Soil texture, climate and management effects on plant growth, grain yield and water use by rainfed maize–wheat cropping system: Field and simulation study

In sub-mountain tract of Punjab state of India, maize (Zea mays, L.) and wheat (Triticum aestivum L.) crops are grown as rainfed having low crop and water productivity. To enhance that, proper understanding of the factors (soil type, climate, management practices and their interactions) affecting it is a pre-requisite. The present study aims to assess the effects of tillage, date of sowing, and irrigation practices on the rainfed maize–wheat cropping system involving combined approach of field study and simulation. Field experiments comprising 18 treatments (three dates of sowing as main, three tillage systems as subplot and two irrigation regimes as the sub-subplot) were conducted for two years (2004–2006) and simulations were made for 15 years using CropSyst model. Field and simulated results showed that grain yields of maize and wheat crops were more in early July planted maize and early November planted wheat on silt loam soil. Different statistical parameters (root mean square error, coefficient of residual mass, model efficiency, coefficient of correlation and paired t-test) indicated that CropSyst model did fair job to simulate biomass production and grain yield for maize–wheat cropping system under varying soil texture, date of planting and irrigation regimes.     

Agricultural water productivity assessment for the Yellow River Basin

Agricultural water productivity (WP) has been recognized as an important indicator of agricultural water management. This study assesses the WP for irrigated (WPI) and rainfed (WPR) crops in the Yellow River Basin (YRB) in China. WPI and WPR are calculated for major crops (corn, wheat, rice, and soybean) using experimental, statistical and empirically estimated data. The spatial variability of WPI and WRR is analyzed with regard to water and energy factors. Results show that although irrigated corn and soybean yields are significantly higher than rainfed yields in different regions of the YRB, WPI is slightly lower than WPR for these two crops. This can be explained by the seasonal coincidence of precipitation and solar energy patterns in the YRB. However, as expected, irrigation stabilizes crop production per unit of water consumption over space. WPI and WPR vary spatially from upstream to downstream in the YRB as a result of varying climate and water supply conditions. The water factor has stronger effects on both crop yield and WP than the energy factor in the upper and middle basin, whereas energy matters more in the lower basin. Moreover, WP in terms of crop yield is compared to that in terms of agricultural GDP and the results are not consistent. This paper contributes to the WP studies by a basin context, a comparison between WPI and WPR, a comparison of WP in terms of crop yield and economic value, and insights on the water and energy factors on WP. Moreover, policy implications based on the WP analysis are provided.     

Crop yield responses to climate change in the Huang-Huai-Hai Plain of China

Global climate change may impact grain production as atmospheric conditions and water supply change, particularly intensive cropping, such as double wheat-maize systems. The effects of climate change on grain production of a winter wheat-summer maize cropping system were investigated, corresponding to the temperature rising 2 and 5 °C, precipitation increasing and decreasing by 15% and 30%, and atmospheric CO₂ enriching to 500 and 700 ppmv. The study focused on two typical counties in the Huang-Huai-Hai (3H) Plain (covering most of the North China Plain), Botou in the north and Huaiyuan in the south, considering irrigated and rain-fed conditions, respectively. Climate change scenarios, derived from available ensemble outputs from general circulation models and the historical trend from 1996 to 2004, were used as atmospheric forcing to a bio-geo-physically process-based dynamic crop model, Vegetation Interface Processes (VIP). VIP simulates full coupling between photosynthesis and stomatal conductance, and other energy and water transfer processes. The projected crop yields are significantly different from the baseline yield, with the minimum, mean (±standardized deviation, SD) and maximum changes being −46%, −10.3 ± 20.3%, and 49%, respectively. The overall yield reduction of −18.5 ± 22.8% for a 5 °C increase is significantly greater than −2.3 ± 13.2% for a 2 °C increase. The negative effect of temperature rise on crop yield is partially mitigated by CO₂ fertilization. The response of a C3 crop (wheat) to the temperature rise is significantly more sensitive to CO₂ fertilization and less negative than the response of C4 (maize), implying a challenge to the present double wheat-maize systems. Increased precipitation significantly mitigated the loss and increased the projected gain of crop yield. Conversely, decreased precipitation significantly exacerbated the loss and reduced the projected gain of crop yield. Irrigation helps to mitigate the decreased crop yield, but CO₂ enrichment blurs the role of irrigation. The crops in the wetter southern 3H Plain (Huaiyuan) are significantly more sensitive to climate change than crops in the drier north (Botou). Thus CO₂ fertilization effects might be greater under drier conditions. The study provides suggestions for climate change adaptation and sound water resources management in the 3H Plain.     

Land allocation conditioned on El Niño-Southern Oscillation phases in the Pampas of Argentina

The El Niño-Southern Oscillation (ENSO) contributes to the vulnerability of crop production to climate variability in the Pampas region of Argentina. Predictability of regional climate anomalies associated with ENSO may provide opportunities to tailor decisions to expected climate, either to mitigate expected adverse conditions or to take advantage of favorable conditions. Model analysis was used to explore the potential for tailoring land allocation among crops to ENSO phases at the farm scale in two sub-regions of the Pampas. The model identifies as a function of risk preferences and initial wealth the crop mix that maximizes expected utility of wealth at the end of a 1-year decision period based on current costs and prices, and crop yields simulated for each year of historical weather. The model reproduced recent land allocation patterns at the district scale under moderate risk aversion, and predicted increasing diversification with increasing risk aversion. Differences in land allocation among ENSO phases were consistent with known climate response to ENSO, and crop response to water availability. Tailoring land allocation to ENSO phase increased mean net farm income between US$5 and $15 ha⁻¹ year⁻¹ relative to optimizing the crop mixture for all years, depending on location, risk aversion and initial wealth. The relationship between potential value of ENSO information and risk aversion was not monotonic, and differed between locations. Crop mix and information value also varied with crop prices and initial soil moisture. There are potential financial benefits of applying this approach to tailoring decisions to ENSO phases.     

Increasing water productivity with improved N fertilizer management

There is continuing debate about the role of water productivity and the potential to increase it in response to significantly increased water demand to meet the future needs for food—estimated to be roughly double that of today by 2050. The debate centers round the relative potential benefits of enhancing rainfed agriculture, improving irrigation and expanding areas of both. All expansion and intensification options will require significantly more water to be used, often in places where the ecosystem impacts of agriculture are already severe. Improvement in water productivity can result from improving the provision and management of the other factor inputs of crop production. There is considerable debate on the ability of other inputs—typically nitrogen—to substitute for water. This paper describes a set of simulations undertaken with well calibrated maize (Zea mays L.) crop model in Decision Support System for Agro-technology Transfer (DSSAT). The simulations investigate the response to nitrogen under rainfed conditions in Florida, and show that neither the transpiration ratio nor the harvest index are constant in practice, and that fertilizer use can enhance water productivity, even in quite high yield conditions and that the transpiration ratio can be increased by N fertilizer application at low levels of crop water use.     

气候变化条件下旱作玉米用水效率与单产变化趋势分析

以渭北旱塬合阳和长武2个试验站点为研究区域,通过多年的玉米田间试验数据评估CERES-Maize模型的适用性,再利用区域气候模式Reg CM4.0输出的气象数据对2050年前玉米单产及生产水足迹进行预测。结果表明:CERES-Maize模型可以很好地模拟雨养玉米产量和物候期,多数年份二者的绝对相对误差(Absolute relative error,ARE)在10%以内,CERES-Maize模型在渭北旱塬旱作农业区有很好的适用性。应用CERES-Maize模型模拟玉米生产水足迹,较传统水足迹计算方法得到的结果更为精确可靠。在RCP2.6气候情景下,随着温度升高和生育期有效降水量的增加,玉米产量呈上升趋势;在RCP8.5气候情景下,随着温度升高和生育期有效降水的减少,玉米产量呈下降趋势。气温上升幅度过大对玉米单产有明显的负面影响,降水与玉米用水效率呈正相关。为有效应对气候变化对旱作作物产量造成的负面影响,应采取减少温室气体排放量、增强土壤蓄水保墒能力、发展集雨补灌、筛选和培育节水抗旱新品种等措施。     

Effects of winter crop and supplemental irrigation on crop yield,water use efficiency and profitability in rainfed rice based cropping system of eastern India

Soil moisture availability is the main limiting factor for growing second crops in rainfed rice fallows of eastern India. Only rainfed rice is grown with traditional practices during the rainy season (June–October) with large areas (13 m ha⁻¹) remaining fallow during the subsequent dry season (November–March) inspite of annual rainfall of the order 1000–2000 mm. In this study an attempt was made to improve productivity of rainfed rice during rainy season and to grow second crops in rice fallow during dry (winter) season with supplemental irrigation from harvested rainwater. Rice was grown as first crop with improved as well as traditional farmers’ management practices to compare the productivity between these two treatments. Study revealed that 87.1–95.6% higher yield of rice was obtained with improved management over farmers’ practices. Five crops viz., maize, groundnut, sunflower, wheat and potato were grown in rice fallow during dry (winter) season with two, three and four supplemental irrigations and improved management. Sufficient amount of excess rainwater (runoff) was available (381 mm at 75% probability level) to store and recycle for supplementary irrigation to second crops grown after rice. Study revealed that supplemental irrigation had significant effect (P < 0.001) on grain yield of dry season crops and with two irrigation mean yields of 1845, 785, 905, 1420, 8050 kg ha⁻¹ were obtained with maize (grain), groundnut, sunflower, wheat and potato (tuber), respectively. With four irrigations 214, 89, 78, 81, 54% yield was enhanced over two irrigations in respective five crops. Water use efficiency (WUE) of 13.8, 3.35, 3.39, 5.85 and 28.7 kg ha⁻¹ was obtained in maize, groundnut, sunflower, wheat, potato (tuber), respectively with four irrigations. The different plant growth parameters like maximum above ground biomass, leaf area index and root length were also recorded with different levels of supplemental irrigation. The study amply revealed that there was scope to improve productivity of rainfed rice during rainy season and to grow another profitable crops during winter/dry season in rice fallow with supplemental irrigation from harvested rainwater of rainy season.     

Designing crop technology for a future climate: An example using response surface methodology and the CERES-Wheat model

Future crop production will be adapted to climate change by implementing alternative management practices and developing new genotypes that are adapted to future climatic conditions. It is difficult to predict what new agronomic technologies will be necessary for crop production under future climatic conditions. The purpose of this work was to develop an approach useful in identifying crop technologies for future climatic conditions. As an example of the approach, we used response surface methodology (RSM) in connection with the CERES-Wheat model and the HADCM2 climate simulation model to identify optimal configurations of plant traits and management practices that maximize yield of winter wheat in high CO₂ environments. The simulations were conducted for three Nebraska locations differing in altitude and rainfall (Lincoln, Dickens and Alliance), which were considered representative of winter wheat growing areas in the central Great Plains. At all locations, the identified optimal winter wheat cultivar under high CO₂ conditions had a larger number of tillers, larger kernel size, fewer days to flower, grew faster and had more kernels m⁻² than the check cultivar under normal CO₂ conditions. In addition, optimal sowing dates were later and optimal plant densities were smaller than under normal conditions. We concluded that RSM used in conjunction with crop and climate simulation models was useful in understanding the complex relationship between wheat genotypes, climate and management practices.     

Nutrient management adaptation for dryland maize yields and water use efficiency to long-term rainfall variability in China

Rainfed crop production in northern China is constrained by low and variable rainfall, and by improper management practices. This study explored both the impact of long-term rainfall variability and the long-term effects of various combinations of maize stover, cattle manure and mineral fertiliser (NP) applications on maize (Zea mays L.) yields and water use efficiency (WUE) under reduced tillage practices, at Shouyang Dryland Farming Experimental Station in northern China from 1993 onwards. The experiment was set up according to an incomplete, optimal design, with 3 factors at five levels and 12 treatments including a control with two replications. Grain yields were greatly influenced by the amount of rain during the growing season, and by soil water at sowing. Annual mean grain yields ranged from 3 to 10 t ha⁻¹ and treatment mean yields from 4.2 to 7.2 t ha⁻¹. The WUE ranged from 40 in treatments with balanced nutrient inputs in dry (weather/or soil) years to 6.5 kg ha⁻¹ mm⁻¹ for the control treatments in wet years. The WUE averaged over the 15-year period ranged from 11 to 19 kg ha⁻¹ mm⁻¹. Balanced combination of stover (3000-6000 kg), manure (1500-6000 kg) and N fertiliser (105 kg) gave the highest yield and hence WUE. It is suggested that 100 kg N per ha should be a best choice, to be adapted according to availability of stover and manure. Possible management options under variable rainfall conditions to alleviate occurring moisture stress for crops must be tailored to the rainfall pattern. The potentials of split applications, targeted to the need of the growing crop (response nutrient management), should be explored to further improve grain yield and WUE.     

土壤空间变异对水氮淋失和产量影响的模拟研究

基于CERES-Maize模型,研究了土壤空间变异和水文年型对半干旱地区土壤水氮淋失和玉米产量的影响.结果表明,土壤空间变异对作物产量和土壤水氮淋失的影响程度与降雨密切相关.丰水年水氮淋失量显著高于平水年和枯水年.降雨对作物产量和农田尺度水氮淋失的空间变异有明显影响,并能在一定程度上减弱土壤空间变异对产量和农田尺度水氮淋失的影响.随着土壤空间变异程度的增大,产量降低,产量的空间变异程度增加.水分渗漏和氮淋失量随土壤空间变异的增加呈增加趋势.当土壤黏粒和粉粒含量变异系数CV≥0.2时,在水氮管理中考虑土壤空间变异有利于提高作物产量,减轻水氮淋失.     

Effects of deficit irrigation scheduling on yields and soil water balance of irrigated maize

This paper presents the findings of the effect of some selected deficit irrigation scheduling practices on irrigated maize crop in a sub-catchment in south western part of Tanzania. Field experiments, in which maize (TMV1-ST) variety was planted under total irrigation, were conducted during the dry seasons of 2004 and 2005. Surface irrigation method was used and the crop was planted in basins. The seasonal water applied ranged from 400 to 750 mm. Soil moisture content from both cropped and bare soils, leaf area index, dry matter, and grain yields were measured. The dry matter yield ranged between 6,966 and 12,672 kg/ha, and grain yields obtained were between 1,625 and 4,349 kg/ha. The results showed that deficit irrigation at any crop growth stage of the maize crop led to decrease in dry matter and grain yields, seasonal evapotranspiration and deep percolation. Deficit irrigation in any one growth stage of the maize crop only seems to affect grain production and no significant effect on biomass production, but deficit irrigation that spanned across two or more growth stages affect both biomass and grain production drastically. Crop water use efficiency (WUE) and Irrigation water use efficiency (IWUE) were strongly influenced by the number of growth stages in which deficit irrigations were applied and how critical the growth stages were to moisture stress rather than the amount of irrigation water applied. While maximum WUE was obtained under full irrigation, maximum IWUE was obtained in the deficit irrigation treatment at vegetative growth stage, which suggest that IWUE may be improved upon by practicing deficit irrigation at the vegetative growth stage of the maize crop.     

Adapting to climate change: Agricultural system and household impacts in East Africa

The East African region exhibits considerable climatic and topographic variability. Much spatial and temporal variation in the response of different crops to climate change can thus be anticipated. In previous work we showed that a large part of this variation can be explained in terms of temperature and, to a lesser extent, water effects. Here, we summarise simulated yield response in two crops that are widely grown in the region, maize and beans, and investigate how the impacts of climate change might be addressed at two levels: the agricultural system and the household. Regionally, there are substantial between-country and within-system differences in maize and bean production responses projected to 2050. The arid-semiarid mixed crop-livestock systems are projected to see reductions in maize and bean production throughout most of the region to 2050. Yields of these crops in the tropical highland mixed systems are projected to increase, sometimes substantially. The humid-subhumid mixed systems show more varied yield responses through time and across space. Some within-country shifts in cropping away from the arid-semiarid systems to cooler, higher-elevation locations may be possible, but increased regional trade should be able to overcome the country-level production deficits in maize and beans caused by climate change to 2050, all other things being equal. For some places in the tropical highlands, maize and bean yield increases could have beneficial effects on household food security and income levels. In the other mixed systems, moderate yield losses can be expected to be offset by crop breeding and agronomic approaches in the coming decades, while more severe yield losses may necessitate changes in crop types, movement to more livestock-orientated production, or abandonment of cropping altogether. These production responses are indicative only, and their effects will be under-estimated because the methods used here have not accounted for increasing weather variability in the future or changes in the distribution and impacts of biotic and other abiotic stresses. These system-level shifts will take place in a context characterised by high population growth rates; the demand for food is projected to nearly triple by the middle of this century. Systems will have to intensify substantially in response, particularly in the better-endowed mixed systems in the region. For the more marginal areas, the variability in yield response, and the variability in households’ ability to adapt, suggest that, even given the limitations of this analysis, adaptation options need to be assessed at the level of the household and the local community, if research for development is to meet its poverty alleviation and food security targets in the face of global change.     

Regional crop modelling in Europe: The impact of climatic conditions and farm characteristics on maize yields

Impacts of climate variability and climate change on regional crop yields are commonly assessed using process-based crop models. These models, however, simulate potential and water limited yields, which do not always relate to observed yields. The latter are largely influenced by crop management, which varies by farm and region. Data on specific management strategies may be obtained at the field level, but at the regional level information about the diversity in management strategies is rarely available and difficult to be considered adequately in process-based crop models. Alternatively, understanding the factors influencing management may provide helpful information to improve simulations at the regional level.In this study, we aim to identify factors at the regional level that explain differences between observed and simulated yields. Observed yield data were provided by the Farm Accountancy Data Network (FADN) and Eurostat. The Crop Growth Monitoring System (CGMS), based on the WOFOST model, was used to simulate potential and water limited maize yields in the EU15 (i.e., the old member states of the European Union). Differences between observed and simulated maize yields were analysed using regression models including: (i) climatic factors (temperature and precipitation), (ii) farm size, (iii) farm intensity, (iv) land use, (v) income and (vi) subsidies. We assumed that the highest yields observed in a region were close to the yield potential as determined by climate and considered the average regional yields as also influenced by management. Model performance was analysed with respect to spatial and temporal yield variability.Results indicate that for potential yield, the model performed unsatisfactory in southern regions, where high temperatures increased observed yields which was in contrast to model simulations. When considering management effects, we find that especially irrigation and the maize area explain much of the differences between observed and simulated yields across regions. Simulations of temporal yield variability also diverted from observed data of which about 80% could be explained by the climatic factors (35%) and farm characteristics (50%) considered in the analysis. However, effects of specific factors differed depending on the regions. Accordingly, we propose different groups of regions with factors related to management which should be considered to improve regional yield simulations with CGMS.     

Calibration and use of CROPGRO-soybean model for improving soybean management under rainfed conditions

Crops such as soybean (Glycine max L.) are grown predominantly under rainfed conditions where water is a major limiting factor and the interannual variability in rainfall pattern is high. Crop modeling has proven a valuable tool to evaluate the long-term consequences of weather patterns, but the candidate crop models must be tested and calibrated for new regions prior to their use as extrapolation tools to predict optimum cultivar choice and sowing dates. The objectives of this paper were to calibrate the CROPGRO-soybean model for growth and yield under rainfed conditions in Galicia, northwest Spain, and then to use the calibrated model to establish the best sowing dates for three cultivars at three locations in this region. The starting point of the calibration process was the CROPGRO-soybean version previously calibrated for non-limiting water conditions. The original model, when simulated versus rainfed soybean field data sets, tended to simulate more severe water stress than actually occurred. In order to calibrate growth and yield for the actual soil we tried several ways for the modelled crop to have access to more water. Modifications were made on soil depth, water holding capacity, and root elongation rate. In addition, other changes were made to predict accurately the observed water-stress induced acceleration of maturity. Long-term simulations with recorded weather data showed that soybean is more sensitive to planting date under irrigated than rainfed management, in the three studied Galician locations.     

Yield gap of rainfed rice in farmers’ fields in Central Java, Indonesia

Yield constraint analysis for rainfed rice at a research station gives insight into the relative role of occurring yield-limiting factors. However, soil nutrient status and water conditions along toposequences in rainfed farmers’ fields may differ from those at the research station. Therefore, yield constraints need to be analyzed in farmers’ fields in order to design management strategies to increase yield and yield stability.We applied production ecological concepts to analyze yield-limiting factors (water, N) on rice yields along toposequences in farmers’ fields using data from on-farm experiments conducted in 2000-2002 in Indonesia. Potential, water-limited, and N-limited yields were simulated using the ORYZA2000 crop growth model. Farmers’ fields showed large spatial and temporal variation in hydrology (354-1235 mm seasonal rainfall, −150 to 50 cm field-water depth) and fertilizer doses (76-166 N, 0-45 P, and 0-51 kg K ha⁻¹). Farmers’ yields ranged from 0.32 to 5.88 Mg ha⁻¹. The range in yield gap caused by water limitations was 0-28% and that caused by N limitations 35-63%, with large temporal and spatial variability.The relative limitations of water and N in farmers’ fields varied strongly among villages in rainfed rice areas and toposequence positions, with yield gaps due to water and N at the top and upper middle positions higher than at the lower middle and bottom toposequence positions, and yield gaps in late wet seasons higher than those in early wet seasons. Management options (e.g. crop establishment dates, shortening turnaround time, using varieties with shorter duration, supplemental irrigation) to help the late-season crop escape, or minimize the negative effects of, late-season droughts and supplying adequate N-fertilizer are important for increasing yield in rainfed lowland rice in Indonesia. More N-fertilizer should be given to upper toposequence positions than to lower positions because the former had a lower indigenous nutrient supply and hence a better response to N-fertilizer inputs. Systems approaches using production ecological concepts can be applied in yield constraint analysis for indentifying management strategies to increase yield and yield stability in farmers’ fields in other rainfed lowland areas.     

Simulation of furrow irrigation practices (SOFIP): a field-scale modelling of water management and crop yield for furrow irrigation

Because of the spatial and temporal variabilities of the advance infiltration process, furrow irrigation investigations should not be limited to a single furrow irrigation event when using a modelling approach. The paper deals with the development and application of simulation of furrow irrigation practices (SOFIP), a model used to analyse furrow irrigation practices that take into account spatial and temporal variabilities of the advance infiltration process. SOFIP can be used to compare alternative furrow irrigation management strategies and find options that mitigate local deep-percolation risks while ensuring a crop yield level that is acceptable to the farmer. The model is comprised of three distinct modelling elements. The first element is RAIEOPT, a hydraulic model that predicts the advance infiltration process. Infiltration prediction in RAIEOPT depends on a soil moisture deficit parameter. PILOTE, a crop model, which is designed to simulate soil water balance and predict yield values, updates the soil moisture parameter. This parameter is an input of a parameter generator (PG), the third model component, which in turn provides RAIEOPT with the data required to simulate irrigation at the scale of an N-furrow set. The study of sources of variability and their impact on irrigation advance, based on field observations, allowed us to build a robust PG. Model applications show that irrigation practices must account for inter-furrow advance variability when optimising furrow irrigation systems. The impact of advance variability on deep percolation and crop yield losses depends on both climatic conditions and irrigation practices.     

Wind effects on solid set sprinkler irrigation depth and yield of maize (<Emphasis Type="Italic">Zea mays</Emphasis>)

A field experiment was performed to study the effect of the space and time variability of water application on maize (Zea mays) yield when irrigated by a solid set sprinkler system. A solid set sprinkler irrigation layout, typical of the new irrigation developments in the Ebro basin of Spain, was considered. Analyses were performed (1) to study the variability of the water application depth in each irrigation event and in the seasonal irrigation and (2) to relate the spatial variability in crop yield to the variability of the applied irrigation and to the soil physical properties. The results of this research showed that a significant part of the variability in the Christiansen coefficient of uniformity (CU), and wind drift and evaporation losses were explained by the wind speed alone. Seasonal irrigation uniformity (CU of 88%) was higher than the average uniformity of the individual irrigation events (CU of 80%). The uniformity of soil water recharge was lower than the irrigation uniformity, and the relationship between both variables was statistically significant. Results indicated that grain yield variability was partly dictated by the water deficit resulting from the non-uniformity of water distribution during the crop season. The spatial variability of irrigation water depth when the wind speed was higher than 2 m s^–1 was correlated with the spatial variability of grain yield, indicating that a proper selection of the wind conditions is required in order to attain high yield in sprinkler-irrigated maize.     

Crop rotations in Argentina: Analysis of water balance and yield using crop models

Cropping schemes have developed in east-central Argentina for rainfed soybean (Glycine max Merr.) production that invariably employ no-tillage management. Often these schemes include growing soybean in a sequence of crops including wheat (Triticum aestivum L.) and maize (Zea mays L.). The full impact of various rotation schemes on soil water balance through a sequence of seasons has not been explored, although the value of these rotations has been studied experimentally. The objective of this work was to investigate through simulations, potential differences in temporal soil water status among rotations over five years. In this study, mechanistic models of soybean (Soy), maize (Maz), and wheat (Wht) were linked over a five-years period at Marcos Juárez, Argentina to simulate soil water status, crop growth, and yield of four no-till rotations (Soy/Soy, Soy/Wht, Soy/Maz, and Soy/Maz/Wht). Published data on sowing dates and initial soil water contents in the first year from a no-till rotation experiment were used as inputs to the model. After the first year, soil water status output from the model was used to initiate the next crop simulation in the sequence. The results of these simulations indicated a positive impact on soil water balance resulting from crop residue on the soil surface under no-till management. Continuous soybean and the two-year soybean/maize rotation did not efficiently use the available water from rainfall. Residue from maize was simulated to be especially effective in suppressing soil evaporation. Thus, the Soy/Maz simulation results indicated that this rotation resulted in enhanced soil water retention, increased deep water percolation, and increased soybean yields compared with continuous soybean crops. The simulated results matched well with experimental observations. The three-crop rotation of Soy/Maz/Wht did not increase simulated soybean yields, but the additional water retained as a result of decreased soil evaporation resulting from the maize residue allowed the addition of a wheat crop in this two-year rotation. Simulated soybean yields were poorly correlated with both the amount of soil water at sowing and the rainfall during the cropping period. These results highlight the importance of temporal distribution of rainfall on final yield. These models proved a valuable tool for assessing the consequences of various rotation schemes now being employed in Argentina on temporal soil water status, and ultimately crop yield.     

Modeling wheat yield and crop water productivity in Iran: Implications of agricultural water management for wheat production

In most parts of Iran, water scarcity has been intensifying and posing a threat to the sustainability of agricultural production. Wheat is the dominant crop and the largest irrigation water user in Iran; hence, understanding of the crop yield-water relations in wheat across the country is essential for a sustainable production. Based on a previously calibrated hydrologic model, we modeled irrigated and rainfed wheat yield (Y) and consumptive water use (ET) with uncertainty analysis at a subbasin level in Iran. Simulated Y and ET were used to calculate crop water productivity (CWP). The model was then used to analyze the impact of several stated policies to improve the agricultural system in Iran. These included: increasing the quantity of cereal production through more efficient use of land and water resources, improving activities related to soil moisture conservation and retention, and optimizing fertilizer application. Our analysis of the ratio of water use to internal renewable water resources revealed that 23 out of 30 provinces were using more than 40% of their water resources for agriculture. Twelve provinces reached a ratio of 100% and even greater, indicating severe water scarcity and groundwater resource depletion. An analysis of Y-CWP relationship showed that one unit increase in rainfed wheat yield resulted in a lesser additional water requirement than irrigated wheat, leading to a larger improvement in CWP. The inference is that a better water management in rainfed wheat, where yield is currently small, will lead to a larger marginal return in the consumed water. An assessment of improvement in soil available water capacity (AWC) showed that 18 out of 30 provinces are more certain to save water while increasing AWC through proper soil management practices. As wheat self-sufficiency is a desired national objective, we estimated the water requirement of the year 2020 (keeping all factors except population constant) to fulfill the wheat demand. The results showed that 88% of the additional wheat production would need to be produced in the water scarce provinces. Therefore, a strategic planning in the national agricultural production and food trade to ensure sustainable water use is needed. This study lays the basis for a systematic analysis of the potentials for improving regional and national water use efficiency. The methodology used in this research, could be applied to other water scarce countries for policy impact analysis and the adoption of a sustainable agricultural strategy.     

2ZYS-2型玉米育苗滤水移栽机的研制

玉米是黑龙江省种植面积最大、分布范围最广、总产量最高的优势作物,其栽培模式长期以来以直播为主。玉米移栽技术是一项抗旱高产新型农艺栽培技术,相比传统的直播种植方式,移栽能够使玉米作物提高有效积温时间、减少春季低温伤害、提高抵抗病虫害的能力,从而确保纸筒秧苗存活率率,提高玉米的产量和品质。过去玉米移栽大都采用人工的方式进行,劳动力需求大,作业效率低下,移栽质量难以保证,无法进行大面积推广应用。玉米育苗滤水移栽机的研制成功为玉米机械化移栽提供有效机械载体,填补了我国在该类型农机装备方面的空白。