Modeling drought stress impacts under current and future climate for peanut in the semiarid pampas region of Argentina

Assessing environment types for maize, soybean, and wheat in the United States as determined by spatio-temporal variation in drought and heat stress

Purpose: This study aimed to determine the relationship of the container environment's type and condition to the existence of Aedes sp larvae in Tanjungpinang Timur District. Methods: An observational study with a cross-sectional approach involved 401 houses with containers in Tanjungpinang Timur District, Tanjungpinang City. Data on the existence of larvae was performed using the single larvae method. Data on container type and container environmental conditions (water pH, water temperature, air temperature, air humidity) and larvae's presence were collected by observing and measuring. Results: 863 containers were observed, 138 of them (15.99%) were found larvae of Aedes sp, containers inside the house (65.57%), and not closed (88.53%). The types of containers were controllable sites (95.13%), disposable sites (3.36%), and under controllable sites (1.51%). The measurement of water pH (76.13%) and water temperature (82.73%) of the containers were categorized as good. Container temperature 98.38% showed results with a range of unfavorable conditions (<200C &> 300C) and air humidity of 99.07% with a range (<81.5% &> 89.5%). Type, location, condition of container closure, water pH, water temperature, and air temperature of containers were related to larvae in Tanjungpinang Timur District (p-value <0.05), while the variable humidity was not related to the existence of larvae. Conclusion: Physical environmental factors strongly support the reproduction of DHF vectors in the East Tanjungpinang District. It is necessary to increase public knowledge and routine home eradication of mosquito nests (PSN), especially controllable site containers widely used as water reservoirs.

Abstract This paper reports a first study exploring genomic prediction for adaptation of sorghum [Sorghum bicolor (L.) Moench] to drought‐stress (D‐ET) and nonstress (W‐ET) environment types. The objective was to evaluate the impact of both modeling genotype × environment interaction (G×E) and accounting for heterogeneous variances of marker effects on genomic prediction of parental breeding values for grain yield within and across environment types (ETs). For this aim, different genetic covariance structures and different weights for individual markers were investigated in best linear unbiased prediction (BLUP)‐based prediction models. The BLUP models used a kinship matrix combining pedigree and genomic information, termed K‐BLUP. The dataset comprised testcross yield performances under D‐ET and W‐ET as well as pedigree and genomic data. In general, modeling G×E increased predictive ability and reduced empirical bias of genomic predictions for broad adaptation across both ETs vs. models that ignored G×E by fitting a main genetic effect only. Genomic predictions for specific adaptation to D‐ET or W‐ET were also improved by K‐BLUP models that explicitly accommodated G×E and used data from both ETs relative to prediction models that used data from the targeted ET exclusively or models that used all the data but assumed no G×E. Allowing for heterogeneous marker variances through weighted K‐BLUP produced clear increments (43–72%) in predictive ability of genomic prediction for grain yield in all adaptation scenarios. We conclude that G×E as well as locus‐specific genetic variances should be accommodated in genomic prediction models to improve adaptability of sorghum to variable environmental conditions.

The genotype-environment interaction under individual and population selection studied studied inarticle. The basic principles of forest genetics, tree breeding and introduction in Ukraine are considered.Despite significant advances in selection and testing of progeny at the individual and population levels,aspects of interaction with the environment have not been investigated. The study of halfsibs and sibsprogeny, varieties and hybrids was conducted only in the context of productivity in the same type ofenvironment condition. At the same time, the issue of reacting and interacting with the environment hasnot been studied. In conditions of global warming, changes in soil and hydrological conditions, there isa need for the use of modern methods for assessing the response of genotypes to environmental changes.The article presents the main approaches to assessing the interaction of genotype (variety) — environmentin order to introduce effective mechanisms for improving the quality of selection. The parametric andnonparametric estimation models based on previous developments of foreign scientists are considered. Inparticular, the main models developed by Eberhart and Russel (1966), Thai (1971), Shukla (1972), Hanson(1988), Nassar and Hyn (1987), Fox (1990) and Kang (Kang, 1991). The interpretation of the resultscalculated for the indicators is given. The paper states that existing models have both positive and flaws.Therefore, when evaluating the interaction of genotype-environment it is expedient to use several models.The use of several models makes it possible to identify with high confidence the most productive, stable and adapted genotypes under certain environmental conditions. This is especially true in the conditions of global climate change, the variability of soil-hydrological conditions of the environment.

Sorghum drought and heat stress patterns across the Argentinean temperate central region

A stochastic point location (SPL) problem aims to find a target parameter on a 1-D line by operating a controlled random walk and receiving information from a stochastic environment (SE). If the target parameter changes randomly, we call the parameter dynamic; otherwise static. SE can be 1) informative (p > 0.5 where p represents the probability for an environment providing a correct suggestion) and 2) deceptive (p <; 0.5). Up till now, hierarchical stochastic searching on the line (HSSL) is the most efficient algorithms to catch static or dynamic parameter in an informative environment, but unable to locate the target parameter in a deceptive environment and to recognize an environment's type (informative or deceptive). This paper presents a novel solution, named symmetrical HSSL, by extending an HSSL binary tree-based search structure to a symmetrical form. By means of this innovative way, the proposed learning mechanism is able to converge to a static or dynamic target parameter in the range of not only 0.6181 <; p <; 1, but also 0 <; p <; 0.382. Finally, the experimental results show that our scheme is efficient and feasible to solve the SPL problem in any SE.

Performance of spring wheat lines near-isogenic for the reduced-tillering ‘tin’ trait across a wide range of water-stress environment-types

A stay-green phenotype enables crops to retain green leaves longer after anthesis compared with senescent types, potentially improving yield. Measuring the normalized difference vegetative index (NDVI) during the whole senescence period allows quantification of component stay-green traits contributing to a stay-green phenotype. These objective and standardized traits can be compared across genotypes and environments. Traits examined include maximum NDVI near anthesis (Nmax), senescence rate (SR), a trait integrating senescence (SGint), plus time from anthesis to onset (OnS), mid-point (MidS), and near completion (EndS) of senescence. The correlation between stay-green traits and yield was studied in eight contrasting environments ranging from well watered to severely water limited. Environments were each classified into one of the four major drought environment types (ETs) previously identified for the Australian wheat cropping system. SGint, OnS, and MidS tended to have higher values in higher yielding environments for a given genotype, as well as for higher yielding genotypes within a given environment. Correlation between specific stay-green traits and yield varied with ET. In the studied population, SGint, OnS, and MidS strongly correlated with yield in three of the four ETs which included well-watered environments (0.43-0.86), but less so in environments with only moderate water-stress after anthesis (-0.03 to 0.31). In contrast, Nmax was most highly correlated with yield under moderate post-anthesis water stress (0.31-0.43). Selection for particular stay-green traits, combinations of traits, and/or molecular markers associated with the traits could enhance genetic progress toward stay-green wheats with higher, more stable yield in both well-watered and water-limited conditions.

Characterization of drought environment types (ETs) has proven useful for breeding crops for drought-prone regions. Here, we consider how changes in climate and atmospheric carbon dioxide (CO2 ) concentrations will affect drought ET frequencies in sorghum and wheat systems of northeast Australia. We also modify APSIM (the Agricultural Production Systems Simulator) to incorporate extreme heat effects on grain number and weight, and then evaluate changes in the occurrence of heat-induced yield losses of more than 10%, as well as the co-occurrence of drought and heat. More than six million simulations spanning representative locations, soil types, management systems, and 33 climate projections led to three key findings. First, the projected frequency of drought decreased slightly for most climate projections for both sorghum and wheat, but for different reasons. In sorghum, warming exacerbated drought stresses by raising the atmospheric vapor pressure deficit and reducing transpiration efficiency (TE), but an increase in TE due to elevated CO2 more than offset these effects. In wheat, warming reduced drought stress during spring by hastening development through winter and reducing exposure to terminal drought. Elevated CO2 increased TE but also raised radiation-use efficiency and overall growth rates and water use, thereby offsetting much of the drought reduction from warming. Second, adding explicit effects of heat on grain number and grain size often switched projected yield impacts from positive to negative. Finally, although average yield losses associated with drought will remain generally higher than that for heat stress for the next half century, the relative importance of heat is steadily growing. This trend, as well as the likely high degree of genetic variability in heat tolerance, suggests that more emphasis on heat tolerance is warranted in breeding programs. At the same time, work on drought tolerance should continue with an emphasis on drought that co-occurs with extreme heat.

According to the general biological theory the develop-ment and evolution of humans into complete bio-psycho-social beings are realized through continuous morpholog-ical and functional adjustment processes. The basic goalsof these processes are (a) survival in all the different typesof environment that the individual is confronted with,and (b) assurance of the continuation of the species viathe succession of its generations. In this evolutionary bio-logical theory and in agreement with the value of observ-ing behaviours lie also the roots of ethology.

Petroleum hydrocarbons were characterized at eleven sites withinthe sediments of a coastal stream in south Texas, U.S.A. following a medium sized crude oil spill. Bank and open-water(deep) sediments were collected at each site. Hydrocarbonstargeted for analysis included 22 aliphatic hydrocarbons (C-11to C-34) and 16 polynuclear aromatic hydrocarbons. Sedimentconcentrations were measured at intervals of 1, 2, 3, 4, 6, and12 months post-spill. Higher hydrocarbon concentrations were observed for a longerduration within the deep sediments than bank sediments. Initialhydrocarbon constituents in impacted sediments matched the crudeoil fingerprint accurately with the exception of the lighter-endhydrocarbons. The lighter-end aliphatic hydrocarbons areaffected immediately by evaporation and dissolution processesduring the spill event and were found below the detection levelsat most of the sites. Total hydrocarbon concentrations insediments within each hydrocarbon group returned to backgroundlevels by the end of the study period. Observed decreases inhigh molecular weight polycyclic aromatic hydrocarbons (PAH)concentrations exceeded known environmental degradation rateswhich suggests the influence of a sediment transport process. Overall, the fate of petroleum hydrocarbons within this type ofenvironment were likely related to both degradation and sedimenttransport processes. By the end of the study period, most individual PAH constituent concentrations were below thresholdconcentrations thought to produce toxic effects in marine andestuarine organisms. PAH constituents concentrations remainingabove threshold concentrations included benz(a)anthracene,chrysene, and benzo(a)pyrene.

Genotype × environment (G×E) interactions due to variation in soil moisture and rainfall complicate the interpretation of sorghum hybrid performance trials over locations (L) and years (Y). This paper aims to use pattern analysis to explain measures of the G×L interaction for yield, and whether these can, in turn, be explained using simulation models to determine the occurrence of environment types (within-season patterns of drought). The aim of this work is to simplify the analysis of G×E by explaining it in terms of interactions of genotypes with environment types (ET) that are not ‘fixed’ to locations and years. In a sequential analysis of 17 seasons, 18 locations were separated into groups that tended to represent either the northern (i.e. central Queensland, CQ) or southern Queensland (SQ) regions. For a subset of 6 locations, ordination partially explained differences among locations as being related to latitude ( r = 0.88) and rainfall ( r = -0.46), but they were better related ( r &amp;gt; 0.9) to the frequencies of 3 stress ETs as determined by long-term crop simulations. These 3 environment types were: ( 1 ) low stress (occurring in 33% of seasons); ( 2 ) severe terminal stress with an early-season (9%) or midseason time (29%) of onset; and ( 3 ) intermediate terminal stress with a midseason (9%) or late-season (20%) time of onset. Low stress ETs were more common in two SQ locations than in CQ. Stress ETs as defined by simulation models and pattern analysis had more consistent relationships with simulated yields than did the fixed descriptors of locations and years. Sorghum hybrid trials for broad adaptation in Queensland should include locations at least from each of the 2 regions and the results should be interpreted in the context of the season in which they are conducted. To match the long-term patterns in the 6 locations of the analysis, trial yields would need to sample from at least 3 yield ranges: &amp;lt;1 t/ha, 1–3.5 t/ha, and &amp;gt;3.5 t/ha. Additional seasons of testing are likely to be required when the locations used during a season do not adequately represent the target population of environments over all locations and years.

The variable nature of rainfall in north-eastern Australia confounds the process of selecting sorghum hybrids that are broadly adapted. This paper uses a crop simulation model to characterise the drought environment types (ET) that occur in the target population of environments (TPE) for dryland sorghum. Seventy seasons (1921–1990) of simulations of the yield of a sorghum genotype and the associated within-season sequence of a stress index were conducted for a small TPE of 6 locations and also for a large TPE of 211 locations that attempted to represent the entire sorghum region. Previously, using the small dataset of 6 locations, pattern analysis enabled us to group seasonal stress indices from each trial into major ETs: ‘low terminal stress’ (ET1), severe terminal stress (ET2), and intermediate mid-season/terminal stress (ET3) in the ratio 33 : 38 : 29. When the dataset was broken into a sequence of 16 multi-environment trials (METs), each of 3 years and 6 locations, the ratios of ET1 : ET2 : ET3 differed greatly among METs, i.e. any single MET was not randomly sampling the TPE. Hence, for any MET, the average yield ( GV u) was not the same as the overall mean of the entire 70-year dataset. If the trial yields were weighted according to the ratio of ET1 : ET2 : ET3 in the overall TPE, then GV w (s.d. = 0.13) for a single MET was much closer to the overall mean than was GV u (0.38). For different METs, the values of GV w were up to 30% higher or 15% lower than GV u. Across METs, the difference between GV u and GV w was positively correlated ( r = 0.88, n = 16, P &amp;lt; 0.05) with the frequency of ET1 (‘low terminal stress’) encountered within the MET and negatively correlated ( r = -0.82) with the frequency of ET2. The value of weighting was confirmed by its ability to verify that two simulated genotypes had the same mean yield over many trials, even though they differed in their specific adaptation to the different ETs. The large TPE consisted of more than 15 000 simulations and was classified in 2 stages (within/among locations), repeated for each of 3 soil types. In years in which the simulation sowing criteria were met, the ratios of ET1 : ET2 : ET3 were about 4:2:4, 4:5:1, and 6:3:1 in the shallow, intermediate, and deep soils, respectively. Hence, over all soil types and locations, the sorghum TPE for northern Australia consists of at least 30% each of low terminal stress (ET1) or severe terminal stress (ET2) and these environment types need to be sampled. The incidence and nature of the ‘intermediate midseason/terminal stress’ environment type (ET3) varies with soil type and location. Weighting genotype performance should improve the precision of the estimate of its broadly adapted value, and be of practical use in breeding programs in these variable environments. Although the ‘boundary conditions’ of the TPE are not yet resolved, this paper also shows that simulation and pattern analyses can be used to determine the structure of the abiotic TPE. Taking other factors into account (e.g. soil type distribution, shire production levels, and farm profit), selection trials could be weighted to improve selection for narrow or broad adaptation, depending on the purpose of the breeding program.