Search Results (8)

Active accumulated temperature (AAT) serves as a pivotal metric for assessing soybean adaptation across diverse climatic conditions, particularly in the northeastern regions of China. This study embarked on a genome-wide association analysis (GWAS) to elucidate the genetic determinants influencing AAT and its impact on flowering time among soybean varieties. Leveraging a panel of 140 elite soybean varieties encompassing both Chinese and European early-maturity groups and employing high-density genotyping, significant associations were identified on chromosome 6. Notably, a key gene, Glyma.06g204500, emerged as a central component, exhibiting strong linkage to the well-established E1 locus, alongside three distinct haplotypes. This investigation underscores Glyma.06g204500’s potential role in mediating soybean’s response to temperature fluctuations, offering novel insights into the genetic mechanisms underpinning soybean adaptation to local environmental conditions. Full article

In soybeans (Glycine max (L.) Merr.), their growth periods, DSF (days of sowing-to-flowering), and DFM (days of flowering-to-maturity) are determined by their required accumulative day-length (ADL) and active temperature (AAT). A sample of 354 soybean varieties from five world eco-regions was tested in four seasons in Nanjing, China. The ADL and AAT of DSF and DFM were calculated from daily day-lengths and temperatures provided by the Nanjing Meteorological Bureau. The improved restricted two-stage multi-locus genome-wide association study using gene–allele sequences as markers (coded GASM-RTM-GWAS) was performed. (i) For DSF and its related ADL_DSF and AAT_DSF, 130–141 genes with 384–406 alleles were explored, and for DFM and its related ADL_DFM and AAT_DFM, 124–135 genes with 362–384 alleles were explored, in a total of six gene–allele systems. DSF shared more ADL and AAT contributions than DFM. (ii) Comparisons between the eco-region gene–allele submatrices indicated that the genetic adaptation from the origin to the geographic sub-regions was characterized by allele emergence (mutation), while genetic expansion from primary maturity group (MG)-sets to early/late MG-sets featured allele exclusion (selection) without allele emergence in addition to inheritance (migration). (iii) Optimal crosses with transgressive segregations in both directions were predicted and recommended for breeding purposes, indicating that allele recombination in soybean is an important evolutionary drive. (iv) Genes of the six traits were mostly trait-specific involved in four categories of 10 groups of biological functions. GASM-RTM-GWAS showed potential in detecting directly causal genes with their alleles, identifying differential trait evolutionary drives, predicting recombination breeding potentials, and revealing population gene networks. Full article

Global climate change has greatly influenced the ecosystems in the Tibetan Plateau. Many studies focused on the direct effects of climate warming on the headwater regions by mean temperature, while less investigating its implication for the eco-environment. To address this, the study discussed the spatial-temporal variations of the bio-related climate indicators ≥0 °C annual accumulated temperature AAT0 and its lasting days LDT0, and corresponding ≥5 °C indicators AAT5 and LDT5 on the source region of the Yellow River (SRYR). The stationarity of indicators during 1979–2018 were tested by Pettitt test, and trends checked by linear regression analysis and Mann-Kendall test. Normalized difference vegetation index NDVI (2001–2016) was adopted to detect the correlation between vegetation activities and indicators. Results show that the AAT and LDT0 exhibited significant increasing trend over the SRYR, while the LDT5 significantly increased mainly under 4000 m. Most LDT extended due to the combined efforts of the early onset and late termination of the given temperature. 1997 was detected in the abrupt change analysis of AAT0 both on the basin scale and most area, and was adopted to divide the period into two stages. The regional mean AAT0 linearly grew at a rate of 96 °C decade⁻¹ during the entire period, and 104 °C decade⁻¹ during the second stage. Except for a drastic jump in the areal mean values, there was a distinct upward-shift of isoline in elevation between stages. NDVI showed strong correlativity with ≥0 °C indicators on the basin scale, according to the Pearson, Spearman and Kendall correlation coefficients, ranging from 0.5 to 0.7. Spatially, the overlap area between Pearson’s γ ≥ 0.5 and linearly rising AAT0 reached 50%, which was fully covered with significantly increasing AAT0 during the recent stage. Thus the rapid growth of ≥0 °C indicators would effectively accelerate NDVI over this major alpine grasslands, especially around the eastern low regions, where indicators are higher and grow faster. Full article

Crop heat units (CHU) and ≥10 °C active accumulated temperature (≥10 °C AAT) are important indexes to quantify the effects of temperature on soybean development. The relative maturity group (RMG) is widely used in the classification of different soybean varieties. However, CHU and ≥10 °C AAT (AAT) were applied in Canada and northeastern China, respectively, and the relationships among CHU, AAT and RMG are poorly documented. The objective of this study is to analyze the conversion function among CHU, AAT and RMG based on two datasets. The first dataset was obtained to analyze the relationship between RMG and AAT in 395 varieties in Northeast China. The second dataset was obtained to calculate the relationship between CHU and AAT at 95 weather stations based on 30-year climatic data (1990–2019). The results showed that both relationships were significantly and positively correlated, and the R-square of these relationships were 0.90 and 0.98, respectively. The distribution of CHU or AAT in the Northeast is proposed. These results can be extensively used for predicting the CHU or AAT of soybean cultivars given the known RMG, thus determining the adaptation zone as well as the growth stage of agricultural practices and responses to heat accumulation. The conclusion of the current study is expected to be widely adopted by soybean regionalization and germplasm exchanges throughout the world. Full article

Soybean (Glycine max (L.) Merr.) is a typical short-day and thermophilic crop. This study aimed to reveal the required accumulative day length (ADL) and accumulative active temperature (AAT) for DSF (days of sowing to flowering) and DFM (days of flowering to maturity) in global soybeans. A sample consisted of 354 varieties from 27 countries in five geographic regions, which were tested in Nanjing, China in two spring-sowing and two summer-sowing seasons. The ADL and AAT were calculated from the climatological data provided by the Public Service of Nanjing Meteorological Bureau. The results showed that the average DSF and DFM of global soybeans were 41.0 d and 83.3 d, which required ADL_DSF of 606.6 d·h and AAT_DSF of 1185.9 d·°C, ADL_DFM of 1126.7 d·h and AAT_DFM of 2145.1 d·°C, respectively, all with a wide variation among/within geographic and MG(maturity-group)-set subpopulations. From the multiple regression of DSF and DFM on required ADL and AAT, the ADL, AAT and ADL×AAT contributed 38.5%, 44.79% and 17.10% to DSF variation and 86.98%, 11.42% and 0.54% to DFM variation, respectively, and their relative importance to DSF and DFM varied among the geographic and MG subpopulations. The geographic subpopulations matched only partially with the genomic marker clusters, indicating multiple genetic sources of each subpopulation and that genetic exchange happened among subpopulations. Full article

Remotely sensed data have been used in crop condition monitoring for decades. Traditionally, crop growth conditions were assessed by comparing Normalized Difference Vegetation Index (NDVI) of the current year and past years at a pixel scale on the same calendar day. The assumption of this comparison is that the different years’ crops were at the same growing stage on the same day. However, this assumption is often violated in reality. This paper proposes to combine remotely sensed data and meteorological data to assess corn growth conditions at the same growth stages at county level. The proposed approach uses the active accumulated temperature (AAT) computed from Daymet, a daily weather data product, to align different years of NDVI time series at the same growth stages estimated from AATs. The study area covers Carroll County, Iowa. The best index slope extraction (BISE) method and Savitzky–Golay filter are used to filter noise and to reconstruct 11 years of corn growing season NDVI time series from 250 m MODIS daily surface reflectance data product (MOD09GQ). The corn growth stages are identified every year with precise Julian dates from AAT time series. The corn growth conditions are assessed based on the aligned growth stages. The validation of the assessed crop conditions is performed based on National Agricultural Statistics Service (NASS) reports. The study indicates that the crop condition assessment results based on aligned growth stages are consistent with the NASS reported results and they are more reliable than the results based on the same calendar days. The proposed method provides not only crop growth condition information but also crop phenology information. Potentially, it can help improve crop yield prediction since it can effectively measure crop growth changes with NDVI and AAT data. Full article

High-resolution meteorological data products are crucial for agrometeorological studies. Here, we study the accuracy of an important gridded dataset, the near-surface temperature dataset from the 5 km × 5 km resolution China dataset of meteorological forcing for land surface modeling (published by the Beijing Normal University). Using both the gridded dataset and the observed temperature data from 590 meteorological stations, we calculate nine universal meteorological indices (mean, maximum, and minimum temperatures of daily, monthly, and annual data) and five agricultural thermal indices (first frost day, last frost day, frost-free period, and ≥0 °C and ≥10 °C active accumulated temperature, i.e., AAT0 and AAT10) of the 11 temperature zones over mainland China. Then, for each meteorological index, we calculate the root mean square errors (RMSEs), correlation coefficient and climate trend rates of the two datasets. The results show that the RMSEs of these indices are usually lower in the north subtropical, mid-subtropical, south subtropical, marginal tropical and mid-tropical zones than in the plateau subfrigid, plateau temperate, and plateau subtropical mountains zones. Over mainland China, the AAT0, AAT10, and mean and maximum temperatures calculated from the gridded data show the same climate trends with those derived from the observed data, while the minimum temperature and its derivations (first frost day, last frost day, and frost-free period) show the opposite trends in many areas. Thus, the mean and maximum temperature data derived from the gridded dataset are applicable for studies in most parts of China, but caution should be taken when using the minimum temperature data. Full article

Given that chilling injury, which involves late spring cold and early autumn freezing, significantly affects maize growth in middle-latitude cold areas, a highly efficient cultivation technique combining suitable planting date (PD) and mulched drip irrigation is being studied to guarantee maize production. A field experiment for medium-mature variety “Xianyu 335” was conducted in 2015 to 2016 in Chifeng, Inner Mongolia, China, to explore the effects of PD on the active accumulated temperature (AAT) distribution and maize growth under mulched drip irrigation. Based on the dates (around May 1) of late spring cold occurring in the area, four PDs were designed, namely, April 20 (MD₁), May 2–3 (MD₂), May 12 (MD₃), and May 22 (MD₄), and a non-film mulching treatment (NM-D₂) was added on the second PD. Results indicated that: (1) the warming effect of film mulching effectively compensated for the lack of heat during the early stages of maize growth. Compared with that in NM-D₂, the soil temperature under mulching in MD₂ for the sowing–emergence and seedling stage increased by 14.3% and 7.6%, respectively, promoting maize emergence 4 days earlier and presenting 5.6% and 9.7% increases in emergence rate and grain yield, respectively; (2) the AAT reduction caused by PD delay was mainly observed in reproductive stage, which reached 96.6 °C for every 10 days of PD delay in this stage; (3) PD markedly affected maize growth process and yield, which were closely related to the chilling injury. The late spring cold slowed down the emergence or jointing for maize (under MD₁ and MD₂), but brought insignificant adverse effect on maize later growth and grain yield (16.1 and 15.9 Mg·ha⁻¹, respectively). While the maize in both MD₃ and MD₄ treatments suffered from early autumn freezing damage at the anthesis–maturity stages, resulting in shortening in reproductive period by 4–8 days and decrease in grain yield by 11.4–17.3% compared with those in MD₁ and MD₂; and (4) taking the typical date (May 1) of late spring cold occurring as the starting point, the grain yield penalty reached 8.5% for every 10 days of PD delay; for every 100 °C of AAT decrease during reproductive stage, the grain yield decreased by 6.1%. The conclusions offer certain reference values for maize cultivation in the same latitude areas with similar ecological environments. Full article