Deciphering the Environmental Impacts on Rice Quality for Different Rice Cultivated Areas

Abstract

Background: Rice (Oryza sativa L.) is cultivated in a wide range of climatic conditions, and is one of mankind's major staple foods. The interaction of environmental factors with genotype effects major agronomic traits such as yield, quality, and resistance in rice. However, studies on the environmental factors affecting agronomic traits are often difficult to conduct because most environmental factors are dynamic and constantly changing. Results: A series of recombinant inbred lines (RILs) derived from an indica/japonica cross were planted into four typical rice cultivated areas arranging from latitude N22°to N42°. The environmental data from the heading to mature (45 days) stages were recorded for each RIL in the four areas. We determined that light, temperature, and humidity significantly affected the milling quality and cooking quality overall the four areas. Within each area, these environmental factors mainly affected the head rice ratio, grain length, alkali consumption, and amylose and protein content. Moreover, the effect of these environmental factors dynamically changed from heading to mature stage. Compared to light and humidity, temperature was more stable and predictable, and night temperature showed a stronger correlation efficiency to cooking quality than day temperature, and the daily temperature range had contrary effects compared to day and night temperature on grain quality. Conclusions: The present study evaluated the critical phase during the grain filling stage by calculating the dynamic changes of correlation efficiency between the quality traits and climate parameters. Our findings suggest that the sowing date could be adjusted to improve rice quality so as to adjust for environmental changes.

Genome sequencing of rice subspecies and genetic analysis of recombinant lines reveals regional yield- and quality-associated loci

“…In the wild-type plants, although Hd3a mRNA is highly expressed at day lengths ≤ 13 h, its expression markedly decreased to about one-tenth of the expression, at a day length of 13.5 h and became undetectable at day lengths of ≥ 14 h [ 21 ]. Our previous study has monitored day length and the temperature during the whole growth season in all three areas in 2016 [ 22 ]. We observed RIL growth under long-day conditions for the whole growing season in SY and JS, and the day length even exceeded 15 h in SY at July.…”

“…Thus, we assumed that the photoperiod-sensitive genes play supporting roles in SZ as it maintains optimal day length possibly for the entire growth season, and other factors, such as temperature, play a lead role in establishing heading date. Then, we analyzed the relationship between temperature and heading date in SZ using the method described in our previous study [ 22 ]. We found that temperature has a strong correlation with heading date, and this correlation exhibited a positive/negative change by a 10-day rhythm (Additional file 14 : Figure S8).…”

“…Field experiments were conducted in three typical rice cultivated areas: the Agricultural Genomics Institute at Shenzhen (SZ; N22°, E114°), the sub-base of China National Hybrid Rice R&D Center in Jiangsu Province (JS; N32°, E120°), and the Rice Research Institute of Shenyang Agricultural University (SY; N41°, E123°) for two growing seasons during 2015–2016. The cultivation method and field management were described in our previous report [ 22 ]. We harvested the field examination plants at 45 days after heading for each line in each of the three areas.…”

“…A total of 20 plants from the middle rows were harvested for each line. The quality measurement was conducted as described in our previous study [ 22 ]. We only used the 2016 data in the present study, as the 2 years of data showed similar trends and are highly correlated.…”

How Does the Control of Grain Purchase Price Affect the Sustainability of the National Grain Industry? One Empirical Study from China

“…Through the analysis of existing studies on the MPP policy, it is found that comparing the change of grain-cultivated areas before and after the policy implementation is the most commonly used standard to measure the implementation effect of the MPP policy, because the cultivated area is the key factor determining the grain output [31]. However, there are many natural and human factors affecting the area of grain cultivation [32], so it is unfair to evaluate the MPP policy effect from this standard only.…”