Regulation of subsoiling tillage on the grain filling characteristics of maize varieties from different eras

Grain filling is the key stage for achieving high grain yield. Subsoiling tillage, as an effective conservation tillage, has been widely used in the maize planting region of China. This study was conducted to explore the effects of subsoiling on the grain filling characteristics of maize varieties of different eras. Five typical maize varieties from different eras (1970s, 1980s, 1990s, 2000s and 2010s) were used as experimental materials with two tillage modalities (rotation tillage and subsoiling tillage). The characteristic parameters (Tmax: the time when the maximum grouting rate was reached, Wmax: the grain weight at the maximum filling rate, Rmax: the maximum grouting rate, P: the active grouting stage, Gmean: the average grouting rate; A: the ultimate growth mass) and rate parameters (T1: the grain filling duration of the gradually increasing stage, V1: the average grain filling rate of the gradually increasing stage, T2: he grain filling duration of the rapidly increasing stage, V2: the average grain filling rate of the rapidly increasing stage, T3: the grain filling duration of the slowly increasing stage, V3: the average grain filling rate of the slowly increasing stage) of grain filling of two tillage modalities were analyzed and compared. The results showed that the filling parameters closely correlated with the 100-kernel weight were significantly different among varieties from different eras, and the grain filling parameters of the 2010s variety were better than those of the other varieties, the P and Tmax prolonged by 4.06–19.25%, 5.88–27.53% respectively, the Rmax and Gmean improved by 5.68–14.81%, 4.76–12.82% and the Wmax increased by 10.14–32.58%. Moreover, the 2010s variety helped the V2 and V3 increase by 6.49–13.89%, 4.55–15.00%. In compared with rotation tillage, the grain yield of maize varieties from different eras increased by 4.28–7.15% under the subsoiling condition, while the 100-kernel weight increased by 3.53–5.06%. Under the same contrast conditions, subsoiling improved the Rmax, Wmax and Gmean by 1.23–4.86%, 4.01–5.96%, 0.25–2.50% respectively, delayed the Tmax by 4.04–5.80% and extended the P by 1.19–4.03%. These differences were major reasons for the significant increases in 100-kernel dry weight under the subsoiling condition. Moreover, subsoiling enhanced the V2 and V3 by 0.70–4.29%, 0.00–2.44%. The duration of each filling stage and filling rate of maize varieties from different eras showed different responses to subsoiling. Under the subsoiling condition, the average filling rate of the 1970–2010s varieties were improved by 1.18%, 0.34%, 0.57%, 1.57% and 2.69%. In the rapidly increasing period, the grain filling rate parameters of the 2010s variety were more sensitive to subsoiling than those of the other varieties. The rapidly increasing and slowly increasing period are the key period of grain filling. Since the 2010s variety and subsoiling all improve the grain filling rate parameters of two periods, we suggest that should select the variety with higher grain filling rate in the rapidly increasing and slowly increasing period, and combine subsoiling measures to improve the grain filling characteristic parameters of maize in production, so as to achieve the purpose of increasing 100 grain weight and yield.

Meta-QTLs, Ortho-metaQTLs and Candidate Genes for Grain Yield and Associated Traits in Wheat (Triticum Aestivum L.)

Meta-QTL analysis was conducted using 8,998 known QTLs, which included 2,852 major QTLs for grain yield (GY) and its following ten component/related traits: (i) grain weight (GWei), (ii) grain morphology related traits (GMRTs), (iii) grain number (GN), (iv) spikes related traits (SRTs), (v) plant height (PH), (vi) tiller number (TN), (vii) harvest index (HI), (viii) biomass yield (BY), (ix) days to heading/flowering and maturity (DTH/F/M) and (x) grain filling duration (GFD). The QTLs used for this study were retrieved from 230 reports (including 19 studies conducted in tetraploid wheat) that were based on 190 mapping populations (1999–2020). The study resulted in the identification of 141 meta-QTLs (MQTLs), with an average confidence interval (CI) of 1.37 cM (reduced 8.87 fold), the average CI in the initial QTLs being > 12.15 cM. As many as 63 MQTLs, each based on at least 10 initial QTLs were stable and robust; with 13 MQTLs are described as breeder’s QTLs. MQTLs were also utilized for the identification of 1,202 candidate genes (CGs), which included 18 known genes. The MQTLs were also found to contain 50 wheat genes that were homologous to 35 known yield-related genes from rice, barley, and maize. Further, the use of synteny and collinearity allowed the identification of 24 ortho-MQTLs which were common among the wheat, barley, rice, and maize. The results of the present study should prove useful for wheat breeding and future basic research in cereals including wheat, barley, rice, and maize. In particular, the breeder’s QTLs can be used for marker-assisted selection for grain yield and fine mapping leading to cloning of QTLs/genes for yield and related traits.

Responses of Grain Yield and Yield Related Parameters to Post-Heading Low-Temperature Stress in Japonica Rice

There is unprecedented increase in low-temperature stress (LTS) during post-heading stages in rice as a consequence of the recent climate changes. Quantifying the effect of LTS on yields is key to unraveling the impact of climatic changes on crop production, and therefore developing corresponding mitigation strategies. The present research was conducted to analyze and quantify the effect of post-heading LTS on rice yields as well as yield and grain filling related parameters. A two-year experiment was conducted during rice growing season of 2018 and 2019 using two Japonica cultivars (Huaidao 5 and Nanjing 46) with different low-temperature sensitivities, at four daily minimum/maximum temperature regimes of 21/27 °C (T1), 17/23 °C (T2), 13/19 °C (T3) and 9/15 °C (T4). These temperature treatments were performed for 3 (D1), 6 (D2) or 9 days (D3), at both flowering and grain filling stages. We found LTS for 3 days had no significant effect on grain yield, even when the daily mean temperature was as low as 12 °C. However, LTS of between 6 and 9 days at flowering but not at filling stage significantly reduced grain yield of both cultivars. Comparatively, Huaidao 5 was more cold tolerant than Nanjing 46. LTS at flowering and grain filling stages significantly reduced both maximum and mean grain filling rates. Moreover, LTS prolonged the grain filling duration of both cultivars. Additionally, there was a strong correlation between yield loss and spikelet fertility, spikelet weight at maturity, grain filling duration as well as mean and maximum grain filling rates under post-heading LTS (p < 0.001). Moreover, the effect of post-heading LTS on rice yield can be well quantified by integrating the canopy temperature (CT) based accumulated cold degree days (ACDDCT) with the response surface model. The findings of this research are useful in modeling rice productivity under LTS and for predicting rice productivity under future climates.

Meta-QTLs, Ortho-MetaQTLs and Candidate Genes for Grain yield and Associated Traits in Wheat (Triticum aestivum L.)

The present study involved meta-QTL analysis based on 8,998 QTLs, including 2,852 major QTLs for grain yield (GY) and its following ten component/related traits: (i) grain weight (GWei), (ii) grain morphology related traits (GMRTs), (iii) grain number (GN), (iv) spikes related traits (SRTs), (v) plant height (PH), (vi) tiller number (TN), (vii) harvest index (HI), (viii) biomass yield (BY), (ix) days to heading/flowering and maturity (DTH/F/M) and (x) grain filling duration (GFD). The QTLs used for this study were retrieved from 230 reports involving 190 mapping populations (1999–2020), which also included 19 studies involving durum wheat. As many as 141 meta-QTLs were obtained with an average confidence interval of 1.37 cM (reduced 8.87 fold), the average interval in the original QTL being > 12.15 cM. As many as 63 MQTLs, each based on at least 10 original QTLs were considered to be the most stable and robust with thirteen identified as breeder’s meta-QTL. Meta-QTLs (MQTLs) were also utilized for identification of as many as 1,202 candidate genes (CGs), which also included 18 known genes. Based on a comparative genomics strategy, a total of 50 wheat homologues of 35 rice, barley and maize yield-related genes were also detected in these MQTL regions. Moreover, taking the advantage of synteny, a total of 24 ortho-MQTLs were detected at co-linear regions between wheat with barley, rice and maize. The present study is the most comprehensive till date, and first of its kind in providing stable and robust MQTLs and ortho-MQTLs, thus providing useful information for future basic studies and for marker-assisted breeding for yield and its component traits in wheat.

Characterization and Grouping of All Primary Branches at Various Positions on a Rice Panicle Based on Grain Growth Dynamics

Grain filling can directly influence rice yield. However, there is limited information on the growth relationship among grains at different positions on the entire panicle during grain filling. In this study, field experiments were conducted in 2014–2015 to compare the growth dynamics of grains at various positions for two rice cultivars (Nongle 1 and Guifeng 2). The results showed that a high similarity and a slow–fast–slow trend of dry-matter accumulation occurred in all primary branches. However, the maximum grain growth rates of the top primary branches were 86% and 44% higher than basal primary branches of Nongle 1 and Guifeng 2, respectively. Similarly, the maximum final grain weights were 32% and 18% greater in the top primary branches than in the basal primary branches of Nongle 1 and Guifeng 2, respectively. In contrast, the active grain filling duration was 1.5 and 1.3 times longer in the basal primary branches than the top primary branches of Nongle 1 and Guifeng 2, respectively. The time to reach the maximum rate of grain growth of the basal primary branches for Nongle 1 and Guifeng 2 was 2.2 and 2.5 times longer than those of the top primary branches, respectively. Based on cluster analysis of growth characteristics of all primary branches, Group I (superior primary-branches) was considered to be the fastest for grain filling and greatest for dry matter weight, followed by Group II (medium primary-branches). The poorest growth occurred in Group III (inferior primary-branches). Therefore, the yield of poor-filling grains at the basal panicle could be achieved primarily by improving the growth of Group III.

Effects of drought stress on growth, grain filling duration, yield and quality attributes of barley (Hordeum vulgare L.)

A pot experiment was conducted to investigate the effect of drought stress at start of anthesis (applied by adjusting the field capacities at 100, 50 and 30%) on barley growth, grain filling duration, grain shape, yield and quality attributes. The effect of drought stress was more prominent on plant fresh biomass accumulation, grain yield and grain filling duration. However, it produced non-significant effect on total number of tillers and grain protein contents. With the increasing intensity of drought stress, barley growth and yield traits significantly diminished. Water stress gradually shortened the plant height and biomass accumulation but the difference was more prominent in fresh biomass accumulation (– 45%) over dry biomass accumulation. The field capacity of 30% caused 29 - 41% reduction in leaf chlorophyll content and 10 - 27% in grain quality traits. Root fresh and dry biomass accumulation decreased by drought stress while root length increased. Drought stress produced uneven grain size that resulted in lower grain yield (42%) specially at 30% field capacity. This reduction in yield was also due to the decreased grain filling duration (38 d) at 30% field capacity as compared to 100% field capacity. So, it may be concluded that drought stress affected barley yield through impaired grain development and grain filling duration. The results of present study are satisfactory and needed further exploration about the physiological mechanism and management strategies to overcome drought stress related yield losses in barley crop.

Identification of genotypes and marker validation for grain filling rate and grain filling duration in wheat under conservation agriculture

Increase in ambient temperature beyond threshold level as predicted by global climate models may impact wheat production severely in India if it happens during grain filling stage. Grain filling rate (GFR) and grain filling duration (GFD) are critical determinant for final grain yield realization in wheat. GFR in wheat follow a slow-fast-slow pattern, however, wheat genotypes may have quantitative differences in this pattern. Ninty six diverse wheat genotypes were evaluated for GFR in two phases i.e. during first 20 days after anthesis and thereafter up to physiological maturity and grain filling duration. Out of 96 genotypes, six namely, G958, G1203, G1219, G1275, HD2985 and HDCSW18 were having high GFR during initial phase while seven genotypes viz., G949, G1081, G1124, G1159, G1204, HD3059 and HD2380 exhibited high GFR at terminal phase of grain development. Genotypes, G1263, G1207, G1423 along with some of the released varieties, HD2285, WH1105 and HD2864 were having higher GFD. Correlation between the two traits were not significant (r = -0.17959). ANOVA for GFR and GFD indicated highly significant variability among the genotypes. QTLs identified for GFR and GFD elsewhere were validated in Indian breeding material under conservation agriculture. Two SSR markers viz., XCfd42 and Xwmc500 explained about 6% and 1% variation for GFR, respectively. Similarly, already reported marker Xwmc382 was able to explain about 8% of variation for GFD in the Indian breeding material. It has been postulated from the study that by crossing the genotypes with high GFR in different grain growth stages like HD CSW 18 and HD 3059, genotypes with consistently high grain filling rate throughout the grain growth stage can be developed. The markers XCfd42 and Xwmc 382 can be further explored for fine mapping to integrate in the breeding programme for selection.

Cluster Analysis of Wheat (Triticum aestivum L.) Genotypes Based Upon Response to Terminal Heat Stress

High temperature stress adversely affects plant physiological processes; limiting plant growth and reducing grain yield. Heat stress is often encountered due to late sowing of wheat in winter. Fifty wheat genotypes were studied for days to maturity, thousand kernel weight, grain filling duration, grain filling rate, and SPAD reading in alpha lattice design at Agriculture and Forestry University at Rampur, Chitwan, Nepal with the objective to identify superior heat stress tolerant varieties after clustering them based on their response to heat stress. All the genotypes were clustered using reduction in thousand kernel weight, heat susceptibility index for thousand kernel weight, heat susceptibility index for grain filling duration, area under SPAD retreat curve, maturity duration under normal condition, maturity duration at late sown condition, grain filling rate under normal condition and grain filling rate at late sown condition as variables and dendogram was prepared. UPGMA revealed that these genotypes formed five distinct clusters. The resistant genotypes and susceptible genotypes formed different clusters. The member of cluster 3 was found to be tolerant to terminal heat stress where as members of cluster 2 were found most susceptible to terminal heat stress. From this study genotype BAJ #1/SUP152 was found most tolerant to terminal heat stress. The genotypes belonging to superior cluster could be considered very useful in developing heat tolerant variety and other breeding activities.Int. J. Appl. Sci. Biotechnol. Vol 5(2): 188-193