Plant Biomass Productivity Under Abiotic Stresses in SAT Agriculture

The semi-arid tropics (SAT) include parts of 48 countries in the developing world: in most of India, locations in south east Asia, a swathe across sub-Saharan Africa, much of southern and eastern Africa, and a few locations in Latin America (Fig 1). Semi-arid tropical regions are characterized by unpredictable weather, long dry seasons, inconsistent rainfall, and soils that are poor in nutrients. Sorghum, millet, cowpea, chickpea, pigeonpea and groundnut are the vital crops that feed the poor people living in the SAT. Environmental stresses represent the most limiting factors for agricultural productivity. Apart from biotic stresses caused by plant pathogens, there are a number of abiotic stresses such as extremes temperatures, drought, salinity and radiation which all have detrimental effects on plant growth and yield, especially when several occur together (Mittler 2006)

Coupling DSSAT and HYDRUS-1D for simulations of soil water dynamics in the soil-plant-atmosphere system

Abstract Accurate estimation of the soil water balance of the soil-plant-atmosphere system is key to determining the availability of water resources and their optimal management. Evapotranspiration and leaching are the main sinks of water from the system affecting soil water status and hence crop yield. The accuracy of soil water content and evapotranspiration simulations affects crop yield simulations as well. DSSAT is a suite of field-scale, process-based crop models to simulate crop growth and development. A “tipping bucket” water balance approach is currently used in DSSAT for soil hydrologic and water redistribution processes. By comparison, HYDRUS-1D is a hydrological model to simulate water flow in soils using numerical solutions of the Richards equation, but its approach to crop-related process modeling is rather limited. Both DSSAT and HYDRUS-1D have been widely used and tested in their separate areas of use. The objectives of our study were: (1) to couple HYDRUS-1D with DSSAT to simulate soil water dynamics, crop growth and yield, (2) to evaluate the coupled model using field experimental datasets distributed with DSSAT for different environments, and (3) to compare HYDRUS-1D simulations with those of the tipping bucket approach using the same datasets. Modularity in the software design of both DSSAT and HYDRUS-1D made it easy to couple the two models. The pairing provided the DSSAT interface an ability to use both the tipping bucket and HYDRUS-1D simulation approaches. The two approaches were evaluated in terms of their ability to estimate the soil water balance, especially soil water contents and evapotranspiration rates. Values of the d index for volumetric water contents were 0.9 and 0.8 for the original and coupled models, respectively. Comparisons of simulations for the pod mass for four soybean and four peanut treatments showed relatively high d index values for both models (0.94–0.99)

Frontier Research on the Processing Quality of Cereal and Oil Food

As everyone knows, cereal and oil are still the main part of our diet and provide essential nutrients and energy every day. With the progress of food processing technology, the quality of cereal and oil food is also improved significantly. Behind this, major nutrients of grain and oil, including protein, carbohydrate, lipid, and functional components, have experienced a variety of physical, chemical, and biological reactions during food processing. Moreover, research in this field also covers the multi-scale structural changes of characteristic components, such as component interaction and formation of key domains, which is essential for the quality enhancement of cereal and oil food. Based on the increasing consumer demand for nourishing, healthy, and delicious cereal and oil food, it might be interesting to report the latest research on the application of novel technology in food processing, multi-scale structural changes of characteristic components in food processing, structure-activity mechanism of food functional components. This book aimed to provide useful reference and guidance for the processing and utilization of cereal and oil food so as to provide technical support for the healthy development of cereal a oil food processing industry wordwide

Agricultural Research Service research highlights in remote sensing for calendar year 1981

Selected examples of research accomplishments related to remote sensing are compiled. A brief statement is given to highlight the significant results of each research project. A list of 1981 publication and location contacts is given also. The projects cover emission and reflectance analysis, identification of crop and soil parameters, and the utilization of remote sensing data

INTENSIVE CASSAVA PRODUCTION: CROP FOR THE FUTURE

Cassava (Manihot esculenta Crantz) is a major staple food in sub-Saharan Africa (SSA), providing an importantsource of calories and options for food security for the increasing population. It is a warm season crop, withunique and useful environmental physiological traits, including the ability to produce in marginal soils, and yieldeven under conditions of extreme drought. Analysis of literature was carried out to understand the crop's yieldpotential, since there is wider recognition of cassava as a crop of choice for climate change adaptation strategiesand to increase food security in the near future, particularly in (SSA). Literature study includes: cassavaphysiology, yield potential, crop characteristics for potential yield, understanding the nutrient dynamics, andmodelling of cassava growth and yield. The study indicates that cassava has a high yield potential of over 90 tonsha-1 of fresh storage roots (32 t DM ha-1) in a year, and high nutrient use efficiency. This suggests that some cropparameters used currently in cassava growth simulation models require modification. Good estimates of potentialyields provide important benchmarks for realistic yield targets and understanding of yield gaps with localrelevance. The increasing demand for cassava offers farmers the opportunity to intensify production, earn higherincomes, and boost their food supply. Therefore, the use of inorganic fertilizers, following 4R nutrientstewardship (right amount, right time, right place and right source), is inevitable to sustainably improveproductivity in the future. Also, understanding the dynamics of nutrient requirements and the impact of uptakelimitations of cassava during the growth cycle enables prediction of cassava yields under nutrient limitedconditions, and may provide insight in best management practices to improve nutrient use efficiency. Knowledgeof nutrient (N, P and K) demand and uptake patterns under deficient conditions in cassava can be used to developa simulation model. After testing the model, it may be used for many purposes, including: generation of cropresponses for series of years in order to characterize cassava growth and nutrient uptake, provide locationspecificfertilizer recommendation, and extrapolate from the studied area to other areas where less detailedinformation is available. Increasing cassava yield requires an in-depth understanding of limitations in growth.Therefore, researchers need to adopt a wholesome approach in developing useful technologies for goodagronomic practices that will support sustainable cassava production and bridge the large yield gap

Designing, modeling, and evaluation of improved cropping strategies and multi-level interactions in intercropping systems in the North China Plain

Adjusting cropping systems in order to increase their efficiency is a global issue. High yield and sustainability are the catchphrases of production in the 21st century, and agricultural production has to solve the balancing act between ecology and economy. Therefore, the requests for farmers, consultants and researchers are rising, and production modes are changing. Nevertheless, solutions have to be detected spatially explicit and locally adapted and accepted in order to be implemented successfully. Taking the North China Plain as an example, the productivity of arable land needs to be further increased by applying strategies to reduce or avoid negative environmental effects. Further yield increases are not possible by increasing input factors like N-fertilizer or irrigation water as N-fertilizer rates are extremely high and irrigation water is limited. However, yield increases might be possible by developing improved cropping strategies operated by cropping designs. Taking modeling and simulation tools into account back up the acceleration of research attainments and the understanding of cropping systems. The present thesis embraces the designing and modeling of such a potential cropping system, to wit strip intercropping. Thus, the main goals of the study were to analyze, design, evaluate, and in the end model intercropping. Intercropping systems are complex systems which strongly need to be designed and evaluated carefully in order to fulfill the premises of ecological and economical efficiency as well as sustainability. Multi-level interactions have to be weighted and taken into regard for evaluating datasets applicative for modeling and simulating intercropping. The main results of the study indicated, that traditional cropping systems like intercropping are widespread in China, where approximately one third of arable land is under intercropping. Reviewing cereal intercropping systems in China, the four agro-ecological regions ?Northeast and North?, the ?Northwest?, the ?Yellow-Huai River Valley? and the ?Southwest? could be classified, distinguished and described. Intercropping offers a great variation of species combination, benefits as well as challenges for cropping systems design and farmers. Carefully balanced between facilitation and competition, intercropping bears the potential of increased yield and yield stability, income security, resource use efficiency and biodiversity. Intercropping gives evidence about traditional cropping systems with the potential for future production systems under the paradigm of sustainability. Further, results from conducted field experiments indicated that border effects are the key component of intercropping performance. Nevertheless, analyzing strip intercropping statistically has peculiarities as they lack in randomization because the cropping system imposes alternating strips. Thus, spatial variability and its effect on yield were regarded differently within a geo-statistical analysis. In addition to the geo-statistical analysis, the crop growth modeling approach paid tribute to monocropping effects as well as to field border effects occurring in strip intercropping systems. Further on a model-based approach was tested to quantify multi-level interactions with special regard to changing microclimatic conditions and to optimize intercropping systems from an agronomical point of view. In comparison to other interspecific competition modeling approaches, a shading algorithm was evaluated and implemented into the process-oriented crop growth model DSSAT in order to simulate competition for solar radiation. More common in modeling mixed intercropping, a modified Beer?s law subroutine has been used instead, e.g. in APSIM. APSIM and DSSAT were compared by modeling the conducted field trials. As a result, the Beer?s law approach was not capable to model strip intercropping. In contrast, the modeling with a changed DSSAT model showed that applying a simple shading algorithm that estimated the proportion of shading in comparison to the monocropping situation and in dependency from neighboring plant height seems to be a promising approach. The results indicated that competition for solar radiation in those systems is a driving force for crop productivity but neither the most dominant nor the one and only. Resource distribution and allocation in space and time seems to be more important than the total amount of resources. Those effects have to be taken into account when simulating interspecific competition.Definiert als der Anbau von zwei oder mehr Feldfrüchten auf der gleichen Fläche und innerhalb der gleichen oder einer sich überlappenden Vegetationsperiode, bietet Intercropping eine große Bandbreite an Kombinationsmöglichkeiten von Feldfrüchten, verbunden mit vorteilhaften und nachhaltigen Effekten für die jeweiligen Kulturarten. Intercropping ist aber gleichzeitig eine Herausforderung für jeden Landwirt und stellt hohe Ansprüche an die Gestaltung des jeweiligen Produktions- oder Anbausystems. Intercropping ist in China weit verbreitet. Schätzungen zufolge wird Intercropping auf rund einem Drittel der gesamten Anbaufläche praktiziert. Intercropping gilt als ein Anbausystem, welches bei geringerem Betriebsmitteleinsatz höhere Erträge oder Gewinne erzielt, verglichen mit den ausgedehnten Monocropping Systemen moderner Agrar-Industriebetriebe. Damit belegt Intercropping, dass in traditionellen Anbausystemen ein Potential für zukünftige und nachhaltige Produktionssysteme schlummert. Um diesen Paradigmen und um politischen, sozialen und ökonomischen Prämissen gerecht zu werden, muss die Agrarforschung Lösungen und Strategien für angepasste Produktionssysteme bereitstellen ? und das in immer kürzeren Zeitspannen. Der Einsatz von computergestützten Pflanzenwachstumsmodellen, mit deren Hilfe komplexe Anbausysteme regional und überregional, sowie über längere Zeiträume hinweg simuliert und analysierte werden können, hat sich dabei als wertvoll erwiesen. Wie Intercropping Systeme gestaltet werden müssen und welche Probleme dabei auftauchen, welche Datengrundlage für eine Modellierung benötigt wird und welche systemimmanenten Interaktionen berücksichtig werden müssen, sind Gegenstand der vorliegenden Dissertation. Allerdings gestaltet sich die statistische Auswertung von speziell Strip Intercropping als schwierig, da Intercropping-Versuche aufgrund der zwangsläufig streifenförmigen Anordnung nicht randomisiert werden können. Intercropping bedarf also einer räumlichen Betrachtungsweise, um ertragsrelevante Effekte adäquat abzuschätzen und statistisch abzusichern. Deshalb wurden die Versuche geostatistisch ausgewertet und mehrere räumliche Modelle evaluiert und getestet, um die Modellgüte zu verbessern. Nicht nur die statistische Auswertung von Intercropping ist diffizil, auch die Datengrundlage von Intercropping in China ist lückenhaft. Im Vergleich zu anderen Ländern wie beispielsweise Indien oder Teilen Afrikas, wo Intercropping gängige Praxis ist, scheint die Dokumentation und Erforschung von Intercropping Systemen in China Nachholbedarf zu haben. In einer Literaturstudie wurde deshalb ein erster Versuch unternommen, China in agro-klimatische Regionen hinsichtlich ihres Potentials und ihrer Verbreitung von Getreide betonten Intercropping Systemen einzuteilen. In einer zweiten Literaturstudie wurde dargestellt, welche Modelle für Intercropping bereits evaluiert, kalibriert und validiert wurden. Exemplarisch für ein prozess-orientiertes Pflanzenwachstumsmodell, welches multiple Anbausysteme und deren Konkurrenz um Sonnenlicht mithilfe des Beer-Lambert?schen Gesetzes simuliert, wurde APSIM gewählt. Dieser in der Forschung recht gängige Ansatz wurde mit dem in der vorliegenden Dissertation evaluierten, getesteten und in DSSAT implementierten Beschattungs-Algorithmus verglichen. Mit dem DSSAT Modell war es bislang nicht möglich, Intercropping zu simulieren. Es zeigte sich, dass es mit einem modifizierten Beer-Lambert?schen Gesetz nicht möglich war, Strip Intercropping adäquat zu simulieren. Unter der Voraussetzung, dass es im Strip Intercropping einen Gewinner und einen Verlierer gibt, das heißt, dass eine Kulturart mehr Sonnenlicht erhält als im Monocropping und eine andere dafür weniger, ist der Beer-Lambert?sche Ansatz viel versprechend und verwendbar. Die Kompensationsfähigkeit einer Fruchtart kann jedoch nicht simuliert werden, ebenso keine Ertragssteigerung der im System dominanten Fruchtart. Im Gegensatz dazu zeigte sich, dass der Beschattungs-Algorithmus, der in DSSAT integriert wurde, beide Systeme ? Intercropping und Monocropping ? simulieren konnte. Allerdings wurde in diesem Ansatz zusätzlich berücksichtig und getestet, dass Konkurrenz um solare Einstrahlung nicht die einzig bestimmende ist. Der Beschattungs-Algorithmus konnte zwar einen Teil des Ertragszuwachses im Intercropping erklären beziehungsweise simulieren, allerdings erst unter Berücksichtigung mikroklimatischer Effekte. Der Allokation von Pflanzenwachstumsfaktoren in Raum und Zeit kommt in Intercropping Systemen eine größere Rolle zu als deren absolute Höhe oder Menge. Solche Effekte müssen berücksichtig werden, um die Modellierung von Strip Intercropping weiterhin zu verbessern und Strip Intercropping Systeme zu optimieren

Controlled Ecological Life Support System. First Principal Investigators Meeting

Control problems in autonomous life support systems, CELSS candidate species, maximum grain yield, plant growth, waste management, air pollution, and mineral separation are discussed

USING MANUAL DEFOLIATION TO SIMULATE SOYBEAN RUST: EFFECT ON GROWTH AND YIELD FORMATION

Field experiments were conducted in Kentucky and Louisiana in 2008 and 2009 (split-plot in a randomized complete block design with four replications) to investigate it is possible to simulate with manual defoliation the effect of soybean rust (SBR) (Phakopsora pachyrhizi Syd. and P. Syd) injury on a healthy soybean [Glycine max, (L.) Merr.] canopy, understand how defoliation affects the growth dynamics and canopy light interception, and if defoliation affectsleaf senescence and nitrogen remobilization during the seed-filling period. Two manual defoliation treatments based on changes in effective leaf area index (ELAI) (calculated as the reduction in leaf area equivalent to SBR-induced premature leaf abscission, loss in green leaf area, and reduction in photosynthetic capacity of diseased leaves) in infected canopies in Brazil were used to simulate SBR infection at growth stage R2 (full flowering) and R5 (beginning of seed-fill). Both defoliation treatments reduced yield in all experiments and the reduction was larger for the treatments at growth stage R2. The yield losses were equivalent to that observed in infected soybean canopies in Brazil. This suggests that a system of manual defoliation to simulate changes in effective leaf area duration shows promise as a tool to simulate the impact of SBR on soybean yield. The radiation use efficiency and crop growth rate from growth stage R2 to R5 were not influenced by defoliation. Defoliation started at growth stage R2 reduced seed number per unit area, while defoliation started at growth stage R5 reduced seed size due to shortening the seed-fill duration and a lower seed growth rate. There is no evidence that manual defoliation affected leaf senescence or nitrogen redistribution to the seed. This study found that the reduction of light interception by SBR was the main reason for the reductions in soybean growth and yield