Irrigated Production Systems Research Articles

Impacto de plantas de cobertura e da drenagem do solo nas emissões de CH 4 e N 2 O sob cultivo de arroz irrigado

Resumo O objetivo deste trabalho foi avaliar o impacto das plantas de cobertura de inverno azevém (Lolium multiflorum) e azevém+cornichão (Lotus corniculatus), bem como da drenagem parcial do solo, nas emissões de CH4 e N2O em um Planossolo cultivado com arroz irrigado. Amostras de ar foram coletadas semanalmente com câmara estática fechada, parcialmente inserida no solo (0,05 m). Calcularam-se o potencial de aquecimento global parcial (PAGp=CH4×25+N2O×298) e o PAGp por unidade de produtividade de grãos (PAGpPG). A drenagem parcial foi estabelecida pela suspenção temporária da irrigação por períodos de 8 a 15 dias, durante três ocasiões ao longo do ciclo da cultura. O aporte de resíduos pelas plantas de cobertura intensificou os fluxos de CH4 do solo, que excederam em dez vezes a emissão acumulada do solo em pousio invernal. As emissões de N2O foram maiores com o consórcio azevém+cornichão, em comparação ao azevém e ao pousio. O cultivo de plantas de cobertura elevou o índice PAGpPG (0,35 kg de CO2eq por quilograma de arroz), comparativamente ao pousio (0,06 kg kg-1). Nos tratamentos com cobertura de inverno, as estratégias de mitigação devem focar principalmente no CH4, que foi responsável pela maior porção (80%) do PAGp. A drenagem parcial reduziu em até 50% o PAGp e apresenta grande potencial para mitigar as emissões de gases em sistemas de produção de arroz irrigado.

Mapping Slight and Moderate Saline Soils in Irrigated Agricultural Land Using Advanced Land Imager Sensor (EO-1) Data and Semi-Empirical Models

ABSTRACTAround the world, especially in semi-arid regions, millions of hectares of irrigated agricultural land are abandoned each year because of the adverse effects of irrigation, mainly secondary salinity and sodicity. Accurate information about the extent, magnitude, and spatial distribution of salinity and sodicity will help create the sustainable development of agricultural resources. In Morocco, south of the Mediterranean region, the growth of the vegetation and potential yield are limited by the joint influence of high temperatures and water deficit. Consequently, the overuse of surface and ground water, coupled with agricultural intensification, generates secondary soil salinity. Knowing when, where, and how salinity may occur is very important to the sustainable development of any irrigated production system. Remedial actions require reliable information to help set priorities and to choose the type of action that is most appropriate in each situation. Ground-based electromagnetic measurements of soil electrical conductivity (EC) are generally accepted as the most effective method for quantification of soil salinity. Unfortunately, these methods are expensive, time consuming, and need considerable human resources for land surveying. Moreover, the dynamic nature of soil salinity in space and time makes it more difficult to use conventional methods for comparisons over large areas. A major challenge of remote sensing, as a potential alternative technique, is to detect different levels of soil salinity. The main aim of this research is to assess the potential of the Advanced Land Imager (ALI) sensor on board the Earth Observing-1 (EO-1) satellite, with its rich infrared bands, for the discrimination and mapping of slight and moderate soil salinity in the Tadla’s irrigated agricultural perimeter in Morocco. To achieve this goal, semi-empirical predictive models developed in a previous study using second order regression analysis between the EC of salt-affected soils and different spectral salinity indices were applied to the ALI image. This was atmospherically corrected and the radiometric sensor drift was calibrated. Visual comparisons and statistical validation of these models using ground truth were undertaken in order to identify the best semi-empirical model for slight and moderate salinity mapping. The obtained results show that the model based on the Normalized Difference Salinity Index (NDSI) does not give any results. The model based on the Salinity Index-1 (SI-1) and the SI-Advanced Space-borne Thermal Emission and Reflection Radiometer (SI-ASTER) confuses vegetation with high soil salinity, although the model does bring out areas of lower salinity. Both R2 of 0.67 for the SI-1 and 0.65 for the SI-ASTER further reinforce that these models cause too much confusion to be used with accuracy for salt-affected soil detection. The semi-empirical model based on Soil Salinity and Sodicity Index-1 (SSSI-1) performs better than the two last models. However, there is a relative confusion between the classes in the slight and moderate salinity and in areas that are shown by the validation map; the higher class of salinity does not appear to contain higher levels of salinity. The statistical validation of this model reinforces what is seen on the derived map with only an R2 = 0.68. The model based on the SSSI-2 clearly provides the best results in comparison to the ground truth. Its derived map gives the closest overall visual approximation of the EC map, with a whole range of values. With a statistical validation of R2 = 0.97 to the ground truth, it is by far the best performance of any of the other models, and the different classes are statistically well separated, which further reinforces the accuracy of the visual analysis.

Economic performance of irrigation capacity development to adapt to climate in the American Southwest

Growing demands for food security to feed increasing populations worldwide have intensified the search for improved performance of irrigation, the world’s largest water user. These challenges are raised in the face of climate variability and from growing environmental demands. Adaptation measures in irrigated agriculture include fallowing land, shifting cropping patterns, increased groundwater pumping, reservoir storage capacity expansion, and increased production of risk-averse crops. Water users in the Gila Basin headwaters of the U.S. Lower Colorado Basin have faced a long history of high water supply fluctuations producing low-valued defensive cropping patterns. To date, little research grade analysis has investigated economically viable measures for irrigation development to adjust to variable climate. This gap has made it hard to inform water resource policy decisions on workable measures to adapt to climate in the world’s dry rural areas. This paper’s contribution is to illustrate, formulate, develop, and apply a new methodology to examine the economic performance from irrigation capacity improvements in the Gila Basin of the American Southwest. An integrated empirical optimization model using mathematical programming is developed to forecast cropping patterns and farm income under two scenarios (1) status quo without added storage capacity and (2) with added storage capacity in which existing barriers to development of higher valued crops are dissolved. We find that storage capacity development can lead to a higher valued portfolio of irrigation production systems as well as more sustained and higher valued farm livelihoods. Results show that compared to scenario (1), scenario (2) increases regional farm income by 30%, in which some sub regions secure income gains exceeding 900% compared to base levels. Additional storage is most economically productive when institutional and technical constraints facing irrigated agriculture are dissolved. Along with additional storage, removal of constraints on weak transportation capacity, limited production scale, poor information access, weak risk-bearing capacity, limited management skills, scarce labor supply, low food processing capacity, and absolute scale constraints, all can raise the economic value of additional irrigation capacity development. Our results light a path forward to policy makers, water administrators, and farm managers, who bear the burden of protecting farm income, food and water security, and rural economic development in the world’s dry regions faced by the need to adapt to climate variability.

Genetic Diversity of Natural Crossing in Six Cotton Cultivars

We have previously shown genetic diversity in mature cotton (Gossypium hirsutum L.) pollen sensitivity to low humidity. In vitro studies showed reduced pollen germination and pollen tube growth under low humidity. The present study investigated the impact of pollen sensitivity to low humidity on the amount of outcrossing to neighboring plants. We utilized “red” and “green” pigmented cotton, in addition to gossypol glanded and glandless cotton cultivars, to study pollen movement in the field. Genetic diversity in outcrossing was observed among the six cultivars tested. Differences in outcrossing of 5 to 15% were observed under both irrigated and dryland production systems. Higher levels of outcrossing were observed within a row compared to outcrossing between rows. Cotton cultivars with mature pollen sensitive to low humidity exhibited reduced outcrossing compare to cultivars that were less sensitive to low humidity. These results suggest that cultivars with pollen sensitive to low humidity can be used to reduce natural outcrossing and subsequently adventitious presence in adjacent fields throughout the Southwest.

Potential contributions of surface and ground water to nitrous oxide emissions from irrigated cotton production systems

The potential contribution of surface and ground water to overall nitrous oxide emissions from irrigated production systems has not yet been quantified. In this study we have used the International Panel on Climate Change (IPPC) emission factor five (EF5) to determine the indirect emissions from the irrigation water surface and from the ground water when it is pumped back onto the surface for irrigation. The additional land surface emission from the irrigation water source N was also calculated and termed the “indirect land surface emission”. The study primarily used data collected (2000–2010) from the Australian Cotton Research Institute, Narrabri, Australia to calculate indirect and direct farm emissions during the cotton production season from the research station. The average annual direct and indirect N2O-N emissions are 0.90kgN2O-Nha−1yr−1 direct; 0.30kgN2O-Nha−1yr−1 indirect emissions from the land surface;0.08kgN2O-Nha−1yr−1 from the head ditch; 0.03kgN2O-Nyr−1 from the tail drain. In total 26% of the emissions could be potentially emitted via the indirect pathway at the farm scale using river water for irrigation. If ground water with a concentration of (1.0NO3-NmgL−1) was used to irrigate the crop then in total ∼1.4% of the emissions would be emitted via the indirect pathway at the farm scale. But further refinement of the indirect emission factor and improved monitoring of temporal and spatial surface and ground water total N concentrations are required for mass balance calculations. Direct measurement of the N2O-N water surface emissions is required to validate the IPCC calculated values.

‘TAM 304’ Wheat, Adapted to the Adequate Rainfall or High-Input Irrigated Production System in the Southern Great Plains

‘TAM 304’ Wheat, Adapted to the Adequate Rainfall or High-Input Irrigated Production System in the Southern Great Plains

Causes of yield stagnation in irrigated lowland rice systems in the Senegal River Valley: Application of dichotomous decision tree analysis

In the Senegal River Valley (SRV), there was substantial yield gap between potential and actual yield obtained by farmers in irrigated rice production systems. Integrated crop management (ICM), covering almost all the agricultural practices from land preparation to harvest, was introduced to farmers for boosting yields since the early 2000s. A repeated farm survey was conducted over the period 2002–2010 to monitor farmers’ agricultural practices during the wet season in the Delta and Middle Valley of the SRV. The objectives of this study were to: (i) assess spatial and temporal variation in on-farm yields, and (ii) determine factors affecting variation in the yields through Classification and Regression Tree (CART) analysis. The data set consists of 829 farmer-year observations. While mean yields across nine years were 5.0 and 5.6t/ha in the Delta and Middle Valley, respectively, mean attainable yields (upper 10 percentile) were 7.2 and 8.6t/ha, respectively. Yield gap between attainable yield and mean yield was 2.2–3t/ha. There were no temporal trends in yield or yield gap in either zone. CART analysis identified six and eight yield determining factors. The primary factor was sowing time, and delayed sowing resulted in yield reduction by around 1t/ha in both zones. The major reasons behind delayed sowing were related to availability of credit, machinery, and irrigation water. The two other commonly identified factors were fertilizer management and bird control. We conclude that creating enabling environment through institutional arrangements for improving access to resources and machineries is essential for enhancing the adoption of ICM and breaking the yield stagnation. Development of alternative agricultural practices such as no tillage system is also needed to help farmers practice timely sowing.

Genetic variability of hull-less barley accessions based on molecular and quantitative data

The objective of this work was to characterize and quantify the genetic, molecular, and agronomic variability of hull-less barley genotypes, for the selection of parents and identification of genotypes adapted to the irrigated production system in the Brazilian Cerrado. Eighteen hull-less barley accessions were evaluated, and three covered barley accessions served as reference. The characterization was based on 157 RAPD molecular markers and ten agronomic traits. Genetic distance matrices were obtained based on molecular markers and quantitative traits. Graphic grouping and dispersion analyses were performed. Genetic, molecular, and agronomic variability was high among genotypes. Ethiopian accessions were genetically more similar, and the Brazilian ones were genetically more distant. For agronomic traits, two more consistent groupings were obtained, one with the most two-rowed materials, and the other with six-rowed materials. The more diverging materials were the two-rowed CI 13453, CN Cerrado 5, CN Cerrado 1, and CN Cerrado 2. The PI 356466, CN Cerrado 1, PI 370799, and CI 13453 genotypes show agronomic traits of interest and, as genetically different genotypes, they are indicated for crossing, in breeding programs.

Managing soil salinity with permanent bed planting in irrigated production systems in Central Asia

Land degradation due to water logging and its influence on secondary soil salinization processes pose a major threat to the sustainability of irrigated agriculture in the semi-arid production ecologies of Central Asia. In rainfed conditions, conservation agriculture (CA) practices, i.e., reduced tillage, residue retention and crop rotation, have proven to have substantial scope for arresting or reversing soil degradation. Previous research findings suggest that CA can be beneficially applied to irrigated croplands as well, but influences on salinization processes are insufficiently documented. This study investigates the effect of CA practices on soil salinity dynamics in irrigated production systems in the Khorezm region, Uzbekistan, Central Asia. The study was conducted under a cotton-wheat-maize rotation system, typical for the region, from 2007 to 2009 with two tillage methods (‘CA’ – permanent raised beds (PB); conventional tillage (CT)) combined with two residue levels (residue harvested (RH); residue retained (RR)). Compared to pre-experiment levels, salinity in the top 30cm soil increased significantly during cotton (May–October), while a negligible change occurred during wheat (October–June) and maize (July–September) season. In absence of crop residues, soil salinity on top of the beds increased compared to CT without crop residue retention. When retaining crop residues, the soil salinity under PB was reduced by 32% in the top 10cm and by 22% over the top 90cm soil profile compared to CT without crop residue retention. Thus, PB+RR seems a promising option to slow down on-going soil salinization in salt-affected agro-ecologies such as those in the irrigated arid lands of Central Asia.

Genetic improvement of triticale for irrigated systems in south-eastern Australia: a study of genotype and genotype×environment interactions

Research into winter cereal breeding in Australia has focused primarily on studying the effects of rainfed environments. These studies typically show large genotype × environment (GE) interactions, and the complexity of these interactions acts as an impediment to the efficient selection of improved varieties. Wheat has been studied extensively; however, there are no published studies on the GE interactions of triticale in Australia under irrigated production systems. We conducted trials on 101 triticale genotypes at two locations over 4 years under intensive irrigated management practices and measured the yield potential, GE interactions, heritability and estimated genetic gain of yield, lodging resistance and several other traits important for breeding triticale. We found that high yield potential exceeding 10 t ha–1 exists in the Australian germplasm tested and that, in these irrigated trials, genotype accounted for a high proportion of the variability in all measured traits. All genetic parameters such as heritability and estimated genetic gain were high compared with rainfed studies. Breeding of triticale with improved yield and lodging resistance for irrigated environments is achievable and can be pursued with confidence in breeding programs.

A Study on the Accumulation of Proline - An Osmoprotectant Amino Acid under Salt Stress in Some Native Rice Cultivars of North Kerala, India

Salinity is a major yield reducing factor in coastal as well as arid irrigated rice production systems. Salt induced abiotic stress is an acute problem, interrupting the metabolic processes of plants, resulting in reduced growth and productivity. Proline is an amino acid which increases in plants under abiotic stress. Salinity stress affects the metabolism of plants leading to severe crop damage and loss of productivity. Oxidative stress is one consequence of salinity that may be responsible for much of the damage. We inspected the immediate accumulation of proline in salinity induced stress in seven native rice (Oryza sativa L.) cultivars. Among the seven, five namely Orthadian, Chovvarian, Kuttusan, Kuthiru and Orkazhama were collected from a saline rice tract of the region and two namely Kunhutty and Veliyan from a non-saline rice tract of the region. The plants were subjected to different levels of salt stress ranging from 0 to 200 mM of NaCl and the concentration of proline in the leaf samples was inspected. Results showed that proline concentration increased in all the cultivars studied in relation to increase in salt stress and it was progressive along with increase in stress. This property was shown by all the cultivars irrespective of the fact whether they evolved in a saline habitat or a non-saline habitat. However, proline accumulation was higher in the cultivars collected from the saline tract when compared to the cultivars collected from the non-saline tract.

Efficient Water Use for Sustainable Irrigation Industry

The aim of this paper is to evaluate the economic efficiency of irrigated agricultural enterprises using a non-radial data envelopment analysis approach. While a number of studies have used radial measures based on data envelopment analysis to obtain efficiency scores for a given production technology, we calculate non-radial measures to understand the efficiency of using individual inputs employed in the production process. In particular, the measures of economic efficiency are decomposed into water use efficiency and managerial efficiency. This decomposition enables us to obtain an efficiency score for the use of water as an environmentally sensitive input in irrigated crop production systems. Treating water input in this way goes beyond traditional measurement of water use efficiency, as the calculated efficiency scores can be used as indicators of sustainability in terms of water withdrawals for irrigation purposes. The results show that the overall efficiency for the considered irrigated enterprises is quite high. This is in contrast to the findings on the water use efficiency scores, which are fairly low. This indicates that while Australian irrigated farms are comparatively more efficient in overall farm activity management, they are not very efficient in managing water resources. In turn, this threatens the sustainability of this industry. There is a substantial variation of water use efficiency scores across irrigated enterprises and across regions. Analysing these variations can provide important insights for current policy and for future efforts to improve water use efficiency that will lead towards more sustainable irrigation industry.

Integrated assessment of water–energy–GHG emissions tradeoffs in an irrigated lucerne production system in eastern Australia

Robust understanding of possible trade-offs and synergies between climate change, energy and water sector policies is critical to achieving economically viable and environmentally sound agricultural production systems in a low-carbon water-constrained economy, in which greenhouse gas (GHG) emissions are penalized and water savings rewarded. Accurate assessment of the potential costs/benefits of investment decisions can help to optimize the economic efficiency of agricultural production while minimizing environmental impacts. This paper presents a novel integrated framework, based on carbon and water accounting, which enables analysis of potential trade-offs between water savings, energy consumption, GHG emissions and economic costs/benefits associated with the adoption of new water efficient irrigation technologies. The framework was applied to an irrigated lucerne cropping system in eastern Australia and compares the costs/benefits of old roll-line sprinkler irrigation systems against new pressurized systems. Positive synergies were found with the adoption of the new technology, which saved both water and energy use, reduced total GHG emissions and resulted in net economic returns across a range of carbon prices. The results of this study provide support for an integrated evidence-based approach to policy development and strategic decision-making and for the prioritization of investments on both economic and environmental grounds.

Identification of Shoot Traits Related to Drought Tolerance in Common Bean Seedlings

Drought is an important abiotic stress that limits common bean (Phaseolus vulgaris) productivity. The objective of this study was to determine shoot traits that are associated with drought tolerance in common bean seedlings. Ten common bean genotypes consisting mainly of cultivars and breeding lines from the Mesoamerican race of the Middle American gene pool were first evaluated in the greenhouse. Genotypes were grown in a shallow soil profile to limit root growth and assess shoot phenotypes under stress. Water stress was imposed by withholding watering for 24 days after planting. Traits evaluated included wilting, unifoliate senescence, stem greenness, and recovery from drought. Biomass and number of pods/plant produced after drought recovery were evaluated to quantify the effect of early drought stress on bean growth and reproduction. A second group of 94 common bean genotypes from the Bean Coordinated Agricultural Project (BeanCAP) were evaluated using the same protocol to determine the genetic variability for the same traits in a wider range of genotypes. In general, genotypes known to possess drought avoidance in the field conferred by deep rooting traits performed poorly in these conditions suggesting that the assay could be used to identify seedling shoot traits that contribute to drought tolerance. Genotypes from race Mesoamerica showed the greatest range in wilting. Genotypes that showed a slow rate of wilting maintained a green stem and had a higher recovery rate after watering. Importantly, these genotypes demonstrated a smaller reduction in biomass and pod number under stress compared with non-stress treatments. A few genotypes recovered completely despite expressing severe wilting, whereas the majority of genotypes with high wilting rates did not recover. Among the BeanCAP materials, genotypes bred in the rainfed midwestern United States showed overall better recovery than those bred under the irrigated production system used in the western United States. Because recovery from drought is a prerequisite to plant regrowth, biomass, and pod production after drought stress, factors that contribute to recovery were studied. Stem greenness was highly positively correlated to the recovery, whereas wilting was negatively correlated to the recovery. In a regression analysis, stem greenness and slow wilting were found to be important contributors to the variability of recovery. In addition, photosynthetic rate and stomatal conductance (gS) explained variation in wilting and stem greenness. These results suggest that wilting and stem greenness might be useful traits to screen for drought tolerance in seedlings of common bean.

MONTE CARLO SIMULATION MODEL OF ENERGY CONSUMPTION IN WHEAT PRODUCTION SYSTEMS UNDER EGYPTIAN CONDITIONS

The Monte Carlo simulation method was used in this study to examine uncertainty propagation in a modeled irrigated wheat production system in Egypt. After running the Monte Carlo Simulation for 10000 runs for each operation, the alternative with higher frequency in each operation was selected and the energy consumption was calculated. The result of the current study was new system in addition to the nineteen systems involved. The total energy consumption was10205.09MJ/fed. This system consisted of Chisel plow 1st pass+ Disc harrow+ Steel leveler + Wooden Ridger + Mounted seed drill + Surface irrigation + Manual fertilizer Broadcasting + Manual operated knapsack sprayer + Combine. Among the nineteen systems involved in the study, the highest energy consumption system was system thirteen which consumed14650.8 MJ /Fed. The system of minimum energy consumption within the 19 systems used in this study was S4 with 10109.174 MJ /fed. This system consisted of Mould board Plow+ Disc harrow+ Wooden leveller+ Wooden ridger+ Mounted seed drill + Surface irrigation+ Manual fertilizer broadcasting + Manual operated knapsack Sprayer +Self-propelled mower+ Trailer + Stationary threshing machine. It can be concluded from the results of this study that Monte Carlo simulation model is capable of selecting the minimum energy consumption wheat production system.

Generating global crop distribution maps: From census to grid

We describe a new crop allocation model that adds further methodological and data enhancements to the available crop downscaling modeling. The model comprises the estimates of crop area, yield and production for 20 major crops under four rainfed and irrigated production systems across a global 5arc minute grid. The new model builds on prior work by the authors (and published in this journal) in developing regional downscaled databases for Latin America and the Caribbean (LAC) and sub-Saharan Africa (SSA) and encompasses notions of comparative advantage and potential economic worth as factors influencing the geographic distribution of crop production. This is done through a downscaling approach that accounts for spatial variation in the biophysical conditions influencing the productivity of individual crops within the cropland extent, and that uses crop prices to weigh the gross revenue potential of alternate crops when considering how to prioritize the allocation of specific crops to individual grid cells. The proposed methodology also allows for the inclusion of partial, existing sources of evidence and feedback on local crop distribution patterns through the use of spatial allocation priors that are then subjected to an entropy-based optimization procedure that imposes a range of consistency and aggregation constraints. We compare the global datasets and summarize factors that give rise to systematic differences amongst them and how such differences might influence the fitness for purpose of each dataset. We conclude with some recommendations on priorities for further work in improving the reliability, utility and periodic repeatability of generating crop production distribution data.

Impacts of Public, Private, and RD Investments on Total Factor Productivity Growth in Tunisian Agriculture

The paper analyzes the patterns of productivity and economic growth in Tunisian agriculture during the period 1981–2007. A regression approach is used to test the hypotheses that government-funded research, development and extension (RD&E), private and investment, terms of trade, and share of irrigated area are significant determinants of total factor productivity (TFP) in the agricultural sector. Results indicate that agricultural output experienced moderate annual growth between 1981 and 2007. Over the whole period, land and capital were found to be the most important contributors to productivity, and labour and livestock the least significant. TFP contribution to agricultural output was important in the 1980s, less important in the 1990s, and became significant again between 2001 and 2007. The findings show that TFP growth was the result of investments in the agricultural sector, with the use of intensive irrigated production systems and the adoption of new production technologies. We found significant negative cross-price elasticities between labour and capital suggesting that agricultural policies in the form of subsidies for agricultural machinery could be introduced without negatively affecting the agricultural labour force. Finally, Tunisian government should strengthen its domestic agricultural research system through a variety of policy tools that include joint public-private partnerships.

Combining permanent beds and residue retention with nitrogen fertilization improves crop yields and water productivity in irrigated arid lands under cotton, wheat and maize

Intensive soil tillage and mismanagement of irrigation water and fertilizers are increasing production costs, reducing soil fertility and crop water productivity and threatening the sustainability of crop production systems in the irrigated arid lands of Uzbekistan, Central Asia. Conservation agriculture (CA) practices combined with optimum nitrogen (N) management can counterbalance some of these adverse effects. Most work has been done in rainfed areas so there is less information available for irrigated production systems. This study compared the effects of tillage, crop residue management and N rates on yield and water productivity for irrigated cotton, winter wheat and maize grown in a two-year rotational sequence in Uzbekistan under CA practices vs. current conventional farmer practices. Permanently raised beds (PB) and conventional tillage (CT) were compared under two crop residue levels (retained residue – RR and removed residue – RH), and three N levels (zero, medium and high, with actual rates depending on the crops) on a sandy loam to loam soil. Raw cotton yield, yield components and water productivity were not affected by tillage methods. However, the following crops, wheat and maize, produced 12 and 42% higher grain yields, respectively, under PB than under CT. Under PB, water productivity increased in wheat by 27% and in maize by 84%, while 11% less water was applied during wheat and 23% during maize production, compared to CT. All three crops showed a considerable increment in yield and water productivity when N fertilizer levels were increased from zero to medium N application, and a relatively much lower increment when the N rate was doubled from medium to high N, for both tillage methods. In maize, the response to applied N was more pronounced with PB than with CT. Irrespective of tillage method, RR increased the grain yield of wheat by 5% compared to RH. In maize, RR in PB increased grain yields by 15% compared to RH. RR had no effect for CT. The positive effect of PB and RR on yield and water productivity of wheat and maize and the lack of negative effects on cotton yield reflect that PB with RR and proper N application may be viable alternatives to the present, unsustainable conventional agriculture practices in these irrigated arid lands, assuming the patterns are confirmed in the long-run.

Evaluation of the Precision Agricultural Landscape Modeling System (PALMS) in the Semiarid Texas Southern High Plains

Accurate models to simulate the soil water balance in semiarid cropping systems are needed to evaluate management practices for soil and water conservation in both irrigated and dryland production systems. The objective of this study was to evaluate the application of the Precision Agricultural Landscape Modeling System (PALMS) model to simulate soil water content throughout the growing season for several years and for three major soil series of the semiarid Texas Southern High Plains (SHP). Accuracy of the model was evaluated by comparing measured and calculated values of soil water content and using root mean squared difference (RMSD), squared bias (SB), squared difference between standard deviations (SDSD), and lack of correlation weighted by the standard deviation (LCS). Different versions of the model were obtained by modifying soil hydraulic properties, including saturated hydraulic conductivity (Ks) and residual (θr) and saturated (θs) soil volumetric water content, which were calculated using Rosetta pedotransfer functions. These modifications were combined with updated routines of the soil water solver in PALMS to account for rapid infiltration into dry soils that often occur in the SHP. Field studies were conducted across a wide range of soil and water conditions in the SHP. Soil water content was measured by neutron attenuation and gravimetrically throughout the growing seasons at each location to compare absolute values and the spatial distribution of soil water with PALMS calculated values. Use of Rosetta calculated soil hydraulic properties improved PALMS soil water calculation from 1% - 13% of measured soil volumetric water content (θv) depending on soil type. Large-scale models such as PALMS have the potential to more realistically represent management effects on soil water availability in agricultural fields. Improvements in PALMS soil water calculations indicated that the model may be useful to assess long-term implications of management practices designed to conserve irrigation water and maximize the profitability of dryland and irrigated cropping systems in the SHP.

Challenges in the nutrition and management of herbivores in the temperate zone

The expected higher global demand for animal proteins and the competition for starch and sugars between food, fuel and feed seem to favour herbivores that convert solar energy captured in fibrous plants into animal products. However, the required higher production level of herbivores questions the sustainability of this conversion. An increase in herbivore production can be achieved by increasing the number of animals associated with the increasing demand of plant biomass or by improving the efficiency with which plant biomass is converted into meat and milk. The potential to increase food production by cattle, the main food-producing herbivore in the temperate zones outside China, was considered in three production systems: grassland-based, mixed rain-fed and mixed irrigated systems. The potential to increase plant biomass production in grassland-based systems seems limited, unless fertiliser is imported in large quantities and crop production is increased, sacrificing valuable, high-quality grasslands, which often conflicts with sustainable production methods. Also, in mixed systems with high inputs of fertiliser or water, improvements in plant biomass production seem marginal and the main challenges for these systems are in breeding high-quality plant biomass at lower levels of fertiliser and the use of new co-products from food processing and bio-based economies. Consequently, the main challenge in herbivore nutrition management is to improve the efficiency of plant biomass utilisation. Stocking rate management along with seasonal variation in the grazing capacity of grasslands and moderate use of fertiliser may increase meat production in grassland-based systems by 400%. Improving plant biomass utilisation in the more industrialised mixed rain-fed systems seems possible by better feed storage technologies and for dairy cattle by improving animal health and lifetime production level. Managing the transition period seems crucial to achieve more sustainable mixed rain-fed and mixed irrigated dairy production systems. Whether sustainable production methods will be implemented also depends on macro-economic conditions and awareness of regional and global environmental concerns.