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Red soil (Ultisol) with high clay content and low aggregation results in high soil mechanical resistance and often suppresses crop root growth and productivity. Bio-tillage can be an effective tillage method to reduce the high soil mechanical resistance. This study aims to investigate different bio-tillage plants' root effects on soil mechanical resistance through soil aggregates properties. The experiment designed 5 fall/winter cover crops (2 raps cultivars, lucerne, one-year vetiver (Vet₁Y) and six-year vetiver (Vet₆Y) as bio-tillage before summer maize and one control treatment. Plant root morphological and chemical traits, soil organic carbon (SOC), soil aggregate properties and soil mechanical resistance (measured and fitted values using model) were determined. The fibrous-rooted vetiver showed the largest root length density (RLD) (ranging from 2.71 to 4.82 cm cm.sup.-3), highest root diameter (RD) in deep soil depth, highest percentage of fine roots (0.2-0.5 mm), while lowest root lignin/cellulose ratio than tap-rooted lucerne and rapes. These root properties resulted in the highest improvement in the macroaggregate (> 5 mm and 5-2 mm) percentage for vetiver and especially for perennial Vet₆Y compared to other crops and control. Finally, fibrous-rooted vetiver contributed to the least soil mechanical resistance values followed by lucerne and two rapes compared to fallow. This was attributed to their positive root effect on improvement in macroaggregate and decrease in soil bulk density. Our finding suggested that fibrous-rooted vetiver can be selected as a bio-tillage plant to improve soil physical properties, especially to reduce high mechanical resistance in clayey red soil.

Purpose Red soil (Ultisol) with high clay content and low aggregation results in high soil mechanical resistance and often suppresses crop root growth and productivity. Bio-tillage can be an effective tillage method to reduce the high soil mechanical resistance. This study aims to investigate different bio-tillage plants' root effects on soil mechanical resistance through soil aggregates properties. Methods The experiment designed 5 fall/winter cover crops (2 raps cultivars, lucerne, one-year vetiver (Vet_1Y) and six-year vetiver (Vet_6Y) as bio-tillage before summer maize and one control treatment. Plant root morphological and chemical traits, soil organic carbon (SOC), soil aggregate properties and soil mechanical resistance (measured and fitted values using model) were determined. Results The fibrous-rooted vetiver showed the largest root length density (RLD) (ranging from 2.71 to 4.82 cm cm −3 ), highest root diameter (RD) in deep soil depth, highest percentage of fine roots (0.2–0.5 mm), while lowest root lignin/cellulose ratio than tap-rooted lucerne and rapes. These root properties resulted in the highest improvement in the macroaggregate (> 5 mm and 5–2 mm) percentage for vetiver and especially for perennial Vet_6Y compared to other crops and control. Finally, fibrous-rooted vetiver contributed to the least soil mechanical resistance values followed by lucerne and two rapes compared to fallow. This was attributed to their positive root effect on improvement in macroaggregate and decrease in soil bulk density. Conclusion Our finding suggested that fibrous-rooted vetiver can be selected as a bio-tillage plant to improve soil physical properties, especially to reduce high mechanical resistance in clayey red soil.

Maize (Zea mays L.) is a major staple food and cash crop in sub-Saharan Africa (SSA). However, its production and productivity are severely constrained by drought. A total of 120 single-cross hybrids and an open-pollinated control variety were evaluated for 2 years at two locations under managed drought and rain-fed conditions in Nigeria. The objective of the present study was to assess their performance, classify them into distinct heterotic groups and identify promising hybrids for commercialization in the West and Central Africa sub-region. General combining ability and specific combining ability mean squares were highly significant for grain yield and other traits under the research environments. However, there was a preponderance of additive gene action over non-additive. Only six out of 39 inbreds were classified into distinct heterotic groups by the testers. The highest-yielding drought-tolerant hybrid, TZEEI 102 × TZEEI 95, out-yielded the open-pollinated control variety by 43·70%. The average yield reduction under drought was 54·90% of the yield under rain-fed conditions. The hybrids TZEEI 81 × TZEE1 79, TZEEI 100 × TZEEI 63 and TZEEI 64 × TZEEI 79 were the highest-yielding and most stable across environments. These outstanding drought-tolerant hybrids, which are also resistant to Striga, have the potential to contribute to food security and increased incomes in SSA and should be tested extensively on-farm and commercialized.

This is a completely revised edition of the previously titled Solute Movement in the Soil-Root System. It describes in detail how plant nutrients and other solutes move in the soil in response to plant uptake, and it provides a basis for understanding processes in the root zone so that they can be modeled realistically in order to predict the effects of variations in natural conditions or our own practices.

An understanding of the mineral nutrition of plants is of fundamental importance in both basic and applied plant sciences. The Third Edition of this book retains the aim of the first in presenting the principles of mineral nutrition in the light of current advances. This volume retains the structure of the first edition, being divided into two parts: Nutritional Physiology and Soil-Plant Relationships. In Part I, more emphasis has been placed on root-shoot interactions, stress physiology, water relations, and functions of micronutrients. In view of the worldwide increasing interest in plant-soil interactions, Part II has been considerably altered and extended, particularly on the effects of external and interal factors on root growth and chapter 15 on the root-soil interface. The third edition will be invaluable to both advanced students and researchers.

Deep learning (DL) constitutes a modern technique for image processing, with large potential. Having been successfully applied in various areas, it has recently also entered the domain of agriculture. In the current paper, a survey was conducted of research efforts that employ convolutional neural networks (CNN), which constitute a specific class of DL, applied to various agricultural and food production challenges. The paper examines agricultural problems under study, models employed, sources of data used and the overall precision achieved according to the performance metrics used by the authors. Convolutional neural networks are compared with other existing techniques, and the advantages and disadvantages of using CNN in agriculture are listed. Moreover, the future potential of this technique is discussed, together with the authors’ personal experiences after employing CNN to approximate a problem of identifying missing vegetation from a sugar cane plantation in Costa Rica. The overall findings indicate that CNN constitutes a promising technique with high performance in terms of precision and classification accuracy, outperforming existing commonly used image-processing techniques. However, the success of each CNN model is highly dependent on the quality of the data set used.

Aims The theory of ecological stoichiometry mostly builds on studies of natural terrestrial ecosystems, whereas only limited stoichiometry information is available in response to agronomic practices. Methods We designed a greenhouse experiment in order to disentangle the specific role of cover crop identity and soil characteristic in affecting nutrient stoichiometry of a plant-microbe-soil system. Results Nutrient ratios of cover crop biomass were species-specific and the growth rate explained, for most species considered, the stoichiometric differences in response to soil type. In contrast, the nutrient stoichiometry of soil microbes was more homeostatic and did not respond to either cover crop identity or soil type. Compared to bare soil, the presence of cover crop enhanced microbial phosphorus immobilization in the clay-rich soil, whereas it promoted microbial carbon biomass and microbial nitrogen immobilization in the sandy-rich soil. A greater microbial cumulative respiration in clay soils, where a higher microbial biomass C at the beginning of the incubation was observed, suggested a major role of soil type, compared to cover crop identity, in affecting microbial metabolism. Conclusions By understanding the stoichiometric constraints in the plant-microbe-soil system, our findings can help to implement agro-ecological practices by selecting appropriate cover crop species in relation to soil type in order, for example, to avoid nutrient limitation due to microbial nutrient immobilization.

Owing to its contribution to the maintenance of carbon stocks, soil nitrogen and nutrient cycling for subsequent crops, the integrated systems become increasingly important for agricultural conservation. Thus, the objective of this study was to evaluate the biomass production of and total nutrient in Brachiaria spp. and Panicum maximum forage grasses used as mulch and soybean yields in an integrated crop–livestock system and second-crop maize succession system. The treatments consisted of the following cropping systems: Xaraes palisadegrass intercropped with soybean, Congo grass intercropped with soybean, Mombaça guinea grass intercropped with soybean, Tamani guinea grass intercropped with soybean and a soybean/maize succession system. The forage grasses were established during the soybean R6–R7 stage. Compared with Congo grass, Xaraes palisadegrass, Mombaça guinea grass and Tamani guinea grass produced more biomass and equivalent amounts of fertilizer returned to the soil and resulted in greater nutrient cycling, indicating the benefits of these grasses for use as mulch in integrated production systems. Maize had a greater C/N ratio, but the forage grasses also exhibited high potential by protecting the soil until the end of the soybean development cycle. The use of an integrated crop–livestock system combined with a forage cropping system provided greater soil nutrient cycling than the maize cropping system did, which resulted in increased soybean yields, thus contributing to the sustainability of agricultural systems.

Crop production is at the core of a ‘perfect storm’ encompassing the grand challenges of achieving food and nutrition security for all, in the face of climate change, while avoiding further conversion of natural habitats for agriculture and loss of biodiversity. Here, we explore current trends in crop modelling related to these grand challenges by reflecting on research presented at the Second International Crop Modelling Symposium (iCropM2020). A keyword search in the book of abstracts of the symposium revealed a strong focus on ‘climate change’, ‘adaptation’ and ‘impact assessment’ and much less on ‘food security’ or ‘policy’. Most research focused on field-level investigations and far fewer on farm(ing) systems levels – the levels at which management decisions are made by farmers. Experimentation is key to development and testing of crop models, yet the term ‘simulation’ outweighed by far the terms ‘experiments’ and ‘trials’, and few contributions dealt with model improvement. Cereals are intensively researched, whereas roots, tubers and tropical perennials are under-researched. Little attention is paid to nutrient limitations apart from nitrogen or to pests and diseases. The aforementioned aspects represent opportunities for future research where crop models can help in devising hypotheses and driving new experimentation. We must also ensure that crop models are fit for their intended purposes, especially if they are to provide advice to policymakers. The latter, together with cross-scale and interdisciplinary efforts with direct engagement of stakeholders are needed to address the grand challenges faced by food and agricultural systems in the next century.

Biochar, a late-model environmental functional material, has been widely applied in environmental remediation, agricultural production, and energy utilization due to its excellent characteristics such as porosity and high specific surface area. In recent years, many studies on the effects of biochar on agricultural soil and crop quality have been performed. The application of biochar can influence soil microbial status directly or indirectly by changing the physicochemical properties of soil. Apart from increasing soil pH, biochar can also increase soil organic matter and nutrient elements, which ultimately affect crop yield and quality. This review summarizes and overviews the recent research advances on the influence of biochar application on soil microbial community diversity, microbial ecological functions, soil enzymes and their functional genes, and on crop quality and yield from the perspective of soil microorganisms. This review provides guidance and references for further research into biochar applications.