稻米外观与加工品质对大气CO2浓度升高的响应

doi:10.16819/j.1001-7216.2019.8134

摘要/Abstract

摘要：

【目的】大气CO₂浓度升高会降低水稻的外观与加工品质。为探明其下降机制并予以缓解,【方法】采用开放式大气CO₂浓度升高(FACE)平台、两种栽培品种及其三种不同的基因调控遗传材料 (中花11及其蒸腾调节材料ZmK2.1-15、ZmK2.1-20、OsKAT3-26、OsKAT3-30; 中花11及其促冠根生长材料ERF3-7和ERF3-12; 日本晴及其促硝酸盐吸收材料NIL),研究稻米外观与加工品质对CO₂浓度升高的响应。【结果】稻米外观品质与加工品质对CO₂浓度升高的响应因品种不同而异。CO₂浓度升高下,中花11的垩白粒率和垩白度增加9.2%和4.4%,整精米率降低5.3%;而日本晴的垩白粒率和垩白度降低11.1%和7.9%,整精米率提升9.8%。蒸腾调节材料显著改善了CO₂浓度升高对中花11外观与外观品质的负面效应,与当前CO₂浓度相比,CO₂浓度升高,ZmK2.1-15、ZmK2.1-20、OsKAT3-26、OsKAT3-30的垩白粒率相对变化量为-2.7%、-16.3%、-14.8%,+7.4%,垩白度为-8.7%、-22.3%、-15.1%、-3.0%,整精米率为+2.1%、+6.4%、+3.6%、-7.0%。促冠根生长材料加大了CO₂浓度升高对中花11号外观与加工品质的负面效应,ERF3-7、ERF3-12的垩白粒率在CO₂浓度升高下分别增加17.7%和11.5%,垩白度增加34.4%和19.1%,整精米率分别降低10.1%和0.8%。促硝酸盐吸收材料(NIL)的垩白粒率和垩白度在CO₂浓度升高下无明显变化,整精米率下降4.2%。NIL的外观品质较日本晴明显改善,CO₂浓度升高下垩白粒率和垩白度分别下降16.5%和17.9%,当前CO₂浓度条件下分别下降26.3%和28.9%。【结论】未来CO₂浓度升高条件下,通过基因改良促进水稻蒸腾作用和硝酸盐吸收是提升稻米外观与加工品质的有效途径之一。

关键词: CO₂浓度升高, 水稻, 外观品质, 加工品质

Abstract:

【Objective】Rice appearance and processing quality will be reduced by elevated atmosphere CO₂ concentration ([CO₂]). To ascertain the mechanism behind this decline and then alleviate it, 【Method】we used a Free-air Carbon Dioxide Enrichment (FACE) facility, two kinds of cultivars and its three kinds of genetically modified materials (Zhonghua 11 and its transpiration-promoting genetic materials, ZmK2.1-15, ZmK2.1-20, OsKAT3-26, OsKAT3-30; Zhonghua 11 and its crown root-promoting genetic materials, ERF3-7 and ERF3-12; Nipponbare and its nitrate absorption-promoting genetic material, NIL) to study the responses of appearance and processing quality of different rice genetic materials to elevated [CO₂]. 【Results】The responses of rice appearance and processing quality to elevated [CO₂] varied among these genotypes. The chalky grain percentage and chalkiness degree of Zhonghua11 increased by 9.2% and 4.4% under elevated [CO₂] compared with ambient [CO₂], and head rice percentage decreased by 5.3%, while the chalky grain percentage and chalkiness degree of Nipponbare decreased by 11.1% and 7.9%, and head rice percentage increased by 9.8%. Transpiration-promoting genetic materials significantly mitigated the negative effect of elevated [CO₂] on the appearance and processing quality of Zhonghua11. As compared with ambient [CO₂], the changes in chalky grain percentages for ZmK2.1-15, ZmK2.1-20, OsKAT3-26 and OsKAT3-30 under elevated [CO₂] were -2.7%, -16.3%, -14.8%, +7.4%, and that of chalkiness degree was -8.7%, -22.3%, -15.1%, -3.0%, and that of head rice percentage was +2.1%, +6.4%, +3.6%, -7.0%. Crown root-promoting genetic materials exacerbated the negative impact of elevated [CO₂] on the appearance and processing quality of Zhonghua 11, with the chalky grain percentage increased by 17.7% and 11.5% under elevated [CO₂], and the chalkiness degree increased by 34.4% and 19.1%, head rice percentage decreased by 10.1% and 0.8%, respectively. The chalky grain percentage and chalkiness degree of nitrate absorption-promoting material (NIL) did not change significantly at elevated [CO₂], and the head rice percentage decreased by 4.2%. The appearance quality of NIL was significantly improved as compared with that of Nipponbare, with the chalky grain percentage and chalkiness degree decreased by 16.5% and 17.9% under elevated [CO₂], and 26.3% and 28.9% under ambient [CO₂]. 【Conclusion】The promotion of transpiration and nitrate absorption through genetic regulation could be one of the effective ways to improve the appearance and processing quality of rice under elevated [CO₂] in the future.

Key words: elevated CO₂ concentration, rice, appearance quality, milling quality

中图分类号:

S181
S511.01

王东明, 陶冶, 朱建国, 刘钢, 朱春梧. 稻米外观与加工品质对大气CO₂浓度升高的响应[J]. 中国水稻科学, 2019, 33(4): 338-346.

Dongming WANG, Ye TAO, Jianguo ZHU, Gang LIU, Chunwu ZHU. Responses of Rice Appearance and Processing Quality to Elevated Atmospheric CO₂Concentration[J]. Chinese Journal OF Rice Science, 2019, 33(4): 338-346.

图/表 5

参考文献 32

[1]	Dlugokencky D, Tans P.Globally Averaged Marine Surface Annual Mean Data.NOAA/ESRL, 2017.
[2]	International Energy Agency.Global Energy and CO2 Status Report 2017. GECO, 2018.
[3]	The Core Writing Team, Pachauri R K, Meyer L. Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. IPCC, 2014.
[4]	Lobell D B, Schlenker W, Costaroberts J.Climate trends and global crop production Since 1980.Science, 2011, 333(6042): 616-620.
[5]	Zhu C W, Zhu J G, Cao J, Jiang Q, Liu G, Ziska L H.Biochemical and molecular characteristics of leaf photosynthesis and relative seed yield of two contrasting rice cultivars in response to elevated [CO2].J Exp Bot, 2014, 65(20): 6049-6056.
[6]	Yang L X, Wang Y L, Dong G C, Gu H, Huang J Y, Zhu J G, Yang H J, Liu G, Han Y.The impact of free-air CO2 enrichment (FACE) and nitrogen supply on grain quality of rice.Field Crops Res, 2007, 102(2): 128-140.
[7]	Myers S S, Zanobetti A, Kloog I, Huybers P J, Leakey A D B, Bloom A J, Carlisle E, Dietterich L H, Fitzgerald G J, Hasegawa T, Holbrook M, Nelson R L, Ottman M J, Raboy V, Sakai H, Sartor K, Schwartz J, Seneweera S, Tausz M, Usui Y. Rising CO2 threatens human nutrition.Nature, 2014, 510(7503): 139-142.
[8]	Zhu C W, Kobayashi K, Loladze I, Zhu J G, Jiang Q, Xu X, Liu G, Seneweera S, Ebi K L, Drewnowski A, Fukagawa N K, Ziska L H. Carbon dioxide (CO2) levels this century will alter the protein, micronutrients, and vitamin content of rice grains with potential health consequences for the poorest rice-dependent countries. Sci Adv, 2018, 4(5): eaaq1012.
[9]	Smith M R, Myers S S.Impact of anthropogenic CO2 emissions on global human nutrition.Nat Clim Chan, 2018, 8(9): 834-839.
[10]	Usui Y, Sakai H, Tokida T, Nakamura H, Nakagawa H, Hasegawa T.Rice grain yield and quality responses to free-air CO2 enrichment combined with soil and water warming.Glob Chan Biol, 2016, 22(3): 1256-1270.
[11]	董桂春, 王余龙, 黄建晔, 杨洪建, 顾晖, 彭斌, 居静, 杨连新, 朱建国, 单玉华. 稻米品质性状对开放式空气二氧化碳浓度增高的响应. 应用生态学报, 2004, 15(7): 1217-1222.
	Dong G C, Wang Y L, Huang J Y, Yang H J, Gu H, Peng B, Ju J, Yang L X, Zhu J G, Shan Y H.Response of rice grain quality traits to free-air CO2 enrichment.Chin J Appl Ecol, 2004, 15(7): 1217-1222. (in Chinese with English abstract)
[12]	常二华, 张耗, 张慎凤, 王志琴, 杨建昌. 结实期氮磷营养水平对水稻根系分泌物的影响及其与稻米品质的关系. 作物学报, 2007, 33(12): 1949-1959.
	Chang E H, Zhang H, Zhang S F, Wang Z Q, Yang J C.Effects of nitrogen and phosphorus on the root exudates during grain filling and their relations with grain quality of rice.Acta Agron Sin, 2007, 33(12): 1949-1959. (in Chinese with English abstract)
[13]	全国明, 章家恩, 许荣宝, 谢利, 刘金苓. 环境生态因子对稻米品质的影响研究进展. 中国农学通报, 2006, 22(4): 158-162.
	Quan G M, Zhang J E, Xu R B, Xie L, Liu J L.Review on the effect of environmental factors on rice quality.Chin Agric Sci Bull, 2006, 22(4): 158-162. (in Chinese with English abstract)
[14]	Taub D R, Miller B, Allen H.Effects of elevated CO2 on the protein concentration of food crops: A meta-analysis.Glob Chan Biol, 2008, 14(3): 565-575.
[15]	Mcgrath J M, Lobell D B.Reduction of transpiration and altered nutrient allocation contribute to nutrient decline of crops grown in elevated CO2 concentrations.Plant Cell & Environ, 2013, 36(3): 697-705.
[16]	Yoshimoto M, Oue H, Takahashi N, Kobayashi K.The effects of FACE (free-air CO2 enrichment) on temperatures and transpiration of rice panicles at flowering stage.J Agric Meteorol, 2005, 60(5): 597-600.
[17]	杨洪建, 杨连新, 刘红江, 黄建晔, 董桂春, 朱建国, 王余龙. FACE对水稻根系及产量的影响. 作物学报, 2005, 31(9): 1221-1226.
	Yang H J, Yang L X, Liu H J, Huang J Y, Dong G C, Zhu J G, Wang Y L.Effects of free-air CO2 enrichment on root system and yield in rice (Oryza sativa L.).Acta Agron Sin, 2005, 31(9): 1221-1226. (in Chinese with English abstract)
[18]	林赵淼, 郑德益, 张新城, 刘正辉, 王绍华, 丁艳锋. 稻米垩白形成的生理与分子机制研究进展. 中国稻米, 2015, 21(4): 14-19.
	Lin Z M, Zheng D Y, Zhang X C, Liu Z H, Wang S H, Ding Y F.Research advances in the physiological and molecular mechanisms of chalkiness formation in rice.China Rice, 2015, 21(4): 14-19. (in Chinese with English abstract)
[19]	Su Y H, North H, Grignon C, Thibaud J B, Sentenac H, Very A A.Regulation by external K+ in a maize inward shaker channel targets transport activity in the high concentration range.Plant Cell, 2005, 17(5): 1532-1548.
[20]	Wang L, Yang S Y, Guo M Y, Huang Y N, Sentenac H, Very A A, Su Y H.The S1-S2 linker determines the distinct pH sensitivity between ZmK2.1 and KAT1.Plant J, 2016, 85(5): 675-685.
[21]	Zhao Y, Cheng S F, Song Y L, Huang Y L, Zhou S L, Liu X Y, Zhou D X.The Interaction between rice ERF3 and WOX11 promotes crown root development by regulating gene expression involved in cytokinin signaling.Plant Cell, 2015, 27(9): 2469-2483.
[22]	Hu B, Wang W, Ou S J, Tang J Y, Li H, Che R H, Zhang Z H, Chai X Y, Wang H R, Wang Y Q, Liang C Z, Liu L C, Piao Z Z, Deng Q Y, Deng K, Xu C, Liang Y, Zhang L H, Li L G, Chu C C.Variation in NRT1.1B contributes to nitrate-use divergence between rice subspecies.Nat Genet, 2015, 47(7): 834-840.
[23]	Wei W, Hu B, Yuan D, Liu Y Q, Che R H, Hu Y C, Ou S J, Liu Y X, Zhang Z H, Wang H R, Li H, Jiang Z M, Zhang Z L, Gao X K, Qiu Y H, Meng X B, Bai Y, Liang Y, Wang Y Q, Zhang L H, Li L G, Sodmergen, Jing H C, Li J Y, Chu C C. Expression of the nitrate transporter gene OsNRT1.1A/OsNPF6.3 confers high yield and early maturation in rice.Plant Cell, 2018, 30(3): 638-651.
[24]	Yang L X, Huang J Y, Yang H J, Dong G C, Liu H J, Liu G, Zhu J G, Wang Y L.Seasonal changes in the effects of free-air CO2 enrichment (FACE) on nitrogen (N) uptake and utilization of rice at three levels of N fertilization.Field Crops Res, 2007, 100(2): 189-199.
[25]	黄建晔, 杨连新, 杨洪建, 刘红江, 董桂春, 朱建国, 王余龙.开放式空气CO2浓度增加对水稻生育期的影响及其原因分析. 作物学报, 2005, 31(7): 882-887.
	Huang J Y, Yang L X, Yang H J, Liu H J, Dong G C, Zhu J G, Wang Y L.Effects of free-air CO2 enrichment (FACE) on growth duration of rice (Oryza sativa L.) and its cause.Acta Agron Sin, 2005, 31(7): 882-887. (in Chinese with English abstract)
[26]	Siebert S, Ewert F, Rezaei E E, Kage H, Gras R.Impact of heat stress on crop yield: On the importance of considering canopy temperature.Environm Res Lett, 2014, 9(4): 044012.
[27]	罗卫红, Yoshimoto M, 戴剑峰, 朱建国, 韩勇, 刘钢. 开放式空气CO2浓度增高对水稻冠层微气候的影响. 应用生态学报, 2002, 13(10): 1235-1239.
	Luo W, Yoshimoto M, Dai J, Zhu J G, Han Y, Liu G.Effects of free-air CO2 enrichment on rice canopy microclimate.Chin J Appl Ecol, 2002, 13(10): 1235-1239. (in Chinese with English abstract)
[28]	Kobayashi A, Bao G L, Ye S H, Tomita K.Detection of quantitative trait loci for white-back and basal-white kernels under high temperature stress in japonica rice varieties.Breeding Sci, 2007, 57: 107-116.
[29]	庞静, 朱建国, 谢祖彬, 刘钢, 陈改萍. CO2浓度升高条件下水稻蒸腾与N吸收的关系. 中国水稻科学, 2006, 20(2): 205-209.
	Pang J, Zhu J G, Xie Z B, Liu G, Chen G P.Relations between transpiration and N uptake of rice grown in elevated air carbon dioxide concentration.Chin J Rice Sci, 2006, 20(2): 205-209. (in Chinese with English abstract)
[30]	徐习. 高浓度CO2条件下提升水稻增产效应的初步研究.南京: 中国科学院南京土壤研究, 2017.
	Xu X.Preliminary study on raising rice yield response to elevated carbon dioxide. Nanjing: Institute of Soil Science, Chinese Academy of Sciences, 2017. (in Chinese with English abstract)
[31]	Lawlor D W.Carbon and nitrogen assimilation in relation to yield: Mechanisms are the key to understanding production systems.J Exper Bot, 2002, 53(370): 773-787.
[32]	Ambardekar A A, Siebenmorgen T J, Counce P A, Lanning S B, Mauromoustakos A.Impact of field-scale nighttime air temperatures during kernel development on rice milling quality.Field Crops Res, 2011, 122(3): 179-185.

材料 Material	CO₂处理 CO₂treatment	糙米率 Brown rice percentage/%	精米率 Milled rice percentage/%	整精米率 Head rice percentage/%	垩白粒率 Chalky grain percentage/%	垩白度 Chalkiness degree/%
中花11 Zhonghua 11	FACE	82.9±0.7	72.3±1.2	68.0±1.2	13.2±0.9	5.8±0.7
	Ambient	82.6±0.7	72.5±0.4	70.2±0.5	12.1±1.7	5.6±0.7
	Change	0.4	-0.4	-3.1	8.9	4.2
ZmK2.1-15	FACE	82.5±1.2	71.9±0.4	68.0±2.6	42.5±1.5	16.3±0.3
	Ambient	81.8±0.2	71.4±0.8	66.6±3.4	43.7±4.3	17.8±2.1
	Change	0.8	0.8	2.1	-2.7	-8.7
ZmK2.1-20	FACE	83.0±0.2	72.7±0.2	68.5±0.8	39.0±0.6	15.7±0.6
	Ambient	81.3±1.2	71.3±1.7	64.4±2.0	46.6±6.9	20.2±3.5
	Change	2.1	1.9	6.4	-16.3	-22.3
OsKAT3-26	FACE	82.5±0.5	72.3±0.2	70.9±0.1	24.0±3.7	9.9±1.2
	Ambient	82.0±0.8	72.3±1.0	68.5±0.7	28.2±3.5	11.6±1.5
	Change	0.7	0.0	3.6	-14.8	-15.1
OsKAT3-30	FACE	80.1±1.5	68.3±4.5	62.1±3.2	33.9±5.5	13.7±1.2
	Ambient	80.9±0.8	70.5±1.4	66.8±2.4	31.6±4.7	14.1±1.0
	Change	-0.9	-3.1	-7.0	7.4	-3.0
方差分析Analysis of variance
变异来源Source of variation
材料Material(M)		*	0.118	***	***	***
CO₂浓度([CO₂])		0.383	0.805	0.746	0.167	0.127
M×[CO₂]		0.150	0.498	0.101	0.080	0.106

材料 Material	CO₂处理 CO₂treatment	糙米率 Brown rice percentage/%	精米率 Milled rice percentage/%	整精米率 Head rice percentage/%	垩白粒率 Chalky grain percentage/%	垩白度 Chalkiness degree/%
中花11 Zhonghua 11	FACE	82.9±0.7	72.3±1.2	68.0±1.2	13.2±0.9	5.8±0.7
	Ambient	82.6±0.7	72.5±0.4	70.2±0.5	12.1±1.7	5.6±0.7
	Change	0.4	-0.4	-3.1	8.9	4.2
ZmK2.1-15	FACE	82.5±1.2	71.9±0.4	68.0±2.6	42.5±1.5	16.3±0.3
	Ambient	81.8±0.2	71.4±0.8	66.6±3.4	43.7±4.3	17.8±2.1
	Change	0.8	0.8	2.1	-2.7	-8.7
ZmK2.1-20	FACE	83.0±0.2	72.7±0.2	68.5±0.8	39.0±0.6	15.7±0.6
	Ambient	81.3±1.2	71.3±1.7	64.4±2.0	46.6±6.9	20.2±3.5
	Change	2.1	1.9	6.4	-16.3	-22.3
OsKAT3-26	FACE	82.5±0.5	72.3±0.2	70.9±0.1	24.0±3.7	9.9±1.2
	Ambient	82.0±0.8	72.3±1.0	68.5±0.7	28.2±3.5	11.6±1.5
	Change	0.7	0.0	3.6	-14.8	-15.1
OsKAT3-30	FACE	80.1±1.5	68.3±4.5	62.1±3.2	33.9±5.5	13.7±1.2
	Ambient	80.9±0.8	70.5±1.4	66.8±2.4	31.6±4.7	14.1±1.0
	Change	-0.9	-3.1	-7.0	7.4	-3.0
方差分析Analysis of variance
变异来源Source of variation
材料Material(M)		*	0.118	***	***	***
CO₂浓度([CO₂])		0.383	0.805	0.746	0.167	0.127
M×[CO₂]		0.150	0.498	0.101	0.080	0.106

年份 Year	材料 Material	CO₂处理 CO₂treatment	糙米率 Brown rice percentage/%	精米率 Milled rice percentage/%	整精米率 Head rice percentage/%	垩白粒率 Chalky grain percentage/%	垩白度 Chalkiness degree/%
2016	中花11	FACE	80.8±0.6	69.2±0.4	59.5±3.4	32.6±0.8	11.7±0.9
	Zhonghua 11	Ambient	80.5±0.1	68.2±0.2	65.5±0.3	29.4±0.1	9.7±0.1
		Change	0.4	1.5	-9.1	11.1	21.5
	ERF3-7	FACE	78.2±1.1	66.4±1.0	54.9±1.9	78.2±0.9	40.2±0.6
		Ambient	78.2±0.4	63.0±0.7	60.3±0.3	65.3±1.4	29.2±0.7
		Change	-0.1	5.3	-9.0	19.8	37.7
	ERF3-12	FACE	80.6±1.8	67.3±2.6	59.1±1.5	83.2±0.5	46.3±2.0
		Ambient	79.9±1.7	64.9±5.4	57.6±0.4	77.0±1.1	38.9±1.2
		Change	0.9	3.7	2.7	8.1	19.1
2017	中花11	FACE	80.9±0.3	69.4±2.0	60.1±0.7	10.3±0.6	2.9±0.5
	Zhonghua 11	Ambient	81.2±0.6	71.0±1.2	62.4±1.4	9.9±0.8	4.3±0.8
		Change	-0.3	-2.3	-3.7	4.0	-33.2
	ERF3-7	FACE	77.1±0.3	63.8±1.0	51.3±1.2	30.3±2.6	11.1±1.3
		Ambient	78.1±1.0	64.5±1.1	57.8±1.8	26.9±1.0	9.0±0.2
		Change	-1.2	-1.1	-11.2	12.4	23.6
	ERF3-12	FACE	78.2±0.6	65.4±1.7	53.5±2.2	60.2±1.8	24.9±0.9
		Ambient	78.9±2.7	63.8±3.3	56.0±1.6	51.6±1.8	20.9±1.3
		Change	-0.9	2.4	-4.4	16.7	19.1
方差分析Analysis of variance
变异来源Source of variation
年际Year(Y)			*	0.780	*	***	***
材料Material(M)			*	0.062	***	***	***
CO₂浓度([CO₂])			0.505	0.353	*	*	**
Y×M			*	0.056	0.451	***	***
Y×[CO₂]			0.204	0.101	0.641	0.128	*
M×[CO₂]			0.688	0.078	**	**	**
Y×M×[CO₂]			0.845	0.306	0.110	**	*

年份 Year	材料 Material	CO₂处理 CO₂treatment	糙米率 Brown rice percentage/%	精米率 Milled rice percentage/%	整精米率 Head rice percentage/%	垩白粒率 Chalky grain percentage/%	垩白度 Chalkiness degree/%
2016	中花11	FACE	80.8±0.6	69.2±0.4	59.5±3.4	32.6±0.8	11.7±0.9
	Zhonghua 11	Ambient	80.5±0.1	68.2±0.2	65.5±0.3	29.4±0.1	9.7±0.1
		Change	0.4	1.5	-9.1	11.1	21.5
	ERF3-7	FACE	78.2±1.1	66.4±1.0	54.9±1.9	78.2±0.9	40.2±0.6
		Ambient	78.2±0.4	63.0±0.7	60.3±0.3	65.3±1.4	29.2±0.7
		Change	-0.1	5.3	-9.0	19.8	37.7
	ERF3-12	FACE	80.6±1.8	67.3±2.6	59.1±1.5	83.2±0.5	46.3±2.0
		Ambient	79.9±1.7	64.9±5.4	57.6±0.4	77.0±1.1	38.9±1.2
		Change	0.9	3.7	2.7	8.1	19.1
2017	中花11	FACE	80.9±0.3	69.4±2.0	60.1±0.7	10.3±0.6	2.9±0.5
	Zhonghua 11	Ambient	81.2±0.6	71.0±1.2	62.4±1.4	9.9±0.8	4.3±0.8
		Change	-0.3	-2.3	-3.7	4.0	-33.2
	ERF3-7	FACE	77.1±0.3	63.8±1.0	51.3±1.2	30.3±2.6	11.1±1.3
		Ambient	78.1±1.0	64.5±1.1	57.8±1.8	26.9±1.0	9.0±0.2
		Change	-1.2	-1.1	-11.2	12.4	23.6
	ERF3-12	FACE	78.2±0.6	65.4±1.7	53.5±2.2	60.2±1.8	24.9±0.9
		Ambient	78.9±2.7	63.8±3.3	56.0±1.6	51.6±1.8	20.9±1.3
		Change	-0.9	2.4	-4.4	16.7	19.1
方差分析Analysis of variance
变异来源Source of variation
年际Year(Y)			*	0.780	*	***	***
材料Material(M)			*	0.062	***	***	***
CO₂浓度([CO₂])			0.505	0.353	*	*	**
Y×M			*	0.056	0.451	***	***
Y×[CO₂]			0.204	0.101	0.641	0.128	*
M×[CO₂]			0.688	0.078	**	**	**
Y×M×[CO₂]			0.845	0.306	0.110	**	*

年份 Year	材料 Material	CO₂处理 CO₂treatment		精米率 Milled rice percentage/%	整精米率 Head rice percentage/%	垩白粒率 Chalky grain percentage/%	垩白度 Chalkiness degree/%
2016	日本晴	FACE	71.4±0.3	57.9±1.0	53.8±1.8	12.5±0.9	3.8±0.2
	Nipponbare	Ambient	75.0±4.7	60.9±3.6	48.8±4.9	13.4±1.0	4.1±0.1
		Change	-4.9	-4.8	10.3	-6.9	-6.6
	NIL	FACE	78.0±1.4	63.8±0.8	56.8±2.0	8.6±0.2	2.7±0.2
		Ambient	79.5±0.4	64.7±0.3	62.1±0.6	8.1±0.3	2.2±0.2
		Change	-1.8	-1.3	-8.6	6.8	21.8
2017	日本晴	FACE	81.8±0.4	68.7±0.2	67.3±0.6	24.3±1.6	8.2±0.7
	Nipponbare	Ambient	81.5±0.3	68.5±0.3	61.6±1.0	28.0±0.3	8.9±0.2
		Change	0.4	0.3	9.3	-13.1	-8.5
	NIL	FACE	81.5±0.4	68.0±0.9	64.7±1.7	22.1±5.3	7.1±2.0
		Ambient	81.3±0.1	67.9±0.4	64.8±1.0	22.4±2.5	7.0±0.7
		Change	0.3	0.2	-0.1	-1.5	1.5
方差分析Analysis of variance
变异来源Source of variation
年际Year(Y)			**	**	*	**	*
材料Material(M)			0.100	0.088	**	**	*
CO₂浓度([CO₂])			0.393	0.430	0.318	0.535	0.711
Y×M			0.053	*	***	0.549	0.988
Y×[CO₂]			0.250	0.253	0.089	0.499	0.582
M×[CO₂]			0.392	0.460	*	0.164	0.063
Y×M×[CO₂]			0.340	0.324	0.533	0.705	0.894

稻米外观与加工品质对大气CO₂浓度升高的响应

Responses of Rice Appearance and Processing Quality to Elevated Atmospheric CO₂Concentration

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