Towards synthesis for nitrogen fertilisation using a decision support system

Nitrogen (N) fertilisation in crops can be made more efficient by moving from uniform application to meeting variable crop requirements within fields. Within field variable rate N fertilisation of winter wheat (Triticum aestivum L.) is practically feasible using information from web-based decision support systems (DSS). Data from different source platforms, such as satellite, unmanned aerial vehicle (UAV) or weather stations can be used for fertilisation planning. System output offers information that can be used  to instruct variable rate fertilizer spreaders to increase or decrease fertilizer application rate on-the-go. In Sweden, satellite-based variable rate N fertilisation was available for winter wheat via a DSS, however, the existing module could be improved in different ways. In this thesis work, a new N-uptake model was estimated and opportunities using UAV-based modelling of grain quality were tested. Transferability of UAV-based models to a satellite data scale improved understanding of the complexity of data transfer from UAV-scale to a satellite scale for use in a DSS. Furthermore, it was possible to model crop phenology from historical data, which can improve accuracy of current implemented models, by taking timing of field operations in to account

An Evaluation of Unmanned Aircraft Systems\u27 Ability to Assess Stripe Rust in Large Wheat Breeding Nursies

Stripe Rust (Puccinia striiformis f. sp. tritici) is a foliar disease that significantly impacts global wheat production, and resistant cultivars provide the most efficient method of control. High-throughput phenotyping using unmanned aircraft systems (UAS) offers a potentially more efficient method for field-based phenotyping compared to visual assessment. Here we tested the ability of remote sensing to predict stripe rust severity in a diverse population of 594 soft red winter wheat lines, planted in single-rows, and evaluated them by visually rating stripe rust intensity and remotely using the dark green color index (DGCI), normalized difference vegetation index (NDVI) and blue NDVI. Significant relationships (p In a second study, the effect of plot size (single-row, two-row and four-row) on relationship between visual and remote sensing data (DGCI and NDVI) was explored. We evaluated a panel of 13 genotypes preselected to range from 0 to 100% severity, planted in three plot sizes across two measurement days. Significant (

Understanding the interactions between biomass, grain yield and grain protein content in low and high protein wheat cultivars

Grain protein content (GPC) is a key quality attribute and an important marketing trait in wheat. However, a negative relationship between grain yield and GPC has limited selection for increased GPC, since grain yield is the primary driver of breeding programs. GPC is strongly influenced by nitrogen (N) fertilizer application, but the N-use efficiency (NUE) of high and low GPC genotypes appears to be genetically determined. The aim of this PhD thesis was to investigate the grain yield-GPC relationship under controlled and field conditions, and to suggest selection targets and traits for improving NUE in wheat. Firstly, the N responsiveness of six wheat genotypes that varied in GPC were examined under controlled condition. This experiment was designed around non-destructive estimation of biomass using a high-throughput image-based phenotyping system. In parallel, field trials were conducted to allow the comparison of results obtained from the controlled condition study using the six selected genotypes. Estimating the rate of biomass accumulation in breeding plots in the field is difficult. Therefore, the growth rate of biomass related traits such as height and ground cover were assessed in these trials. To examine the grain yield- GPC relationship under multi-environmental conditions, the grain yield and GPC data of over 200 wheat genotypes obtained from the Australian National Variety Trials (NVT) across the Australian wheat-belt were analysed. Results of the controlled environment experiment showed that high GPC genotypes appeared to demand more N to grow their biomass. In both controlled and field environments, high GPC genotypes slowed down the rate of biomass growth under low N supply. Under low yielding conditions, high GPC genotypes seemed able to manage grain N reserves by compromising biomass production. These results indicated the importance of biomass growth analysis to show the differences in the N responsiveness of high and low GPC genotypes. Differences between high and low GPC genotypes in responding to low N could be due to their history of selection. N effect is strongly associated with the amount of available water in the soil. Controlled and multi-environmental studies showed that the slope of the relationship between grain yield and GPC is steeper in low compared to high yielding environments. Therefore, high GPC genotypes bred under stress conditions sacrifice yield in favour of GPC, possibly to enhance the survival chance by producing fewer grains with sufficient nutrient levels. Conversely, low GPC genotypes bred in high yielding environment are less conservative compared to high GPC genotypes in using N for yield production. The outcomes of this PhD project highlight the importance of considering environmental factors for improving NUE in breeding programs. It recommends that wheat breeders focus on selecting in low yielding environments for high yield and high GPC genotypes.Thesis (Ph.D.) -- University of Adelaide, School of Agriculture, Food and Wine, 202

Drones and Geographical Information Technologies in Agroecology and Organic Farming

Although organic farming and agroecology are normally not associated with the use of new technologies, it’s rapid growth, new technologies are being adopted to mitigate environmental impacts of intensive production implemented with external material and energy inputs. GPS, satellite images, GIS, drones, help conventional farming in precision supply of water, pesticides, fertilizers. Prescription maps define the right place and moment for interventions of machinery fleets. Yield goal remains the key objective, integrating a more efficient use or resources toward an economic-environmental sustainability. Technological smart farming allows extractive agriculture entering the sustainability era. Societies that practice agroecology through the development of human-environmental co-evolutionary systems represent a solid model of sustainability. These systems are characterized by high-quality agroecosystems and landscapes, social inclusion, and viable economies. This book explores the challenges posed by the new geographic information technologies in agroecology and organic farming. It discusses the differences among technology-laden conventional farming systems and the role of technologies in strengthening the potential of agroecology. The first part reviews the new tools offered by geographic information technologies to farmers and people. The second part provides case studies of most promising application of technologies in organic farming and agroecology: the diffusion of hyperspectral imagery, the role of positioning systems, the integration of drones with satellite imagery. The third part of the book, explores the role of agroecology using a multiscale approach from the farm to the landscape level. This section explores the potential of Geodesign in promoting alliances between farmers and people, and strengthening food networks, whether through proximity urban farming or asserting land rights in remote areas in the spirit of agroecological transition. The Open Access version of this book, available at www.taylorfrancis.com, has been made available under a Creative Commons 4.0 license

Predicting Nutrient Content, Plant Health, and Site Suitability: A Case Study of Eragrostis tef

Advancements in agricultural and geographic principals have led to worldwide food and agricultural globalization. Because agricultural production continues to further in global interconnectedness, confirmed precision agriculture (PA) methods are required to monitor crops in-field. PA utilizes a remote sensing method referred to as imaging spectroscopy (IS). IS is often performed using a field spectroradiometer that identifies reflectance values. The reflectance values obtained have been utilized in agricultural studies to correlate spectral reflectance to biochemical and biophysical properties. However, while there is a large body of research focusing on IS predicting these agricultural characteristics, many studies have only employed the research in a single region/location resulting in findings that may lacking reproducibility and replication (R&R) for more than a single environment. The lack of regionally comparative IS methods for nutrient and plant health analysis is important as varying geographies may prove to have an effect on IS findings. Therefore, the proposed research utilizes IS methods to predict nutrient and plant health values utilizing tef (Eragrostis tef) as a case study as its cultivated in Ethiopia and the United States. Currently, in the United States, the cultivation of tef is limited thus the United States could benefit from an exploration of site suitability analysis to aid expansion of tef cultivation in the U.S. It is through this interdisciplinary study that potential improvement to geography and remote sensing theory/methods can be obtained to achieve goals within food/agriculture geography

Wheat Improvement

This open-access textbook provides a comprehensive, up-to-date guide for students and practitioners wishing to access in a single volume the key disciplines and principles of wheat breeding. Wheat is a cornerstone of food security: it is the most widely grown of any crop and provides 20% of all human calories and protein. The authorship of this book includes world class researchers and breeders whose expertise spans cutting-edge academic science all the way to impacts in farmers’ fields. The book’s themes and authors were selected to provide a didactic work that considers the background to wheat improvement, current mainstream breeding approaches, and translational research and avant garde technologies that enable new breakthroughs in science to impact productivity. While the volume provides an overview for professionals interested in wheat, many of the ideas and methods presented are equally relevant to small grain cereals and crop improvement in general. The book is affordable, and because it is open access, can be readily shared and translated -- in whole or in part -- to university classes, members of breeding teams (from directors to technicians), conference participants, extension agents and farmers. Given the challenges currently faced by academia, industry and national wheat programs to produce higher crop yields --- often with less inputs and under increasingly harsher climates -- this volume is a timely addition to their toolkit

Handbook of plant and soil analysis for agricultural systems

[SPA] Este libro recopila diferentes protocolos para el análisis de plantas y suelos para sistemas agrícolas. Nuestro objetivo es proporcionar un conjunto completo de indicadores para evaluar la productividad de los cultivos, la calidad de los cultivos, la calidad del suelo y la fertilidad del suelo con procedimientos y métodos viables y sólidos. La evaluación de la sostenibilidad de los agroecosistemas requiere la selección de indicadores adecuados y su medida. El presente manual ha compilado diferentes indicadores para evaluar el crecimiento de los cultivos, la incidencia de plagas y enfermedades, el rendimiento de la granja, la calidad de los cultivos y las características nutricionales, los análisis físicos del suelo, los análisis químicos del suelo y los análisis biológicos del suelo. El libro está organizado en tres partes: i) análisis de plantas y cultivos, ii) análisis físico-químicos del suelo y iii) análisis biológicos del suelo. En total, proporcionamos 90 procedimientos para el análisis de plantas y suelos, incluida la importancia y las aplicaciones, el principio del método descrito, los reactivos necesarios, los materiales y equipos, la descripción detallada del procedimiento, los cálculos necesarios y algunas observaciones específicas.[ENG] This books compiles different protocols for analysis of plant and soil for agricultural systems. We aim to provide a complete set of indicators to assess crop productivity, crop quality, soil quality and soil fertility with feasible and robust procedures and methods. The assessment of the sustainability of agroecosystems needs the selection of suitable indicators and their measure. The present handbook has compiled different indicators to assess crop growth, incidence of pests and diseases, farm yield, crop quality and nutritional characteristics, soil physical analyses, soil chemical analyses and soil biological analyses. The book is organized in three parts: i) plant and crop analyses, ii) soil physicochemical analyses and iii) soil biological analyses. In total we provide 90 procedures for plant and soil analysis, including the importance and applications, the principle of the method described, the reagents needed, the materials and equipment, the detailed description of the procedure, the calculations required and some specific remarks.This project has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No 72800

Genetic architecture of wheat yield responses to drought

Maintaining wheat grain yield under expected more frequent and maybe severe drought episodes requires identifying the drought tolerance traits as well as deciphering the genetic basis of these traits responses to drought, and utilising potential symbiotic endophytes to alleviate drought effects. The aim of this project was to conduct an in-depth study of the genetic architecture of wheat responses to drought, deciphering the genetic basis of both source and sink traits under field conditions, as well as, investigating the ability of the endophyte fungus Piriformospora indica to increase yield in both well-watered and drought conditions and identify QTL underpinning drought-resistance traits influenced by endophytic growth. In the field trial, a representative subset of the elite eight-founder population, comprising 384 RILs, the founders and a check variety 'Kielder' were tested in rainfed vs irrigated field blocks, monitoring soil moisture content at different depth intervals. Field plots were phenotyped throughout the growing season using integrative drone-based and proximal sensing approaches. The results showed maximum soil moisture deficit (SMD) peaking over 120 mm in the rain fed plots, with large deficits (>75 mm) from late April that coincided with tillering and more prolonged large deficits from mid-June to mid-July(> I 00 mm), significantly decreasing crop canopy indices at all measured dates post-irrigation and causing significant increase in canopy temperature of rainfed plots, all driving an average yield reduction of 32.8% which was significantly genotype dependent. Also identifying traits most significantly (p:S0.00 I ) correlated with yield revealed grains.m-2 (r=0.68) and (r=0.72) and canopy temperature depression (CTD) (r=0.52) and (r=0.61) in rainfed and irrigated condition, respectively. QTL analysis for yield revealed a total of 16 novel QTL expressed commonly across both treatments explaining individually I to 4.5% as well as treatment dependent QTL. With remarkable examples of grain yield QTL collocating with major QTL such as grains.m-2 QTL on chromosome 3A and Rht-Dl pleiotropic region on chromosome 40 and highlighting significant SNP-SNP epistatic interactions for yield occasionally coinciding with QTL for crop canopy indices. Investigating the response of 200 MAGIC lines to P. indica inoculation showed the potential of the endophyte to significantly increase yield in well-watered and drought conditions, however, for most traits, there was significant difference in genotypes responses to colonization. Several QTL unique to colonized plants were detected on most chromosomes and linked to measured traits under drought, Those QTL can be investigated as candidate genes governing the symbiosis between wheat and P. indica

XX Convegno nazionale dell'Associazione italiana di Agrometeorologia (AIAM). XLVI Convegno nazionale della Società italiana di Agronomia (SIA). Strategie integrate per affrontare le sfide climatiche e agronomiche nella gestione dei sistemi agroalimentari. Integrated strategies for agro-ecosystem management to address climate change challenges.

Atti del convegno nazionale di due delle principali società scientifiche che si occupano di scienze agrarie (Società Italiana di Agronomia e Associazione Italiana di AgroMeteorologia), quest'anno effettuato congiuntamente. Nel convegno si à trattato dei problemi e delle nuove strategie integrate per affrontare le sfide climatiche e agronomiche nella gestione dei sistemi agroalimentari