Soil Quality Evaluation of Oasis Cotton Fields in Shaya County of Xinjiang

doi:10.11924/j.issn.1000-6850.casb2022-0301

Abstract

Abstract:

By evaluating the soil quality of cotton fields in Shaya County and exploring the relationship between soil salinization and soil quality, the study aims to promote sustainable production in cotton fields. We took the main cotton planting areas of 4 townships in Shaya County as the research objects, and measured six physical and chemical indexes, including soil organic matter, total nitrogen, available potassium, available phosphorus, total salt and bulk density. Then, we calculated the soil integrated fertility index (IFI) and used the M-SQR evaluation method to determine the soil quality rating of cotton fields. The results showed that the nutrient contents of cotton fields were moderate and the soil bulk density was relatively large in Shaya County; up to 30% of the sample sites had different degrees of soil salinization. The soil salinity was negatively correlated with most soil nutrient indicators. According to the scoring results, the soil integrated fertility index of cotton fields could be divided into five levels. Compared with the IFI rating, the number of samples above grade III decreased by 31.37% in the SQR rating, while the number of low-grade soil quality sampling points increased by 16. The soil quality of saline-alkali patch, sand patch and reed patch were grade Ⅴ in this research, and the soil quality of the central cotton area was better than that of the southern and northern cotton areas. In conclusion, the M-SQR evaluation model has certain reliability, and soil salinization could inhibit the accumulation of soil nutrients and is a limiting factor of soil quality. The evaluation results of each sampling point have regional differences in spatial distribution. This study could provide a good way for the improvement of soil salinization and serve the management of soil quality in cotton fields in the region.

Key words: cotton field, soil quality, physical and chemical indexes, principal component analysis, M-SQR

WU Chupeng, SHENG Jiandong, HU Yutong, CHENG Zhihui, YANG Pengfei. Soil Quality Evaluation of Oasis Cotton Fields in Shaya County of Xinjiang[J]. Chinese Agricultural Science Bulletin, 2023, 39(9): 71-78.

Figures/Tables 9

References 34

[1]	郑琦, 王海江, 吕新, 等. 新疆棉田土壤质量综合评价方法[J]. 应用生态学报, 2018, 29(4):1291-1301. doi: 10.13287/j.1001-9332.201804.029
[2]	曹志洪. 继承传统土壤学的成果,促进现代土壤学的发展——论“土壤质量演变规律与可持续利用”研究[J]. 中国基础科学, 2000,(10):13-18.
[3]	王天娇, 朱卫红, 吴婷婷. 延吉市农田土壤肥力综合评价[J]. 安徽农业科学, 2017, 45(26):116-118,125.
[4]	DITZLER C A, TUGEL A J. soil quality field tools: Experiences of USDA-NRCS soil quality institute[J]. Agronomy journal, 2002, 94(1):33-38.
[5]	MUELLER L, SCHINDLER U, SHEPHERD T G, et al. The muencheberg soil quality rating for assessing the quality of global farmland. In Novel measurement and assessment tools for monitoring and management of land and water resources in agricultural landscapes of central Asia[J]. Environmental science and engineering, 2013:235-248.
[6]	闫慧峰, 梁洪波, 许家来, 等. 山东烟叶生产典型样区土壤质量评价[J]. 中国土壤与肥料, 2015(6):41-47.
[7]	DORAN J W, PARKIN T B. Defining and assessing soil quality[J]. Soil science, 1994(35):1-21.
[8]	陈欢, 曹承富, 张存岭, 等. 基于主成分—聚类分析评价长期施肥对砂姜黑土肥力的影响[J]. 土壤学报, 2014, 51(3):609-617.
[9]	刘占锋, 傅伯杰, 刘国华, 等. 土壤质量与土壤质量指标及其评价[J]. 生态学报, 2006(3):901-913.
[10]	李桂林, 陈杰, 檀满枝, 等. 基于土地利用变化建立土壤质量评价最小数据集[J]. 土壤学报, 2008(1):16-25.
[11]	王雪梅, 杨美玲, 康璇. 基于GIS的库车县耕地土壤质量综合评价[J]. 中国农学通报, 2015, 31(29):123-128. doi: 10.11924/j.issn.1000-6850.casb15050132
[12]	茹思博, 杨乐, 钱文东, 等. 利用层次分析法和综合指数法评价新疆棉区土壤质量[J]. 河南农业科学, 2009(8):63-66. doi: 10.3969/j.issn.1004-3268.2009.08.017
[13]	姜艳, 刘东阳, 李健梅, 等. 玛河流域不同连作年限棉田土壤质量分析及综合评价[J]. 干旱地区农业研究, 2021, 39(4):186-193.
[14]	贡璐, 张海峰, 吕光辉, 等. 塔里木河上游典型绿洲不同连作年限棉田土壤质量评价[J]. 生态学报, 2011, 31(14):4136-4143.
[15]	张飞, 塔西甫拉提. 特依拜, 丁建丽, 等. 干旱区土壤盐渍化及其对生态环境的损害评估—以新疆沙雅县为例[J]. 自然灾害学报, 2009, 18(4):55-62.
[16]	新疆渭干河流域管理处. 渭干河流域水盐监测技术报告[R]. 2003:11-32.
[17]	穆耶赛尔·肉孜, 迪里木拉提·玉苏甫, 玉苏甫·买买提. 沙雅县植棉土壤表层养分空间分布特征分析[J]. 农学学报, 2018, 8(9):33-38. doi: 10.11923/j.issn.2095-4050.cjas17050036
[18]	中华人民共和国农业部. NY/T 1634—2008耕地地力调查与质量评价技术规程[S]. 北京: 中国标准出版社, 2008.
[19]	中华人民共和国国土资源部. DZ/T 0295—2016土地质量地球化学评价规范[S]. 北京: 中国标准出版社, 2016.
[20]	全国土壤普查办公室. 中国土壤普查技术[M]. 北京: 中国农业出版社, 1992:43-92.
[21]	王鹏. 基于土壤的宝天曼自然土地质量特征及评价[D]. 郑州: 河南大学, 2019:31-32.
[22]	张炎, 王讲利, 付明鑫, 等. 新疆棉田土壤养分评价指标的建立[C]// 中国科协2005年学术年会“新疆现代农业论坛论”文专集, 2005:46-49.
[23]	新疆维吾尔族自治区土壤调查办公室. 新疆土壤[M]. 北京: 科学出版社, 1996.
[24]	雷志栋, 扬诗秀, 许志荣, 等. 土壤特性空间变异性初步研究[J]. 水利学报, 1985(9):10-21
[25]	赵川, 和丽萍, 李贵祥, 等. 昆阳磷矿废弃地植被恢复对土壤质量的影响及评价[J]. 西部林业科学, 2018, 47(2):106-111.
[26]	陆琦, 马克明, 张洁瑜, 等. 三江平原退化湿地和农田土壤养分的比较研究[J]. 生态与农村环境学报, 2007,(2):23-28.
[27]	费裕翀, 黄樱, 刘丽, 等. 中亚热带紫色土丘陵区几种典型人工林土壤质量评价[J]. 东北林业大学学报, 2020, 48(9):80-87.
[28]	程艳丽, 邹德乙. 长期定位施肥残留养分对作物产量及土壤化学性质的影响[J]. 土壤通报, 2007(1):64-67.
[29]	黄翠华, 薛娴, 彭飞, 等. 不同矿化度地下水灌溉对民勤土壤环境的影响[J]. 中国沙漠, 2013, 33(2):590-596.
[30]	刘杏兰, 高宗, 刘存寿, 等. 有机—无机肥配施的增产效应及对土壤肥力影响的定位研究[J]. 土壤学报, 1996(2):138- 142,144-147.
[31]	柴仲平, 梁智, 王雪梅, 等. 连作对棉田土壤物理性质的影响[J]. 中国农学通报, 2008(8):192-195.
[32]	黄勇, 杨忠芳. 土壤质量评价国外研究进展[J]. 地质通报, 2009, 28(1):130-136.
[33]	马宁, 李强, 郭玉涛, 等. 神东矿区典型植被不同恢复年限对土壤质量的影响[J]. 中国水土保持, 2019(11):59-62,79.
[34]	LIU L M, ZHOU D, CHANG X, et al. A new grading system for evaluating China's cultivated land quality[J]. Land degradation & development, 2020, 31(12):1-20. doi: 10.1002/ldr.v31.1 URL

项目	测定方法	方法依据
全氮	半微量开氏法	NY/T 1634—2008^[18]
速效钾	乙酸铵溶液浸提-火焰光度法
速效磷	碳酸氢钠浸提法
容重	环刀法
全盐量	重量法

项目	测定方法	方法依据
全氮	半微量开氏法	NY/T 1634—2008^[18]
速效钾	乙酸铵溶液浸提-火焰光度法
速效磷	碳酸氢钠浸提法
容重	环刀法
全盐量	重量法

界限值	有机质/(g/kg)	全氮/(g/kg)	速效磷/(mg/kg)	速效钾/(mg/kg)	容重/(g/cm³)
x₁	8	0.5	5	85	1.25
x₂	25	2	30	220	1.45

界限值	有机质/(g/kg)	全氮/(g/kg)	速效磷/(mg/kg)	速效钾/(mg/kg)	容重/(g/cm³)
x₁	8	0.5	5	85	1.25
x₂	25	2	30	220	1.45

指标	极距	极小值	极大值	平均值	标准差	偏度系数	峰度系数	变异系数/%
有机质/(g/kg)	14.72	15.20	29.91	22.55	3.56	-0.00	-0.62	15.80
全氮/(g/kg)	2.02	0.64	2.66	1.47	0.48	0.35	-0.76	32.71
速效磷/(mg/kg)	28.63	5.39	34.02	17.26	7.31	0.41	-0.85	42.35
速效钾/(mg/kg)	295.38	34.31	329.70	136.17	54.38	0.91	1.86	39.93
容重/(g/cm³)	0.66	1.03	1.69	1.50	0.11	-1.16	3.18	7.58
全盐/(g/kg)	16.18	0.15	16.33	4.77	4.53	1.02	-0.38	94.93