Evolution of varieties and development of production technology in Egypt wheat: A review

Wheat was the first crop grown in Egypt, and it remains highly important. Egypt is the largest wheat importer in the world and consumes an extensive amount of bread. It is imperative for wheat scientists to decrease the large gap between production and consumption. Wheat yields in Egypt increased 5.8-fold(6.7 billion kg) between 1961 and 2017 due to variety improvement and the use of better planting methods such as the raised bed method, ideal sowing date, surge flow irrigation and farm irrigation systems, laser levelling, fertilizers, and intercropping with raised beds. In this paper, the development of wheat production techniques and variety evolution over more than five decades in Egypt have been analyzed. In particular, we have focused on the technologies, cultural practices and causes for per unit area yield increase. The main purpose was to study the issues that have arisen during wheat production and to make recommendations for smart agricultural practices. In 1981, the yield was 3 300 kg ha–1 and through the improvement of varieties, expansion of agricultural land and the adoption of modern agricultural techniques yield reached 6 500 kg ha–1 by 2017. The production growth rate was 4.1% annually, and the total grain yield increased 4.3-fold, from 1.9 billion kg in 1981 to about 8.1 billion kg in 2017. The use of new improved varieties, new cultivation techniques, and modern irrigation techniques contributed to 97.0% of the increase in yield per unit area and 1.5% of the increase in yield was due to planting area expansion. Therefore, the increase in total yield mainly depended on the increase in yield per unit area. Wheat production in Egypt has been improved through the development of breeding and cultivation techniques. The use of these new techniques, the popularization of new high-quality seed varieties, and the use of the raised bed method instead of the old method of planting in basins have made the largest contributions to increased yield. In the future, wheat yield could be further increased by using the tridimensional uniform sowing mode and the development of wheat varieties that are resistant to rusts, deficit irrigation, and abiotic stress, that are highly adaptable to mechanized operation and have high yields. Based on our analysis, we propose the main technical requirements and measures to increase wheat yield in Egypt in the near future.     

Determination of soybean yield gap and potential production in Iran using modeling approach and GIS

Increasing crop production is necessary to maintain food security for the growing global population.Reducing the gap between actual and potential yield is one of the important ways to increase yield per unit area.Potential yield and the yield gap of soybean were determined for Golestan Province,Iran,using Soybean Simulation Model (SSM-i Crop2) and Geographical Information System (GIS).Information from 24 weather stations and soil data of the region were used.Yield gap and production gap were calculated at county and province levels.The average actual yield of soybean in this province was2.28 t ha~(–1) while the province’s potential yield was 4.73 t ha~(–1),so the yield gap was estimated 2.44 t ha~(–1).Thus,there is a great potential for increasing soybean yield in Golestan,which is possible through improving crop management of soybean in farmers’fields.The average water productivity of soybean was estimated to be 0.81 kg m~(–3).Spatial distribution of water productivity in soybean farms showed that the highest and the lowest water productivities (0.99 and 0.44 kg m~(–3)) were in western and eastern regions of the province,respectively,in accordance to vapour pressure deficit.It was concluded that soybean production in the province could increase by 66%(from 109 970 to 182 170 tons) if 80% of the current yield gap could be removed.     

How Could Agricultural Land Systems Contribute to Raise Food Production Under Global Change？

To feed the increasing world population, more food needs to be produced from agricultural land systems. Solutions to produce more food with fewer resources while minimizing adverse environmental and ecological consequences require sustainable agricultural land use practices as supplementary to advanced biotechnology and agronomy. This review paper, from a land system perspective, systematically proposed and analyzed three interactive strategies that could possibly raise future food production under global change. By reviewing the current literatures, we suggest that cropland expansion is less possible amid iferce land competition, and it is likely to do less in increasing food production. Moreover, properly allocating crops in space and time is a practical way to ensure food production. Climate change, dietary shifts, and other socio-economic drivers, which would shape the demand and supply side of food systems, should be taken into consideration during the decision-making on rational land management in respect of sustainable crop choice and allocation. And ifnally, crop-speciifc agricultural intensiifcation would play a bigger role in raising future food production either by increasing the yield per unit area of individual crops or by increasing the number of crops sown on a particular area of land. Yet, only when it is done sustainably is this a much more effective strategy to maximize food production by closing yield and harvest gaps.     

Recognizing production options for pearl millet in Pakistan under changing climate scenarios

Climate change is making the lands a harsher environment all over the world including Pakistan. It is expected to oppose us with three main challenges:increase in temperature up to 2–5°C(heat stress),increasing water stress and severe malnourishment due to climate change. It has been foreseen that there will be a 10% increase of dryland areas with climate change in the world,with more variability and incidences of short periods of extreme events(drought and heat stress). Pearl millet is a hardy,climate smart grain crop,idyllic for environments prone to drought and heat stresses. The crop continues to produce highly nutritious grain sustainably,thereby encouraging the fight against poverty and food insecurity due to its resilience. The crop is more responsive to good production options(planting time,planting density,inter/intra row spacing,nitrogen application and irrigation). It has high crop growth rate,large leaf area index and high radiation use efficiency that confers its high potential yield. In most of the cases,pearl millet is remained our agricultural answer to the climate calamity that we are facing,because it is selected as water saving,drought tolerant and climate change complaint crop. In view of circumstances,pearl millet cultivation must be retrieved by recognizing production options in context to changing climate scenarios of Pakistan using crop modeling techniques.     

Light interception and radiation use efficiency response to tridimensional uniform sowing in winter wheat

Improving radiation use efficiency(RUE) of the canopy is necessary to increase wheat(Triticum aestivum) production. Tridimensional uniform sowing(U) technology has previously been used to construct a uniformly distributed population structure that increases RUE. In this study, we used tridimensional uniform sowing to create a wheat canopy within which light was spread evenly to increase RUE. This study was done during 2014–2016 in the Shunyi District, Beijing, China. The soil type was sandy loam. Wheat was grown in two sowing patterns:(1) tridimensional uniform sowing(U);(2) conventional drilling(D). Four planting densities were used: 1.8, 2.7, 3.6, and 4.5 million plants ha–1. Several indices were measured to compare the wheat canopies: photosynthetic active radiation intercepted by the canopy(IPAR), leaf area index(LAI), leaf mass per unit area(LMA), canopy extinction coefficient(K), and RUE. In two sowing patterns, the K values decreased with increasing planting density, but the K values of U were lower than that of D. LMA and IPAR were higher for U than for D, whereas LAI was nearly the same for both sowing patterns. IPAR and LAI increased with increasing density under the same sowing pattern. However, the difference in IPAR and LAI between the 3.6 and 4.5 million plants ha–1 treatments was not significant for both sowing patterns. Therefore, LAI within the same planting density was not affected by sowing pattern. RUE was the largest for the U mode with a planting density of 3.6 million plants ha–1 treatment. For the D sowing pattern, the lowest planting density(1.8 million plants ha–1) resulted in the highest yield. Light radiation interception was minimal for the D mode with a planting density of 1.8 million plants ha–1 treatment, but the highest RUE and highest yield were observed under this condition. For the U sowing pattern, IPAR increased with increasing planting density, but yield and RUE were the highest with a planting density of 3.6 million plants ha–1. These results indicated that the optimal planting density for improving the canopy light environment differed between the sowing patterns. The effect of sowing pattern×planting density interaction on grain yield, yield components, RUE, IPAR, and LMA was significant(P0.05). Correlation analysis indicated that there is a positive significant correlation between grain yield and RUE(r=0.880, P0.01), LMA(r=0.613, P0.05), and spike number(r=0.624, P0.05). These results demonstrated that the tridimensional uniform sowing technique, particularly at a planting density of 3.6 million plants ha–1, can effectively increase light interception and utilization and unit leaf area. This leads to the production of more photosynthetic products that in turn lead to significantly increased spike number(P0.05), kernel number, grain weight, and an overall increase in yield.     

Studies on the Relationship Between Grain-yield and Climatic Ecological Factors in Summer Corn Under Super-high-yielding Cultivation Conditions

Cultivation experiments on super-high-yield (≥12000kg/ha) of summer corn (Zea mays L. )were conducted in Laizhou, Shangdong Province, from 1986 to 1997, and in Wenxian, Henan Province, from 1996 to 1997. The results showed that requirements of accumulated temperature and hours of sunshine for super-high-yield of summer corn could be met in normal years in the areas of the Huanghuaihai Plain. Amount of precipitation influenced the yield most strongly in indirect way among all the meteorological factors, and the relationship between them displayed significant negative correlation (r = -0. 5418). The regression equation between yield and amount of precipitation at seedling stage and grain filling stage both reached significant level, and the partial regression coefficients were - 4. 8735 and - 13. 7415, respectively. Further research revealed that the key climatic-ecological factors influencing yield were as fellows: the average temperature in the third and the ninth Xun (note: a Xun indicates ten days and the accounting of Xun was from the corresponding sowing date), the hours of sunshine in the sixth and the eighth Xun, the amount of precipitation in the sixth, the seventh and the second Xun. Results obtained by analyzing yield components of summer corn showed that grain numbers per ear (GN/E) made greater contribution to super-high-yield than kernel weight (KW) and the numbers of ears did. The key factors influencing GN/E were the amount of precipitation in the sixth and the eighth Xun and the hours of sunshine in the sixth Xun, with the correlation coefficients of - 0.6074, 0.5793 and 0.5854, respectively.     

Performance in Grain Yield and Physiological Traits of Rice in the Yangtze River Basin of China During the Last 60 yr

Knowledge on the performance in grain yield and physiological traits is essential to understand the main yield-limiting factor and make strategies for breeding and crop management in rice (Oryza sativa L.). This study investigated the changes in grain yield and associated physiological traits of rice in the Yangtze River Basin of China during the last 60 yr. Thirteen mid-season indica and 12 japonica rice cultivars that were popularly used were grown in the field in 2008 and 2009. The grain yield and yield components, biomass, leaf area, leaf photosynthesis, root oxidation activity, and harvest index were examined. The results showed that grain yield and grain yield per day have progressively increased during the years and such increases are mainly attributed to the expanded sink size as a result of more spikelets per panicle, especially for the case of super rice. Both biomass and harvest index were increased with the improvement of cultivars. Increase in biomass for modern rice cultivars was associated with an enhancement of leaf area and photosynthesis, root dry weight, and root oxidation activity, although the indica super rice cultivars showed a lower leaf photosynthetic rate and root oxidation activity than the semi-dwarf cultivars during the grain filling period. Both indica and japonica super rice cultivars exhibited a low percentage of filled grains, which may limit their great yield potential. All the data suggested that grain yield have been substantially improved during the 60 yr of rice breeding in the Yangtze River Basin. Expanded sink size, increased dry matter production and harvest index, and enhanced leaf area and photosynthesis, root dry weight, and root oxidation activity contribute to the improvement in grain yield. Increase in filling efficiency could realize the great yield potential in super rice.     

Suitability of the DNDC model to simulate yield production and nitrogen uptake for maize and soybean intercropping in the North China Plain

Intercropping is an important agronomic practice. However, assessment of intercropping systems using field experiments is often limited by time and cost. In this study, the suitability of using the DeNitrification DeComposition(DNDC) model to simulate intercropping of maize(Zea mays L.) and soybean(Glycine max L.) and its aftereffect on the succeeding wheat(Triticum aestivum L.) crop was tested in the North China Plain. First, the model was calibrated and corroborated to simulate crop yield and nitrogen(N) uptake based on a field experiment with a typical double cropping system. With a wheat crop in winter, the experiment included five treatments in summer: maize monoculture, soybean monoculture, intercropping of maize and soybean with no N topdressing to maize(N0), intercropping of maize and soybean with 75 kg N ha~(–1) topdressing to maize(N75), and intercropping of maize and soybean with 180 kg N ha~(–1) topdressing to maize(N180). All treatments had 45 kg N ha~(–1) as basal fertilizer. After calibration and corroboration, DNDC was used to simulate long-term(1955 to 2012) treatment effects on yield. Results showed that DNDC could stringently capture the yield and N uptake of the intercropping system under all N management scenarios, though it tended to underestimate wheat yield and N uptake under N0 and N75. Long-term simulation results showed that N75 led to the highest maize and soybean yields per unit planting area among all treatments, increasing maize yield by 59% and soybean yield by 24%, resulting in a land utilization rate 42% higher than monoculture. The results suggest a high potential to promote soybean production by intercropping soybean with maize in the North China Plain, which will help to meet the large national demand for soybean.     

Multi-Location Investigation of Optimum Planting Density and Boll Distribution of High-Yielding Cotton （G. hirsutum L.） in Hubei Province,China

Cotton yield per unit ground area has stagnated for a dozen years in Hubei Province, China, although a series of new high- yielding varieties have been commercialized. A multi-location investigation was carried out in 2008 and 2009 in 13 counties to determine if increased planting population density （PPD） would break the stagnant yield. The results showed that significant differences among the fields existed in theoretical yield, PPD, and bolls per square meter （BPM）. The lowest yield of 1 641.1 kg ha-I was resulted from the lowest PPD of 1.7 plants m-2 and the lowest BPM of 71.8 bolls m-2, while the highest yield of 2 779.7 kg ha-~ was resulted from the highest PPD of 2.5 plants m-2, and the highest BPM of 129.4 bolls m-z. Plant mapping revealed that boll retention rate （BRR） was maintained over 30 or 40% for the first 17-18 fruiting branches （FBs） and decreased dramatically thereafter, rotten boll rate （RBR） decreased, but open boll rate （OBR） rose first and dropped later with rising FB from the bottom to the top. But BRR, RBR, and OBR were all dropped with the fruiting positions （FPs） extending outwards. The optimum range of plant density would be 2-3 plants m-2 and the proper individual plant structure would be 16-19 FBs with 5-7 FPs for cotton production in Hubei Province.     

Continuous applications of biochar to rice: Effects on grain yield and yield attributes

Biochar is considered as a beneficial soil amendment for crop production. However, limited information is available on the effects of continuous applications of biochar on rice. In this study, a fixed field experiment was conducted in the early and late rice-growing seasons from 2015 to 2017. Grain yield and yield attributes with a widely-grown rice cultivar Zhongzao 39 were compared, with and without applications of biochar in each season. The results showed that grain yield initially decreased with biochar applications in the first three seasons due to decreases in grain weight and harvest index. Although there were further relative decreases in grain weight and harvest index for rice that was supplied with biochar in the fourth to sixth seasons, grain yield was increased(by 4–10%) because of increases in sink size(spikelets per m2) and total biomass. The increased sink size in rice whose soil had been supplied with biochar in the fourth to sixth seasons was achieved by increasing panicle size(spikelets per panicle) or number of panicles, or both. Our study suggests that the positive effects of biochar application on rice yield and yield attributes depend on the duration of biochar application. Further investigations are needed to determine what are the soil and physiological processes for producing yield responses associated with ongoing applications of biochar. Also, it should be evaluated the performance of biochar application combined with other management practices, especially those can increase the grain weight and harvest index in rice production.     

陕西省粮食生产安全的驱动因素分析

以新中国成立以来陕西省的年鉴统计资料为依据,从粮食生产总量、耕地面积、粮食单产3个方面对粮食生产安全的驱动因素进行分析.结果表明:粮食生产总量和单产变化规律基本趋于一致,都呈波动增长趋势;耕地面积总体呈下降趋势,但下降趋势减缓;粮食生产总量由耕地面积和单产决定,当耕地面积逐渐减少时,粮食生产总量的增长只能依赖于粮食单产大幅增加;制约粮食单产的主要因素有:自然灾害、农业基础实施建设与农业投入、农业生态环境、土地政策、耕地质量、农业科技水平和劳动力文化水平等,所有这些因素都使得提高粮食生产综合能力的潜力变得极为有限.为保障陕西省粮食生产安全,针对陕西省粮食单产的影响因素提出了相应的对策建议.     

唐山市粮食生产态势及影响因素分析

唐山市是我国京津地区具有战略意义的商品粮基地,对唐山粮食生产的研究对确保我国京津唐地区粮食安全有重要意义。利用唐山市粮食生产投入产出数据,应用灰色关联度,对影响唐山市粮食总产因素和生产函数对单产的投入因素分别进行分析和模拟。结果表明:影响唐山市粮食产量相关因子的关联度顺序为有效灌溉面积>粮食单产>耕地面积>粮食作物播种面积>农业机械总动力>受灾面积>化肥施用量>机耕面积>农村用电量>劳动力数量;农业机械总动力、有效灌溉面积和用电量对粮食单产有显著的正影响,目前的施肥水平下,氮肥对粮食单产有显著的负影响,磷肥和钾肥则为正影响。     

基于LMDI模型的新疆粮食生产影响因素分析

从新疆耕地利用角度出发,对影响新疆粮食生产变化的因素进行时间和空间上的科学分析,应用对数平均迪氏分解法(Logarithmic mean weigh division,LMDI)对2000~2014年新疆粮食生产影响因素进行分解研究,因素分别分解为耕地面积、粮食单产、复种指数和粮作比例,同时,对粮食产量变动及其分解因素的统计指标在GIS中属性挂链进行空间分析。结果表明,(1)2014年全新疆粮食总产量为1 390.81万t,15年间粮食产量增加552.03万t,其中在14个地州中,塔城地区的粮食增加量最多达到209.70万t;(2)耕地面积、复种指数、粮作比例和粮食单产的贡献产量分别为231.67万t,377.26万t,-202.32万t和145.41万t;(3)从各地州看,粮食生产空间格局分异大,各个分解因素的累加效应存在区域性空间差异。     

基于灰色关联模型的河南省粮食生产驱动力分析

1材料与方法1．1河南省粮食生产特征河南省1978-2006这29年粮食资料统计表明,其粮食产量变化、单位耕地粮食产量及人均粮食总体特征为波动中趋于上升（图见第124页Fig．1）。具体表现为：一是粮食总产量、人均粮食和单产整体呈上升趋势;二是粮食产量波幅较大;三是粮食产量波动频率较高。这种频率过高、幅度较大的波动,极其严重地影响了粮食生产的稳步发展。     

陇中黄土沟壑区粮食生产驱动影响因素及对策研究——以会宁县为例

应用灰色关联分析方法,分析了会宁县1996～2009年粮食产量与粮食单产、粮食作物播种面积、农村劳动力、农用化肥施用折纯量等要素之间的关联程度,揭示了影响粮食产量的驱动因素。结果表明1,996～2009年,会宁县粮食产量表现为阶段性波动增长的特征。从驱动力看,单产是影响粮食产量的首要因素,农用化肥施用折纯量是影响粮食产量的重要因素,农用地膜、节水灌溉等技术的投入是影响粮食产量的关键因素,且表现出很大的潜力,干旱黄土沟壑区特定的资源禀赋是影响粮食产量的基础性因素。     

1988～2008年内蒙古粮食产量影响因素比较

在灰色关联分析的基础上,筛选了粮食单产（X1）、粮食播种面积（X2）、农业劳动力（X3）、农业机械总动力（X4）、化肥施用量（X5）、农作物受灾面积（X6）、有效灌溉面积（X7）和农业固定资产投资（X8）8个对粮食生产影响较显著的因子来构建指标体系。根据1988～2008年《内蒙古统计年鉴》的相关数据,运用灰色关联分析法对影响内蒙古粮食生产的诸因素进行了关联分析,量化了粮食总产量与诸因素的关联程度,并依据关联度值,总结了各因素对粮食产量的影响能力。结果表明,粮食单产始终是影响内蒙古粮食总产量的主要因素;粮食播种面积和受灾面积是影响粮食产量减少的最主要因素;有效灌溉面积和农业机械总动力是影响粮食产量增加的首要因素;化肥施用量对粮食产量的的影响力在下降;农业固定资产投资对粮食产量的影响力始终很小。     

基于LMDI模型的我国省域粮食生产变化影响因素分析

从耕地利用角度对影响粮食生产变化的因素在时间和空间上产生的影响进行科学分析;应用对数平均迪氏分解法(Logarithmic mean weigh division,LMDI)将影响1980—2010年我国省域粮食生产变化的因素分为粮食单产、复种指数、耕地面积和粮作比例;对粮食生产及其分解因素的统计指标在省级层面进行分析。结果表明:1980—2010年我国粮食产量增加22 592.3万t,粮食生产格局重心由南重北轻逐渐演变为北重南轻;4个因素中粮食单产对粮食产量变化起到最显著的促进作用,但增产作用逐年降低,并被复种指数和粮作比例所替代;耕地面积减少在一定程度上限制了我国粮食产量的持续增加;全国各省域之间粮食生产变化的分解因素效应有比较显著的空间差异,河北、湖北、新疆等14个区域的粮食单产和复种指数效应的叠加效应使得其粮食生产增加显著,而上海、浙江、福建等复种指数与粮作比例的叠加效应对粮食增产的影响最大。粮食单产效应的逐渐减小与耕地面积累积效应起负面作用表明我国粮食生产增加主要是粮食单产作用,且正逼于其上限,耕地利用中要严格保护数量,提升耕地质量。     

徐州市粮食生产影响因素的定量研究

采用因子分析方法定量分析了建国以来徐州市粮食生产主要因素的影响程度。从主要影响因素来看,徐州市粮食生产可分为1949~1984年单产提高与机械化共同推进阶段,1984~1999年农业资金投入和水利化共同推进阶段,1999~2005年粮播面积与粮食单产共同推进阶段。在此基础上,总结出各要素的"集体效应"是粮食产量提高的关键,并认为适度扩大粮食播种面积、提高粮食单产、提升农业水利化、机械化水平、增加农业投入等是徐州粮食生产的发展趋势。     

山东省粮食生产变化及其影响因素的灰色关联分析

探索粮食主产区粮食生产波动变化特征及其影响因素,进而有针对性地采取措施来优化粮食生产结构、提高粮食产量对保障国家粮食安全具有重要意义.本文以我国重要的粮食主产区山东省为例,对2000-2012年粮食生产结构以及产量时空变化进行分析,并采用灰色关联分析法探讨影响粮食总产量的主要因素.研究发现,近十几年来山东省粮食总产量及单产小幅波动但基本呈稳定上升趋势,小麦和玉米占粮食生产结构比重不断增加;农业从业人口、作物单产和农业投入是影响粮食生产的最主要因素.     

基于LMDI分解模型的中国粮食主产区增产格局及贡献因素研究

深入分析中国13个粮食主产省份的增产空间格局、作物结构、贡献因素,为维系其增长态势、优化粮食生产布局、调整种植结构,实现主产区粮食稳步增产提供决策依据。运用LMDI分解模型和GIS空间分析法,将主产区粮食总产量分解为播种面积和作物单产2种因素,分析其增产格局及增产贡献因素。从主产区粮食增产量的空间分布来看：北方主产区优于南方主产区,粮食增产重心呈现出较为明显的北移趋势;增产结构上看,玉米为主要贡献品种,其次为小麦,稻谷贡献率最低;主产区粮食增产贡献因素来看,单产的贡献率高于播面的贡献率,且空间差异明显。分作物看稻谷和玉米的播种面积效应为正值,玉米大于稻谷,小麦的播种面积效应产生负向影响;3种作物的单产效应均为正值,小麦的单产效应最为显著,小麦>稻谷>玉米。面积增加和单产提高都对主产区粮食产量增加产生了积极的贡献。对于主要依靠播面增加来提高产量的地区,应调整种植结构,合理轮作,挖掘优势作物,增加农业技术推广,提高土地产出;对于单产贡献显著的地区,要发展特色产业优势区,形成集群化发展,在生产、流通、销售环节提供全方位的服务,防止增产不增收的现象发生。