稻米：一百年,一千年,一万年

大致说来,一万年前是中国稻作的起源时期,一千年前则是中国稻作传统的形成时期,而最近一百年则是中国稻作发展最快的时期。用一百年、一千年、一万年这三个大致的时间节点,全景展示中国稻米的历史、稻米对于国计民生的重要性、千百年来中国人民为解决吃饭问题所做的努力、近百年来中国稻作科技的发展与进步,展望未来稻米所可能遇到的挑战和前景。     

Impact of climate change on maize yield in China from 1979 to 2016

Climate change severely impacts agricultural production, which jeopardizes food security. China is the second largest maize producer in the world and also the largest consumer of maize. Analyzing the impact of climate change on maize yields can provide effective guidance to national and international economics and politics. Panel models are unable to determine the group-wise heteroscedasticity, cross-sectional correlation and autocorrelation of datasets, therefore we adopted the feasible generalized least square(FGLS) model to evaluate the impact of climate change on maize yields in China from 1979–2016 and got the following results:(1) During the 1979–2016 period, increases in temperature negatively impacted the maize yield of China. For every 1°C increase in temperature, the maize yield was reduced by 5.19 kg 667 m–2(1.7%). Precipitation increased only marginally during this time, and therefore its impact on the maize yield was negligible. For every 1 mm increase in precipitation, the maize yield increased by an insignificant amount of 0.043 kg 667 m–2(0.014%).(2) The impacts of climate change on maize yield differ spatially, with more significant impacts experienced in southern China. In this region, a 1°C increase in temperature resulted in a 7.49 kg 667 m–2 decrease in the maize yield, while the impact of temperature on the maize yield in northern China was insignificant. For every 1 mm increase in precipitation, the maize yield increased by 0.013 kg 667 m–2 in southern China and 0.066 kg 667 m–2 in northern China.(3) The resilience of the maize crop to climate change is strong. The marginal effect of temperature in both southern and northern China during the 1990–2016 period was smaller than that for the 1979–2016 period.     

青藏高原地区积雪变化及特征分析

利用我国高原地区1963-2002年的逐月积雪日数资料,以及1972-2011年的格点积雪月频率资料,分析、对比了两种资料在该地区的时空演变特征。结果表明：同时段的(1972-2002)站点资料与格点资料相比,空间分布其高值区与积雪日数增值区均偏西北,偏北程度大致为3~4°,偏西程度大致为2~3°,且中心更为明显。在青藏高原西侧(85°E以西),积雪日数呈整体下降趋势。两种资料的积雪日数EOF分析存在一定的偏差,这与其对应的空间分布差异及气候趋势空间分布存在的偏差相吻合。     

农村互联网发展对中国玉米全要素生产率的影响

采用DEA-mamlquist指数测算2004—2019年中国17个玉米主产省(区)的全要素生产率,运用联立方程组模型实证检验农村互联网发展对玉米全要素生产率的影响及其作用机理,并分区域探讨其差异性。结果显示:2004—2019年中国玉米全要素生产率年均增长0.2%,主要依靠技术进步的单轨模式驱动。农村互联网的发展显著(P<0.01)提升玉米全要素生产率,主要依靠技术进步和技术效率的协同作用驱动。分区域来看,农村互联网发展对玉米全要素生产率均具有显著(P<0.01)的促进作用,其影响程度由高到低依次为北方春播玉米区>黄淮海平原夏播玉米区>西北灌溉玉米区>西南山地玉米区。建议进一步提高农村互联网的配套设施建设,发挥互联网“连接经济”的优势,应用多元化互联网技术,促进不同生态类型区玉米生产效率的提升。     

何刚德《抚郡农产考略》农业经济思想初探

《抚郡农产考略》是清末江西有代表性的农学著作,不仅保存有抚州地区大量农产种类、栽培与加工技术等资料,还包含了大量的商品经济信息。作者何刚德已经认识到自给自足的自然经济会对生产有束缚作用,他在记载各类农产品时,提出“价值”的概念且用货币价格对其衡量,并深入揭示了农产品上市时间、供求、地理、交通条件等因素对价格的影响,进而寻求增值之道。何氏提倡多种经营,大力种植棉花、烟叶等经济作物,发挥柑橘、甘蔗等名优特产优势,促进农业的商品化生产。他还建议通过深加工的方式获取更高利润,并对未能引进西方的先进加工技术而感到惋惜。《抚郡农产考略》体现了中国近代官僚知识分子对农业经济转型的探索,具有重要的历史价值与现实意义。     

“一带一路”背景下陕西茶叶跨境电商发展路径研究

陕西作为丝绸之路的发源地，以其有利的自然生态条件和区域产业结构，形成了以茶叶为主导的产业发展格局。目前，陕西省茶叶出口规模不大，市场占有率较低。在“一带一路”倡议的推动下，陕西省茶叶出口至沿线国家的潜力较大，未来将逐步呈上升态势。研究了“一带一路”背景下陕西茶叶跨境电商市场发展现状和存在的问题，提出陕西茶叶跨境电商发展路径，通过借力跨境电商平台、开拓国际市场、稳固绿茶品牌、布局海外仓解决出口难的问题，以及完善跨境电商法律秩序，拓展陕西茶叶跨境电商发展路径。      

基于土地利用变化的河北省坝上地区景观生态风险评价

[目的]对河北省坝上地区近40 a来的土地利用动态变化和生态风险进行分析评价并对未来趋势作出预测,为该地区生态建设和治理、可持续发展提供科学依据。[方法]基于坝上地区1980—2018年5期土地利用数据以及通过土地转移矩阵、空间相关性分析等方法揭示和预测该区1980—2026年的土地利用变化特征并评估该区生态风险水平。[结果](1)整个研究期间,坝上地区土地利用类型以耕地为主,所占比例近50%,其中,1980—2018年,耕地、林地扩张面积均超过300 km~2,草地减少近616.60 km~2,水域面积缩减36.04%,其中耕地、林地、草地之间的互相流转程度较为剧烈,空间变化上表现为各地类的重心在2000—2010年明显迁移。(2)1980—2026年,坝上地区6个时期内生态风险值全局空间自相关Moran’s I指数均在0.500左右,其空间分布表现出较高的趋同集聚性。(3)近40 a来,坝上生态风险水平升至为高风险级,其区域增加了123.22 km~2,较高风险区域分布在城镇地区,据CA-Markov模型预测,未来坝上地区中等及中等以上风险区域持续扩张,丰宁县和围场县将分别出现小规模高风险区和较高风险区。[结论](1)近40 a来坝上地区草地退化严重,水域面积显著减少,原因系安固里淖干涸所致。(2)该区生态风险水平与土地格局分布具有较强相关性,且在未来会继续升高。     

都市餐饮企业的净菜需求影响因素分析——以北京市为例

净菜的广泛使用能提高餐饮企业的出餐率,减少其后厨面积、劳动用工和厨余垃圾。基于北京地区708份餐饮企业净菜需求的问卷调查样本,运用垄断竞争市场理论和二元选择模型分析了影响餐饮企业净菜使用行为的具体因素。研究发现,对净菜了解程度不够和净菜价格偏高是制约餐饮企业使用净菜的主要因素,具有不同个体特征和环境特征的餐饮企业选择净菜的倾向性不同。建议在餐饮业大力开展净菜宣传科普工作;大力扶持净菜加工企业和发展相关技术支撑体系以降低净菜价格。     

气候变化情景下流苏香竹潜在分布区预测

流苏香竹（Chimonocalamus fimbriatus）是云南特有珍稀竹种，主要分布于云南西南部。文章以野外调查获取的流苏香竹分布信息为主，运用最大熵模型（MaxEnt）同时结合地理信息系统（ArcGIS），基于19个气候因子，预测其在当前及未来气候变化情景下的潜在分布区。结果表明：当前流苏香竹的高适生区和中适生区主要分布于德宏州、保山市和临沧市等地，除迪庆州、丽江市和昭通市外，云南其他区域均有低适生区零星分布。在未来2050s和2070s的2个时间段，基于2种不同共享社会经济路径（SSP1-2.6和SSP5-8.5），流苏香竹的高适生区面积呈减少的趋势，尤其是SSP5-8.5路径下，高适生区面积仅为当前的12.51%（2050s）和18.63%（2070s）；中、低适生区在SSP1-2.6路径下，显著扩张（2050s）或略微扩张（2070s），在SSP5-8.5路径下，则大幅收缩。流苏香竹野外实际分布区及其潜在分布区均以斑块状为主，可能与云南特殊的地形、地貌有关。影响流苏香竹分布的主导气候因子为最湿月份降水量、最暖月份最高温度、最干季度降水量和平均气温日较差。流苏香竹对气候变化比较敏感，根据其野外分布状况，建议以就地保护为主、迁地保护为辅，在其潜在适生区内适当引种栽培。     

Determination of critical nitrogen dilution curve based on leaf area index for winter wheat in the Guanzhong Plain,Northwest China

Excessive use of nitrogen(N) fertilizers in agricultural systems increases the cost of production and risk of environmental pollution. Therefore, determination of optimum N requirements for plant growth is necessary. Previous studies mostly established critical N dilution curves based on aboveground dry matter(DM) or leaf dry matter(LDM) and stem dry matter(SDM), to diagnose the N nutrition status of the whole plant. As these methods are time consuming, we investigated the more rapidly determined leaf area index(LAI) method to establish the critical nitrogen(N_c) dilution curve, and the curve was used to diagnose plant N status for winter wheat in Guanzhong Plain in Northwest China. Field experiments were conducted using four N fertilization levels(0, 105, 210 and 315 kg ha-1) applied to six wheat cultivars in the 2013–2014 and 2014–2015 growing seasons. LAI, DM, plant N concentration(PNC) and grain yield were determined. Data points from four cultivars were used for establishing the N_c curve and data points from the remaining two cultivars were used for validating the curve. The N_c dilution curve was validated for N-limiting and non-N-limiting growth conditions and there was good agreement between estimated and observed values. The N nutrition index(NNI) ranged from 0.41 to 1.25 and the accumulated plant N deficit(N_(and)) ranged from 60.38 to –17.92 kg ha~(-1) during the growing season. The relative grain yield was significantly affected by NNI and was adequately described with a parabolic function. The N_c curve based on LAI can be adopted as an alternative and more rapid approach to diagnose plant N status to support N fertilization decisions during the vegetative growth of winter wheat in Guanzhong Plain in Northwest China.