fertilizer), or under weed/shade free fertilized control conditions. In all 5 treatments and the control, samples were harvested at V8. Mechanisms underlying early season weed stress on crop growth are not well described. Corn vegetative growth and development, yield, and gene expression response to nitrogen (N), light (40% shade), and weed stresses were compared with the response of nonstressed plants. Vegetative parameters, including leaf area and biomass, were measured from V2 toV12 corn stages. Transcriptome (2008) or quantitative Polymerase Chain Reaction (q PCR) (2008/09) analyses examined differential gene expression in stressed versus nonstressed corn at V8. Vegetative parameters were impacted minimally by N stress although grain yield was 40% lower. Shade, present until V2, reduced biomass and leaf area > 50% at V2 and, at V12, recovering plants remained smaller than nonstressed plants. Grain yields of shade-stressed plants were similar to nonstressed controls, unless shade remained until V8. Growth and yield reductions due to weed stress in 2008 were observed when weeds remained until V6. In 2009, weed stress at V2 reduced vegetative growth, and weed stress until V4 or later reduced yield. Principle component analysis of differentially expressed genes indicated that shade and weed stress had more similar gene expression patterns to each other than to nonstressed or low N stressed tissues. Weed-stressed corn had 630 differentially expressed genes compared with the nonstressed control. Of these genes, 259 differed and 82 were shared with shade-stressed plants. Corn grown in N-stressed conditions shared 252 differentially expressed genes with weed-stressed plants. Ontologies associated with light/photosynthesis, energy conversion, and signaling were down-regulated in response to all three stresses. Although shade and weed stress clustered most tightly together, only three ontologies were shared by these stresses, O-methyltransferase activity (lignification processes), Poly U binding activity (post-transcriptional gene regulation), and stomatal movement. Based on both morphologic and genomic observations, results suggest that shade, N, and weed stresses to corn are regulated by both different and overlapping mechanisms. three biological replicates for each treatment and the control were collected and the resulting labeled cDNA was hybridized to the 46,000-element maize microarray chip developed by the University of Arizona using their protocol (International Microarray Workshop Handbook, 2009Gardiner et al. 2005). The hybridization scheme was a dual hybridization using a rolling circle balanced dye swap design. Thus we had thre biological replicates for each growth condition amd two technical replicates for each biological sample.
Project description:Transcriptomic responses of plants to weed presence gives insight on the physiological and molecular mechanisms involved in the stress response. This study evaluated transcriptomic and morphological responses of two teosinte (Zea mays ssp parviglumis) (an ancestor of domesticated maize) lines (Ames 21812 and Ames 21789) to weed presence and absence during two growing seasons. Responses were compared after 6 weeks of growth in Aurora, South Dakota, USA. Plant heights between treatments were similar in Ames 21812, whereas branch number decreased when weeds were present. Ames 21789 was 45% shorter in weedy vs weed-free plots, but branch numbers were similar between treatments. Season-long biomass was reduced in response to weed stress in both lines. Common down-regulated subnetworks in weed-stressed plants were related to light, photosynthesis, and carbon cycles. Several unique response networks (e.g. aging, response to chitin) and gene sets were present in each line. Comparing transcriptomic responses of maize (determined in an adjacent study) and teosinte lines indicated three common gene ontologies up-regulated when weed-stressed: jasmonic acid response/signaling, UDP-glucosyl and glucuronyltransferases, and quercetin glucosyltransferase (3-O and 7-O). Overall, morphologic and transcriptomic differences suggest a greater varietal (rather than a conserved) response to weed stress, and implies multiple responses are possible. These findings offer insights into opportunities to define and manipulate gene expression of several different pathways of modern maize varieties to improve performance under weedy conditions.
Project description:Research conducted, including the rationale: Weeds reduce yield in soybeans through incompletely defined mechanisms. The effects of weeds on the soybean transcriptome were evaluated in field conditions during four separate gR1.fastqing seasons. Methods: RNASeq data were collected from 6 biological samples of soybeans gR1.fastqing with or without weeds. Weed species and the methods to maintain weed free controls varied between years to mitigate treatment effects and to allow detection of general soybeans weed responses. Key results: Soybean plants were not visibly nutrient or water stressed. We identified 55 consistently down-regulated genes in weedy plots. Many of the down-regulated genes were heat shock genes. Fourteen genes were consistently up-regulated. Several transcription factors including a PHYTOCHROME INTERACTING FACTOR 3-like gene (PIF3) were included among the up-regulated genes. Gene set enrichment analysis indicated roles for increased oxidative stress and jasmonic acid signaling responses during weed stress. Main conclusion: The relationship of this weed-induced PIF3 gene to genes involved in shade avoidance responses in arabidopsis provide evidence that this gene may be important in the response of soybean to weeds. These results suggest the weed-induced PIF3 gene will be a target for manipulating weed tolerance in soybean. Samples were collected from two treatments ("Control" and "Weedy") with six biological replicates (2008, 2009, and twop each for 2010 and 2011) for each treatment.
Project description:Managing production environments in ways that promote weed community diversity may enhance both crop production and the development of a more sustainable agriculture. This study analyzed data of productivity of maize (corn) and soybean in plots in the Main Cropping System Experiment (MCSE) at the W. K. Kellogg Biological Station Long-Term Ecological Research (KBS-LTER) in Michigan, USA, from 1996 to 2011. We used models derived from population ecology to explore how weed diversity, temperature, and precipitation interact with crop yields. Using three types of models that considered internal and external (climate and weeds) factors, with additive or non-linear variants, we found that changes in weed diversity were associated with changes in rates of crop yield increase over time for both maize and soybeans. The intrinsic capacity for soybean yield increase in response to the environment was greater under more diverse weed communities. Soybean production risks were greatest in the least weed diverse systems, in which each weed species lost was associated with progressively greater crop yield losses. Managing for weed community diversity, while suppressing dominant, highly competitive weeds, may be a helpful strategy for supporting long term increases in soybean productivity. In maize, there was a negative and non-additive response of yields to the interaction between weed diversity and minimum air temperatures. When cold temperatures constrained potential maize productivity through limited resources, negative interactions with weed diversity became more pronounced. We suggest that: (1) maize was less competitive in cold years allowing higher weed diversity and the dominance of some weed species; or (2) that cold years resulted in increased weed richness and prevalence of competitive weeds, thus reducing crop yields. Therefore, we propose to control dominant weed species especially in the years of low yield and extreme minimum temperatures to improve maize yields. Results of our study indicate that through the proactive management of weed diversity, it may be possible to promote both high productivity of crops and environmental sustainability.
Project description:A two-year rotation of summer fallow (SF)/winter wheat (WW) is the most common cropping system in low precipitation areas of the U.S. Pacific Northwest (PNW). In SF, multiple tillage operations are used to manage weeds and maximize soil water storage and potential WW yield. Reduced tillage fallow (RTF) is an alternative to SF that leaves >30% of the previous crop's residue on the surface. A four-year (2014-18) field study was conducted to evaluate the influence of SF and RTF on weed species density, cover and composition in dryland WW; determine if changes in these weed infestation attributes have any influence on crop density and yield; and evaluate economic costs of each type of fallow management. The experimental design was randomized complete block with four replications where each phase of SF/WW and RTF/WW rotations was present every year. Individual plots of WW were divided into a weedy sub-plot with no weed control, general area with chemical weed control, and weed-free sub-plot where weeds were manually removed. Infestations of annual grass and other weeds in weedy sub-plots increased throughout the study. Grass weed cover, consisting mainly of downy brome (Bromus tectorum L.), and total weed cover were significantly lower in WW following RTF than following SF in all years except 2018. Densities of grass and total weeds were similar in both fallow managements indicating that weed plants were larger in WW following SF than following RTF due to earlier or faster emergence. Grass cover differences were not found in general areas likely because of a reduced seedbank. When weeds were present, mean yield of WW was higher following RTF than SF indicating that weeds were less competitive in RTF. Reduced tillage fallow could improve weed management in fallow/WW cropping systems of the PNW compared to SF/WW, particularly if the most problematic species are grasses.
Project description:Question:How does the conservation (rarity) value of arable weed communities differ along intensification gradients? Which functional traits best distinguish the weed communities of more and less extensively managed fields? Can the same traits predict the rarity of individual weed species? Location:Hungary. Methods:Using relevé data from 60 cereal and 70 stubble fields, together with weed trait data, we characterized community responses to arable intensification using functional trait analyses based on trait-convergence and trait-divergence assembly patterns. We also examined how well the broad-scale rarity status of species predicts their occurrence along intensification gradients, and how it maps onto our functional classifications describing intensification responses. Results:The response of weeds to intensification in cereal fields was best described by a functional classification based on species' flowering duration, maximum height and seed weight: weeds of extensively managed fields have short flowering seasons (2-5 mo) and particularly large or small seeds. The highest proportions of rare species also happen to be found in these groups. The rarest weeds among these species tend to be late-winter and early-summer annuals, while the rare species of stubble fields tend to be broad-leaved with low nitrogen requirements, small seeds and short height. Stubble fields showed a decline in weed cover with increasing application of fertilizer and distance from the field edge, but we could detect no strong associations of management factors with trait composition, perhaps because the intensification gradient across these fields was shorter. Conclusions:Many rare Hungarian weeds are associated with traditional extensive farming practices. They are particularly characterized by short, midsummer flowering periods and by preference for low nitrogen levels, but a range of trait syndromes must be considered to understand their ecology and conservation. Analyses based on trait-divergence patterns, rather than trait-convergence patterns, provide better insights into the functional composition of weed communities, emphasizing the importance of disruptive filters in weed community assembly and the need for improved methods to detect such effects.
Project description:Weeds are a major threat to biodiversity globally degrading natural areas of high conservation value. But what are our attitudes about weeds and their management including weeds in national parks? Do we know what a weed is? Do we consider weeds a problem? Do we support their management? Are we unintentionally spreading weeds in parks? To answer these questions, we surveyed visitors entering a large popular national park near the city of Brisbane, Australia. Park visitors were knowledgeable about weeds; with >75% correctly defining weeds as 'plants that grow where they are not wanted'. About 10% of the visitors, however, provided their own sophisticated definitions. This capacity to define weeds did not vary with people's age, sex or level of education. We constructed a scale measuring visitors' overall concern about weeds in parks using the responses to ten Likert scale statements. Over 85% of visitors were concerned about weeds with older visitors, hikers, and those who could correctly define weeds more concerned than their counterparts. The majority think visitors unintentionally introduce seeds into parks, with many (63%) having found seeds on their own clothing. However, over a third disposed of these seeds in ways that could facilitate weed spread. Therefore, although most visitors were knowledgeable and concerned about weeds, and support their control, there is a clear need for more effective communication regarding the risk of visitors unintentionally dispersing weed seeds in parks.
Project description:Premise:Weed removal in agriculture is typically achieved using herbicides. The use of autonomous robots to reduce weeds is a promising alternative solution, although their implementation requires the precise detection and identification of crops and weeds to allow an efficient action. Methods:We trained and evaluated an instance segmentation convolutional neural network aimed at segmenting and identifying each plant specimen visible in images produced by agricultural robots. The resulting data set comprised field images on which the outlines of 2489 specimens from two crop species and four weed species were manually drawn. We adjusted the hyperparameters of a mask region-based convolutional neural network (R-CNN) to this specific task and evaluated the resulting trained model. Results:The probability of detection using the model was quite good but varied significantly depending on the species and size of the plants. In practice, between 10% and 60% of weeds could be removed without too high of a risk of confusion with crop plants. Furthermore, we show that the segmentation of each plant enabled the determination of precise action points such as the barycenter of the plant surface. Discussion:Instance segmentation opens many possibilities for optimized weed removal actions. Weed electrification, for instance, could benefit from the targeted adjustment of the voltage, frequency, and location of the electrode to the plant. The results of this work will enable the evaluation of this type of weeding approach in the coming months.