Difference of Nitrogen Uptake and Use Efficiency in Conventional Indica Rice Cultivars with Different Nitrogen Use Efficiency for Grain Output

[Objective] The study aimed to confirm difference of nitrogen uptake and used efficiency with different nitrogen use efficiency for grain output (NUEg) types of indica rice.[Method] 88 and 122 conventional indica rice cultivars were solution-cultured in 2001 and 2002, respectively. Dry matter weight (including root system, culm and sheath, leaves, panicle), nitrogen content of different organs, yield and its components were measured. The tested rice cultivars were classified into 6 types (i.e. A, B, C, D, E and F, A was the lowest, and F was the highest) based on their NUEg level by the MinSSw method.[Result](1)Difference of NUEg of the cultivars used in this study were very large; (2) No significant difference of N content at heading stage was observed among different NUEg types of indica rice. In the cultivars with higher NUEg, however, N content in leaf, stem-sheath and entire rice plant were lower at mature stage. (3)Cultivars with higher NUEg were characterized with lower N uptake before heading and at mature stage; (4) Cultivars with higher NUEg were characterized with higher N use efficiency in biomass production and harvest index. [Conclusion] The cultivars with higher NUEg showed lower N uptake and N content, while nitrogen use efficiency was higher.

Agricultural Policy, Climate Factors and Grain Output: Evidence From Household Survey Data in Rural China

This paper estimates a stochastic frontier function using a panel data set that includes 4 961 farmer households for the period of 2005-2009 to decompose the growth of grain production and the total factor productivity （TFP） growth at the farmer level. The empirical results show that the major contributor to the grain output growth for farmers is input growth and that its average contribution accounts for 60.92% of farmer’s grain production growth in the period of 2006-2009, whereas the average contributions sourced from TFP growth and residuals are only 17.30 and 21.78%, respectively. The growth of intermediate inputs is a top contributor with an average contribution of 44.46%, followed by the planted area （18.16%）, investment in fixed assets （1.05%）, and labor input （-2.75%）, indicating that the contribution from the farmer’s input growth is mainly due to the growth of intermediate inputs and that the decline in labor inputs has become an obstacle for farmers in seeking grain output growth. Among the elements consisting of TFP growth, the contribution of technical progress is the largest （32.04%）, followed by grain subsidies （8.55%）, the average monthly temperature （4.26%）, the average monthly precipitation （-0.88%）, the adjusted scale effect （-5.66%）, and growth in technical efficiency （-21.01%）. In general, the contribution of climate factors and agricultural policy factor are positive and significant.

Weight Determining of Factors Influencing Grain Output Based on Entropy Weight Method

This article selects 8 main factors(the number of rural employees,total power of agricultural machinery,effective irrigation area of crops,growing area of grain crops,fertilizer consumption,electricity consumption in rural areas,area affected and area covered) as the factors influencing grain output,and offers the method of determining weight of factors influencing grain output using entropy weight method.According to the relevant data in the period 1985-2005,we analyze the weight of factors influencing grain output in China by example.The results show that the electricity consumption in rural areas has the greatest impact on grain output,followed by total power of agricultural machinery,fertilizer consumption and area covered.To increase grain output,we must enhance the degree of mechanization,free people from the former process of direct cultivation,strengthen water conservancy construction,and do a good job in disaster prevention and mitigation.

An explanation of labor migration and grain output growth:Findings of a case study in eastern Tibetan Plateau

Although there has been rapid rural-urban migration in rural China since the 1980s, the total grain production of China saw a continuous increase. As of today, the relationship between labor migration and grain output growth remains partial and contradictory. The main aim of this empirical study is to examine some specific measures adopted by peasants to deal with labor shortage and maintain grain output growth. Using tracking survey, participatory rural appraisal methods, and land plot investigation, we investigate 274 households and 1405 arable land plots in four villages in two stages in Jinchuan county, southwestern China. The results show that continuous emigration of labor from the four villages caused the abandon- ment of a small amount of land, decreased labor intensity, and reduced multiple cropping index, shifting from ＂corn-wheat＂ multiple cropping pattern to the ＂corn＂ cropping pattern, which means labor shortage in some households. At the same time, owing to surplus labor in the villages, the peasants utilize a series of means to offset the negative impacts of labor migration on grain output, such as cropland transfer, labor exchange in the busy seasons, and the substitution of capital and technology for labor. The econometric analysis also shows that labor migration boosts grain production. This study provides a reasonable explanation of grain output growth under rural-urban migration.

Input-Occupancy-Output Technique and Its Applications in China' s Grain Output Prediction and Township and Village Enterprises Study

Under the support of National Natural Science Foundation of China including international cooperative research project, key project and other project, professor Chen Xikang from Academy of Mathematics and Systems Science under the Chinese Academy of Sciences, together with his colleagues, put forward in-put-occupancy-output technique and then used it in national grain output prediction approach. The main achievements are as follows:

Policy Suggestions for the Slowdown in Per Capital Output of Grain Growth in China

China is a large agricultural and the most populous country, so it is a crucial importance for the food security. The basic situation of food in our country is self-sufficiency, a certain amount of imports and reserves. The output of grain in our country has increased annually, however, as a result of policy adjustments and other factors like environmental pollution, together with a large population base and the trend of excessively popu- lous growth, the growth of grain output is relatively slow, which will be harmful for our grain security as well as the healthy development of the na- tional economy. In this case, several solutions could be tried, such as improving the level of science and technology, adjusting industrial policies and controlling environmental pollution. Besides, we ought to strongly advocate thrifty behavior to increase income and reduce expenditure.

秦汉的粮食产量与农户生计

秦汉时期粮食的常见高产可达到每市亩产粟247公斤,秦和西汉的平均亩产范围,折合今制也在每市亩产粟74公斤至123公斤之间。正是基于这种较高水平的粮食生产能力,西汉人口才能从初期的约2000万增长到末年的约6000万。只是这一时期粮食产量的不稳定与不均衡性相当突出。这背后有着独特的历史原因,即此时的粮食产量严重依赖于土地质量和气候条件。粮食产量的不稳定和不均衡导致了小农经济的脆弱性。受限于技术,秦汉小农因抵御灾害的能力弱而容易破产,庄园经济则因其对灾害形成了“社会性对冲”,故能接替小农经济,成为中古时期的重要经济形态。

基于超效率Output-DEA模型的主产区粮食生产能力评价

应用超效率Output-DEA模型,对我国2008年13个粮食主产省区的粮食生产能力进行了研究。结果表明,主产区处于技术有效的省份仅有4个,其超效率值存在较大差距。多数省区技术无效率是规模效率低造成的。如果能够提高无效率省区的技术效率,发挥有效率省份的生产潜力,对提升全国的粮食生产能力将产生十分明显的效果。各无效率省区还存在投入的冗余,减少这些投入冗余对于降低粮食生产成本具有重要作用。我国政府应该把提高粮食生产效率作为粮食政策的首要目标,促进粮食生产区域的合理布局,优化粮食生产支持政策。

The changing regional distribution of grain production in China in the 21st century

This paper examines the changing regional distribution of grain production in China. Based on the analysis of data from county statistics for the period 2000-2003, major differences in the main grain-output regions in China can be observed. The main grain-producing areas have shifted from the south to the north of China. New grain production regions have been also added to westem China since the late 1990s. The per capita grain consumption in one third of China＇s main grain-producing counties has fallen below 400 kg; most of these areas are located in southern China. In the new millennium, Northeast China, the central-south North China, and the add and semi-arid regions of Northwest China produced three quarters of the surplus grains. Most of these areas are located in regions susceptible to environmental change. The amount of grain production in these regions shows high fluctuations. It is argued here that fi.trther studies of recent environmental changes as well as a risk assessment of China＇s food security in main grain-output regions are needed.

FORECAST OF CHINA'S GRAINPRODUCTION DEVELOPMENT AND ITSSELF-SUPPORT RATE ANALYSIS

This far stern difficulhes and challenges fatal by the dev ofadn P in etna. to the bac national snon of China and the of and min the world market, China must meet the and Inainly by her own production. Using the input output and system edence metal, this makesa foast abbot China’s glain output, grain and allsupport rate in the year 2030.

China’s grain production: status and prospects

In this paper, we first look back at China’s grain production since reform and opening up and review the main factors of grain production at different stages. Secondly we find that the improvement of the per unit yield has become a major factor in the increase of grain production, and that corn has become a major grain production support variety; compared with the other varieties, paddy rice is most vulnerable in production; grain production has increasingly become dependant on scientific and technological progress and the role of infrastructure. Thirdly, the transformation of low-yielding fields in the future, the development of reserve land resources and acceleration of scientific and technological progress – these factors together promote China's great potential for grain production; but through adjusting variety structure to promote grain production is nearly impossible. Finally, the main constraints of China’s future grain production are as follows: reduction of arable land and water shortages is becoming increasingly constrained; agricultural comparative advantage is low; opportunity cost is high and accelerating at the same time; and the uncertainties of (1) whether the agricultural inputs by government at all levels of can significantly increase the intensity; (2) whether support of the reform of grain production and systems can achieve breakthrough; and (3) whether the risk of the development of grain production can be effectively prevented. On this basis, we draw the relevant conclusions and policy recommendations.

中国自然灾害与粮食产量脱钩关系研究

自然灾害对中国粮食产量仍然有较大影响。本文测算1980—2020年全国自然灾害和粮食产量的脱钩情况,为进一步考察粮食产量韧性的影响因素,构建基于稻谷、小麦和玉米产量的驱动因素模型,利用2010—2020年各地区空间面板数据,选取空间杜宾模型进行计量分析。结果表明,近40年来中国自然灾害与粮食产量的脱钩状态呈现出波动式上升趋势,说明改革开放以来,中国粮食防灾减灾能力建设成效显著;粮食产量与受灾面积、抗灾能力存在空间依赖关系;各地区抗灾能力存在较大差异,粮食主产区应该加强农业防灾减灾能力专项建设,以巩固粮食安全根基。

湖北省粮食产量影响因素分析─基于主成分回归

由于湖北省粮食播种面积、高标准农田数量、耕地有效灌溉面积、农业生产机械化率数据之间存在多重共线性,分析其对湖北省粮食产量影响时,运用最小二乘法估计参数容易失真而缺乏解释性。因此,利用能够解决多重共线性问题的主成分回归来分析粮食播种面积、高标准农田数量、耕地有效灌溉面积、农业生产机械化率对湖北省粮食产量影响。回归的参数客观可靠,真实有效,通过对解释变量的释读,结果发现与湖北省粮食生产的实现情况基本吻合。

基于Output-DEA模型的粮食生产效率分析——以安徽省三大粮食生产功能区为例

文章是基于粮食主产省安徽省2017年的16个地级市面板数据,采用Output-DEA模型对安徽省的水稻、小麦、玉米三大粮食生产功能区的综合效率、纯技术效率、规模效率与规模报酬以及冗余状况进行归类分析。研究发现,横向比较综合效率小麦生产区>水稻生产区>玉米生产区,纵向比较纯技术效率更接近DEA有效,而劳动力冗余问题突出,化肥施用存在过量。据此,提出加速城镇产业化进程、提升农业从业人员科技素养、科学布局粮食生产功能区等对策。

湖北省县域粮劳变化耦合模式与乡村发展类型

利用湖北省2003—2017年81个县域的粮食产量和农业劳动力数据,运用粮劳弹性系数模型方法,分析了湖北省粮劳时空变化特征及对应耦合模式。结果表明,2003—2017年湖北省粮食生产整体呈现稳中有增态势,呈“中高周低”“中增周减”空间特征,高产区集中在鄂西北中部与江汉平原南部;农业劳动力总量持续减少,呈“东多西少”“东增西减”空间特征,密集区集中在江汉平原东部和鄂东北丘陵西部。2003—2017年湖北省最典型的粮劳耦合变化模式为粮增劳减型(60.49%),其次为粮劳同减型(23.46%)和粮劳同增型(11.11%),粮减劳增型占比最低(4.94%)。受地理条件和农业政策的影响,湖北省乡村发展类型呈现多样化并存的格局:中部多分布外延扩张型和农业现代化型县域,东部和西部多分布产业转移型和种养一体化型县域;2010年前后两时段县域乡村发展类型转换较为复杂,维持不变相对较少。

省际粮食贸易隐含污染与环境比较优势研究

为协调粮食生产、贸易与面源污染的矛盾,实现绿色农业发展、区域间利益共赢,在测算省际粮食贸易量的基础上,运用灰水足迹方法计算各省隐含氮污染和污染强度,构建了粮食贸易隐含氮污染网络,解析了省际粮食生产隐含氮污染的环境比较优势。结果表明:中国省际粮食贸易网络格局由“条块式”转向“团块式”,贸易集中化趋势明显;省际粮食贸易隐含污染和污染强度呈下降趋势,但地区差异明显加剧了环境不公平;环境比较优势网络表现出“两头小,中间大”的橄榄形分布,环境比较优势最小的地区集中在华北地区,最大为黑龙江。

基于IGOWLA算子与Theil不等系数的安徽省粮食产量组合预测研究

粮食产量的精准预测对于保障国家粮食安全、优化农业资源配置、指导农业生产和制定政策等方面具有重要意义.基于差分自回归移动平均(ARIMA)、长短期网络(LSTM)以及灰色GM(1,1)三种单项预测模型建立组合预测模型,利用1949—2023年安徽省粮食产量数据对2014—2023年安徽省粮食产量数据进行重新预测,并通过诱导广义有序加权对数平均算子(IGOWLA)将组合预测与三种单项预测结果作对比,以实现泰尔(Theil)不等系数最小化求解变权系数.预测结果表明,组合预测模型在准确性和稳定性方面,相较单预测模型表现得更为出色.最后,利用组合预测模型对安徽省2024—2026年粮食产量进行预测,以期为地方政府和农业部门的粮食生产决策提供科学依据.

基于灰色变权组合模型的河南粮食产量预测分析

科学合理地考虑各生产资源要素在农业中的运用,促进粮食产量的稳定增长,是保障粮食安全的关键。选取河南省2005~2021年粮食产量及相关因素数据,利用灰色关联模型提取影响粮食产量的主要影响因素,基于方差倒数加权法构建由GM(1, N)、Lasso回归、BP神经网络组成的多变量变权重组合预测模型,对河南粮食产量的变化趋势进行拟合与预测。结果表明,变权重组合预测模型的预测误差为0.589%,预测精度高且性能稳定;预测河南粮食产量在2022~2025年将会保持稳定增长,并在2025年达到73 282.65 kt。

钱越多越好吗?农村信贷与农村产业升级的时空关系——基于SAR模型与SEM模型的实证分析

农村信贷为农村经济发展提供资金支撑,是农村产业升级的重要保障。本文利用1978—2019年30省份面板数据,在构建农村信贷对农村产业升级影响的理论框架基础上,建立空间自回归模型(SAR)和空间误差模型(SEM),实证分析农村信贷与农村产业升级的时空关系。研究结果表明:农村产业升级在地理位置上呈现空间集聚性;农村信贷规模扩大到一定程度会对农村产业升级产生抑制作用,呈“倒U型”非线性关系;其中,受农业资源差异影响,整体上东部区和中部区存在“倒U型”关系,西部区并不存在“倒U型”关系;进一步分析发现,粮食主产区“倒U型”关系最显著,三大粮食产区中黄淮海地区和长江流域地区呈明显“倒U型”关系,东北地区则不存在“倒U型”关系。最后,本文提出发挥农村产业升级空间集聚作用、农村信贷坚持因地制宜原则等政策建议。

最低收购价政策可以提高农民种粮积极性吗?——基于双重差分模型的实证检验

基于2000—2020年省级面板数据,利用双重差分法分别考察最低收购价政策对小麦和稻谷的播种面积、产量与价格波动的影响。结果表明:最低收购价政策的实施有助于提升农民种粮的积极性,从而增大粮食播种面积,增加粮食产量;而最低收购政策对粮食价格波动的影响很小,且回归系数不显著,这可能与政策实施力度、粮食的品种特性等因素有关。此外,在经过随机性检验、平行趋势检验以及安慰剂检验后,这一结论仍然成立,确保了估计结果的可信性和稳定性。