•Conjoint analysis for transcriptomics and metabolomics were first used in studying the developmental regularity of backfat (BF) for pig.•Weexploredthecandidategenes and ...metabolitesaffectingfatdepositioninNingxiang pig.•ThesecandidatesregulatedfatdevelopmentviacAMP signaling pathway, regulation of lipolysis in adipocytes, and biosynthesis of unsaturated fatty acids.
Enhancing meat production and quality is the eternal theme for pig breeding industries. Fat deposition has always been the focus of research in practical production because it is closely linked to pig production efficiency and pork quality. In the current study, multi-omics techniques were performed to explore the modulatory mechanisms of backfat (BF) accumulation at three core developmental stages for Ningxiang pigs. Our results identified that 15 differentially expressed genes (DEGs) and 9 significantly changed metabolites (SCMs) contributed to the BF development via the cAMP signaling pathway, regulation of lipolysis in adipocytes, and biosynthesis of unsaturated fatty acids. Herein, we found a series of candidate genes such as adrenoceptor beta 1 (ADRB1), adenylate cyclase 5 (ADCY5), ATPase Na+/K+ transporting subunit beta 1 (ATP1B1), ATPase plasma membrane Ca2+ transporting 3 (ATP2B3), ATPase Na+/K+ transporting subunit alpha 2 (ATP1A2), perilipin 1 (PLIN1), patatin like phospholipase domain containing 3 (PNPLA3), ELOVL fatty acid elongase 5 (ELOVL5) and metabolites like epinephrine, cAMP, arachidonic acid, oleic acid, linoleic acid, and docosahexaenoic acid existed age-specificeffects and played important roles in lipolysis, fat accumulation, and fatty acid composition. Our findings provide a reference for molecular mechanisms in BF tissue development and the optimization of carcass quality.
•Analysis of 49088 phenological observations from 6 tree species in Switzerland.•Leaf unfolding has advanced by up to –3.0 days/decade since 1985.•Leaf colouring was mainly delayed since 1985, ...reaching +4.0 days/decade.•Climate change intensified drought for trees at low and high elevations.•Shifting phenology amplified drying for low-elevation beech, rowan, and sycamore.
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Climate change alters the bioclimatic conditions during the growing period of trees directly, but also indirectly by causing shifts in spring and autumn leaf phenology that lead to changes in the timing and length of the growing period. Several studies researched the ecological consequences of direct climate change effects on bioclimatic conditions during the growing period of trees. However, the complementary and indirect effects through phenological shifts on these conditions have been insufficiently investigated. We analysed 49088 leaf unfolding and leaf colouring dates of six major European tree species from Switzerland, observed between 200 and 1900 m a.s.l. during 1961–2018. We estimated phenological trends, the resulting changes in bioclimatic conditions during the growing period, and the relative contributions of phenological shifts towards these changes. Our results show that climate change advanced leaf unfolding by up to –3.0 days/decade since 1985. Leaf colouring was mainly delayed at low elevations and was advanced or delayed at high elevations with species-specific rates between –3.1 and +4.0 days/decade. While the length of the growing period and growing degree-days increased for most species after 1985, precipitation during the growing period predominantly decreased by up to –43.6 mm/decade. Furthermore, drought intensity during the growing period (based on the number of days with negative water balance) increased significantly for most species, reaching +6.7 days/decade at low elevations. Phenological shifts amplified the trends towards drier conditions by up to +81% at low elevations for beech, rowan, and sycamore, but weakened them by up to –84% at high elevations for beech, rowan, sycamore, and larch. These findings indicate widely increased drought stress, especially at lower elevations. Further, we conclude that future forest net ecosystem productivity in Central Europe will depend strongly on elevation and species composition, despite a general lengthening of the growing period for trees.
Huang-Huai-Hai Plain is an important area for summer maize production in China. The study of drought characteristics during summer maize growing period is of guiding significance for preventing ...drought and flooding and ensuring grain production. Based on daily meteorological data from 1960 to 2020 on Huang-Huai-Hai Plain, daily drought indicators were used to quantitatively identify drought conditions during summer maize growing period, analyze spatial and temporal evolution characteristics of drought, and explore the teleconnection between climate change and drought characteristics. Results showed that the most frequent and long-lasting drought occurred during the summer maize sowing-jointing stage on Huang-Huai-Hai Plain in the 1960 s, and the entire plain was basically in a drought-prone area in the last 61a. Drought occurred less frequently, was short-lived throughout the reproductive stage during jointing-flowering, and was concentrated in the light drought zone. Drought frequency in the flowering-maturation stage was highest during the entire growth period, and drought frequency displayed a ' high-low-high ' three-stage distribution from south to north, mainly in drought-prone and extremely drought-prone areas. The drought barycenter during the sowing-jointing stage showed an east-west distribution pattern, and moved eastward from 1970 to 2000, displaying a south-north distribution pattern during jointing-flowering and flowering-maturation stages. Drought conditions at the sowing-jointing and flowering-maturation stages of summer maize displayed positive correlation with the occurrence of El Niño-Southern Oscillation (ENSO) warm events, and the flowering-maturation stage displayed a negative correlation with the occurrence of ENSO cold events. Oceanic Nino Index (ONI) was the most suitable climatic factor for analyzing causes of drought during summer maize growing period on Huang-Huai-Hai Plain.
•Drought status of summer maize in Huang-Huai-hai Plain was studied.•A daily scale SPEI-PM was used to identify drought conditions in maize.•The remote correlation between ENSO events and drought of maize was explored.•ONI was the main climatic factor affecting the growth of summer maize in this region.
•Warming climate reduced maize yield by shortening growing period.•Maize cultivars with a long growing period have difficulty to offset climate change impacts.•Growing period of maize is related to ...the tolerance of high plant density.•Interaction of growing period and plant density tolerance can further increase maize yield.
Climate changes in temperature, solar radiation, and precipitation potentially interrupt progressive improvement in crop yield. Genetic and agronomic strategies to adapt climate changes were proposed in previous studies, but were rarely evaluated. In this study, meteorological data from 1954 to 2014 at one representative station in the North China Plain (NCP), model simulation of Hybrid-Maize, and a field experiment were combined together to detect climate change impacts on maize yield and to assess the adaptive effects of cultivars. Three maize cultivars with contrasting lengths of growing period were grown at three specific plant densities. Cultivar with a long growing period (LG) was grown at 67500 (optimal density), 82500, and 97500 plant ha−1, medium-growing (MG) cultivar at 82500 (optimal), 97500, and 112500 plant ha−1, and short-growing (SG) cultivar at 97500 (optimal), 112500, and 124500 plant ha−1. During the past six decades, temperature increased and solar radiation decreased significantly in the total, vegetative, and reproductive growing periods of maize in the NCP with a slight decline in precipitation. These climate changes significantly reduced yield at a rate of 30.8, 31.3, and 25.0kgha−1yr−1, respectively, for SG, MG, and LG maize cultivars. Decline in growing degree days (GDD) use efficiency of LG cultivar with changing climate was one-fold slower than that of SG and MG cultivars. MG maize cultivar was estimated to produce the highest grain yield in NCP owing to its relatively long growing period and high tolerance of plant density. LG maize cultivar has a larger potential to adapt changing climate, but has a larger difficulty in improving yield because of lower tolerance of high plant density. Improvement of plant architecture in space and in time is expected to resolve the conflict between adapting climate changes and tolerating high plant density in maize.
In order to define a suitable sowing date and effect of nitrogen fertilizer on quinoa, a randomized complete block design field experiment was conducted based on a split-plot design with three ...replications in 2019 at Ahar, Iran. Experimental treatments included: Five sowing dates (Feb. 24, Mar. 11, Mar. 25, Apr. 9 and Apr. 25) as main plot and five levels of nitrogen fertilizer (0, 90, 180, 270 and 360 kg ha-1) as sub plots. Results indicated that maximum 1000-seed weight (3.48 g) was obtained at sowing date of 25 Apr. under 180 kg ha-1 nitrogen and the highest grain yield and biomass were observed at sowing date of 25 Apr. with application of 270 and 360 kg ha-1 nitrogen fertilizer. The highest plant height and grain nitrogen percentage were obtained in the sowing date of 25 Apr. with application of 90, 180, 270 and 360 kg ha-1. A significant increase in nitrogen agronomic efficiency was observed with increasing application of nitrogen from control to 90 kg ha-1 in all sowing dates. The highest growing period (with 137 days) was observed at sowing date of 24 Feb. and the lowest growing period (with 95 days) was observed at sowing date of 25 Apr. Generally, the sowing date of 25 Apr. with application of 270 kg ha-1 nitrogen fertilizer is suitable for Ahar region owing to the shortest growing period and highest grain yield and biomass.
Crop models require information on both weather and agronomic decisions to simulate crop productivity and to design adaptation strategies. Due to the lack of observational data, previous studies used ...different approaches to determine sowing dates and cultivar parameters. However, the timing of harvest has not yet been sufficiently analyzed.
Here we propose an algorithm to determine location-specific maturity (or harvest) dates for applications in global modelling studies. Given a sowing date and the climatic conditions, the algorithm returns a suitable maturity date, based on crop physiological parameters and agronomic principles.
We test the method on a global land area with a spatial resolution of 0.5° against global reported datasets for major grain crops: winter-wheat, spring-wheat, rice, maize, sorghum and soybean. A single set of rules is able to largely reproduce the observed harvest dates of the six grain crops globally, with a mean absolute error of 19 (maize) to 45 (rice) days. In temperate regions, the temperature seasonality is the major driver of cropping calendars. In sub-tropical regions, crops are grown to match water availability. In the case of limiting growing seasons, the crop cycle is shortened or extended to avoid stressful periods. In the case of long-lasting favorable conditions the crop cycle is shorter than what the growing season would allow.
We find that cropping periods can be largely defined by climate and crop physiological traits. The timing of the reproductive phase is shown to be a general criterion for selecting grain crops cultivars. This work will allow for dynamically representing adaptation to climate change by adjusting cultivars and represents a first step towards improved crop phenology simulations by global-scale crop models.
•Global crop models require information on cropping periods to represent cultivar diversity.•Crop maturity (or harvest) dates can be estimated from climate, crop physiological parameters and agronomic principles.•We propose a method for applications in global modelling studies for dynamically representing adaptation to climate change.
Antimicrobial resistance (AMR) is an important threat to public health worldwide. Furthermore, different studies have demonstrated a close association between antibiotic use in animal production and ...AMR in humans. It is well known that it is necessary to reduce antibiotic administration in farms by finding effective alternative treatments, using more resistant breeds and improving animal welfare. However, to be able to assess the alternatives proposed, it is essential to study the epidemiology of AMR under production conditions. Hence, the aim of this study was to investigate the AMR dynamic in 2 genetic poultry breeds during the growing period. The study was performed in 2 experimental poultry houses to simulate real production conditions, and no antibiotics were administered during the growing period. In addition, 2 poultry breeds were used, fast-growing and slow-growing. To evaluate AMR evolution, Escherichia coli was selected as indicator bacterium. To this end, animals from each experimental group were sampled at different times: on day of arrival, at mid-period, and at slaughter day. In the laboratory, cecal content was removed and inoculated in selective media. Then, biochemical tests were performed to confirm E. coli. Finally, antibiotic susceptibility was assessed according to Decision 2013/653. At the onset of the cycle, significant differences were observed between breeds, as the E. coli strains isolated from fast-growing 1-day-old-chicks showed higher AMR rates. However, at the end of the period, no significant differences were found between breeds and their presence of resistant bacteria (above 95%). Therefore, although no antibiotics were administered during the growing period, a high level of AMR at slaughter day was demonstrated. Further studies are necessary to determine the main risk factors that increase the level of AMR throughout the productive cycle in broiler chickens. In conclusion, it is important to highlight that although it is crucial to control both antibiotic use and animal welfare during the growing period, measures should be taken at all levels of the production chain.
•Knowledge of onset and cessation of rains is critical for crop planning in tropical regions.•Analyses of these parameters at production-relevant scale are lacking.•We quantify interannual ...variability and trends at agroecosystem level.•Results indicate that existing agricultural practices may need to be revised.•Extended weather and sub-seasonal forecast services should be implemented in the area.
Analysis of Rainfall onset date (OD), cessation date (CD), and length of growing period (LGP) for specific sites in highly dissected topography and highly variable climate may not provide actionable information for crop production planning. In tropical highland regions information on these parameters is scant at a resolution relevant for targeted management. This study examined recent (1981-2016) OD, CD, and LGP variability and trends for the main rainy season in different agroecosystems (AESs) in the northwestern Ethiopian Highlands. Onset criteria were derived from surveys, rainfall data, and previous literature whereas cessation criteria were set from the soil water holding capacity (WHC), daily reference evapotranspiration (ETo), and daily rainfall in each site. Dry spells (DS) were analyzed for the small rainy season in higher elevation AESs where the season is relevant for potato production. All analyses were performed using site specific data grouped by agroecosystem (AES), a unit that has similar climate, soil, crop, and farm management for better agricultural decisions. Results show high inter-annual variability of OD and CD, and LGP exhibited a significant trend in some AES and greater variability in higher elevation AES. Generally, trend analysis results showed early onset and cessation of rainfall. Significant increasing trends and variabilities in DS and OD may significantly affect crop production and thus AES specific crop production calendar should be revised to minimize crop failure. The analysis also confirmed that farmers perception is consistent with meteorological analysis. The results emphasize the importance of AES-based improved seasonal weather forecasts and tailored climate information services to guide farm decisions and improve management of climate variability by smallholder farmers. It also concluded that AES level analysis can better provide actionable information for decision makers and growers than site specific and scattered studies as mosaic results are reported between sites grouped in the same agroecosystem.
•Oak growing period decreases by 70 days along an elevational gradient of 1500 m.•Growing period extends in warmer years within population at a given elevation.•Phenological ranks between individuals ...remain mostly stable over years.•Radial growth benefits from warmer temperatures only at higher elevations.•There is no link between radial growth and growing period length within population.
Tree growth and leaf phenology are both affected by global warming. Mountain ecosystems are of paramount importance for studying phenological and growth responses of trees to the gradual variation of temperature. However, the relationship between growing season length and tree growth has been little studied at the level of individual trees. Here, we investigated the relationships between leaf phenology, growing degree-days and radial growth of sessile oaks growing in nine populations along an elevational gradient of 1500 m in the French Pyrenees. In each population, leaf unfolding in spring and leaf coloration in autumn were monitored between 2005 and 2015 on 25-30 trees having contrasting spring phenology (i.e. early vs. late flushing trees). These trees were cored in 2013 to analyse annual tree-ring widths. While trees displayed consistent phenological ranks for both leaf unfolding and leaf coloration within their population over the years, the growing period length decreased with increasing elevation, from about 210 days at the lowest elevation (131 m a.s.l.) to 140 days at the highest elevation (1630 m a.s.l.). For a given year, individual leaf coloration dates correlated positively with leaf unfolding dates at lower elevations, but negatively at higher elevations. Radial growth was positively correlated with growing degree-days at higher elevations, but negatively correlated at lower elevations, likely because higher temperatures are often associated with severe droughts in the lowlands of this region. No clear relationship was found between growing period length and radial growth of oaks within their population. This indicates that climatic conditions during the growing period have a more important impact on the secondary growth of sessile oaks than the growing period length. Our findings suggest that the lengthening of the growing period of trees in response to global warming does not necessarily lead to higher radial growth and productivity.
•A process-based model (ORCHIDEE-crop) is calibrated efficiently with particle filter.•LGP of different rice types show varied response to change in climate and management.•Change in managements have ...larger impacts than climate change for early & single rice.•Regional modelling should consider multiple rice types & changing management practices.•Improved records on management & observation error are vital for reducing uncertainty.
Whether crop phenology changes are caused by change in managements or by climate change belongs to the category of problems known as detection-attribution. Three type of rice (early, late and single rice) in China show an average increase in Length of Growing Period (LGP) during 1991–2012: 1.0±4.8day/decade (±standard deviation across sites) for early rice, 0.2±4.5day/decade for late rice and 2.0±6.0day/decade for single rice, based on observations from 141 long-term monitoring stations. Positive LGP trends are widespread, but only significant (P<0.05) at 25% of early rice, 22% of late rice and 38% of single rice sites. We developed a Bayes-based optimization algorithm, and optimized five parameters controlling phenological development in a process-based crop model (ORCHIDEE-crop) for discriminating effects of managements from those of climate change on rice LGP. The results from the optimized ORCHIDEE-crop model suggest that climate change has an effect on LGP trends dependent on rice types. Climate trends have shortened LGP of early rice (−2.0±5.0day/decade), lengthened LGP of late rice (1.1±5.4day/decade) and have little impacts on LGP of single rice (−0.4±5.4day/decade). ORCHIDEE-crop simulations further show that change in transplanting date caused widespread LGP change only for early rice sites, offsetting 65% of climate change induced LGP shortening. The primary drivers of LGP change are thus different among the three types of rice. Management are predominant driver of LGP change for early and single rice. This study shows that complex regional variations of LGP can be reproduced with an optimized crop model. We further suggest that better documenting observational error and management practices can help reduce large uncertainties existed in attribution of LGP change, and future rice crop modelling in global/regional scales should consider different types of rice and variable transplanting dates in order to better account impacts of management and climate change.
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