Faba Bean Cultivation – Revealing Novel Managing Practices for More Sustainable and Competitive European Cropping Systems

Faba beans are highly nutritious because of their high protein content: they are a good source of mineral nutrients, vitamins, and numerous bioactive compounds. Equally important is the contribution of faba bean in maintaining the sustainability of agricultural systems, as it is highly efficient in the symbiotic fixation of atmospheric nitrogen. This article provides an overview of factors influencing faba bean yield and quality, and addresses the main biotic and abiotic constraints. It also reviews the factors relating to the availability of genetic material and the agronomic features of faba bean production that contribute to high yield and the improvement of European cropping systems. Emphasis is to the importance of using new high-yielding cultivars that are characterized by a high protein content, low antinutritional compound content, and resistance to biotic and abiotic stresses. New cultivars should combine several of these characteristics if an increased and more stable production of faba bean in specific agroecological zones is to be achieved. Considering that climate change is also gradually affecting many European regions, it is imperative to breed elite cultivars that feature a higher abiotic–biotic stress resistance and nutritional value than currently used cultivars. Improved agronomical practices for faba bean crops, such as crop establishment and plant density, fertilization and irrigation regime, weed, pest and disease management, harvesting time, and harvesting practices are also addressed, since they play a crucial role in both the production and quality of faba bean

Reviewing the essential roles of remote phenotyping, GWAS and explainable AI in practical marker-assisted selection for drought-tolerant winter wheat breeding

Marker-assisted selection (MAS) plays a crucial role in crop breeding improving the speed and precision of conventional breeding programmes by quickly and reliably identifying and selecting plants with desired traits. However, the efficacy of MAS depends on several prerequisites, with precise phenotyping being a key aspect of any plant breeding programme. Recent advancements in high-throughput remote phenotyping, facilitated by unmanned aerial vehicles coupled to machine learning, offer a non-destructive and efficient alternative to traditional, time-consuming, and labour-intensive methods. Furthermore, MAS relies on knowledge of marker-trait associations, commonly obtained through genome-wide association studies (GWAS), to understand complex traits such as drought tolerance, including yield components and phenology. However, GWAS has limitations that artificial intelligence (AI) has been shown to partially overcome. Additionally, AI and its explainable variants, which ensure transparency and interpretability, are increasingly being used as recognised problem-solving tools throughout the breeding process. Given these rapid technological advancements, this review provides an overview of state-of-the-art methods and processes underlying each MAS, from phenotyping, genotyping and association analyses to the integration of explainable AI along the entire workflow. In this context, we specifically address the challenges and importance of breeding winter wheat for greater drought tolerance with stable yields, as regional droughts during critical developmental stages pose a threat to winter wheat production. Finally, we explore the transition from scientific progress to practical implementation and discuss ways to bridge the gap between cutting-edge developments and breeders, expediting MAS-based winter wheat breeding for drought tolerance

Cover cropping in water limited environments : a field and modelling study of hydrological and soil structural effects of cover crops and their impact on the water balance

Zwischenfruchtbau ist eine verbreitete Agrarumweltmaßnahme zum Boden- und Grundwasserschutz. Ziel der Studie war die Analyse des Wasserverbrauchs durch Zwischenfrüchte unter semiariden Bedingungen für ein verbessertes Management an wasserlimitierten Standorten. Biomassebildung, Bodenbedeckung und Wurzelparameter von Phacelia, Winterwicke, Roggen und Senf wurden charakterisiert. Effekte auf die Wasserbilanz wurden mit einer Feldmessstelle untersucht und detaillierte Messungen der Infiltration im Makroporenbereich durchgeführt. Die Wasserdynamik wurde mit der FAO Pflanzen-Koeffizienten-Methode sowie dem Modell HYDRUS 1D analysiert. Biomassebildung und Bodenbedeckung von Senf, mit starker Haupt- und dichten Seitenwurzeln, erwiesen sich am stabilsten gegenüber Trockenheit. Wicke zeigte eine geringe Wurzeldichte, jedoch eine homogene Tiefenverteilung, die eine hohe Biomassebildung erlaubte. Das Wurzelsystem von Phacelia war nahe der Sprossbasis konzentriert und nahm in vertikale und horizontale Richtung rasch ab. Roggen erreichte auch unter günstigen Bedingungen eine geringe Bodenabdeckung im Herbst, zeigte jedoch eine hohe Durchwurzelungsintensität. Bei herbstlicher Trockenheit lag die Verdunstung der Begrünungen über der Brache, wobei der Pflanzenanteil nur zwischen 17,6 % und 52,6 % der gesamten Evapotranspiration ausmachte. Wasseranteilunterschiede zur Brache reduzierten sich über Winter auf 2,8 %. Die Infiltration im Makroporenbereich zeigte eine hohe räumliche und zeitliche Variabilität. Es konnte jedoch eine Makroporenstabilisierung durch die Zwischenfrüchte gezeigt werden. Die Ergebnisse bestätigen die Möglichkeit des Zwischenfruchtbaus in semiariden Gebieten ohne überhöhtes Risiko von Ertragsverlusten. Stabilisierung der hydraulischen Bodeneigenschaften über Winter und Verringerung der Bodenverdunstung durch eine rasche Bodenbedeckung im Spätsommer tragen zu einem Ausgleich des potentiell höheren Wasserentzugs während der Wachstumszeit der Begrünungen bei.Cover cropping is a common agro-environmental instrument for soil and groundwater protection. The objective of this study was to assess the risk of soil water depletion by cover crops in a semi-arid environment to improve management for water limited conditions. Aboveground biomass, soil cover and rooting parameters of phacelia, hairy vetch, rye and mustard were characterized. Soil water status under the cover crops and a fallow control was monitored with a field measurement site and infiltration in the macropore range was investigated in detail. Water dynamics were analysis using the FAO Dual Crop Coefficient method and the model HYDRUS 1D. Mustard was most stable under dry conditions with an intense vertical and lateral root system. Vetch had a low rooting density, but a homogeneous depth distribution of roots that could sustain a high biomass growth. The root system of phacelia was intense near the stem base with a high decrease in the vertical and horizontal direction. Rye had only low soil cover before winter, but provided a high root biomass and dense rooting of the soil. Cover crops showed a higher cumulative evapotranspiration compared to fallow under dry conditions in autumn. Plant transpiration accounted for only 17.6 % to 52.6 % of total evapotranspiration. Soil moisture differences to fallow during cover crop growth were reduced over winter to 2.8 % in spring. Water infiltration in the macropore range showed high temporal and spatial variability. A certain stabilization of macropores over winter was found for the cover crops. The study showed that cover cropping in a semi-arid region is feasible without higher risk of yield losses due to water storage depletion. Stabilization of soil structure related hydraulic properties over winter and the reduction of evaporation losses in late summer by plants with a fast canopy cover contribute to equilibrate potential higher water extraction from deep soil layers during the main growing period of the cover crops.submitted by Gernot BodnerAbweichender Titel laut Übersetzung der Verfasserin/des VerfassersZsfassung in dt. SpracheWien, Univ. für Bodenkultur, Diss., 2007OeBB(VLID)193147

The Root Systems in Sustainable Agricultural Intensification

International audienc

Phenotyping: Using Machine Learning for Improved Pairwise Genotype Classification Based on Root Traits

Phenotyping local crop cultivars is becoming more and more important, as they are an important genetic source for breeding—especially in regard to inherent root system architectures. Machine learning algorithms are promising tools to assist in the analysis of complex data sets; novel approaches are need to apply them on root phenotyping data of mature plants.A greenhouse experiment was conducted in large, sand-filled columns to differentiate 16 European Pisum sativum cultivars based on 36 manually derived root traits. Through combining random forest and support vector machine models, machine learning algorithms were successfully used for unbiased identification of most distinguishing root traits and subsequent pair-wise cultivar differentiation. Up to 86% of pea cultivar pairs could be distinguished based on top five important root traits (Timp5)—Timp5 differed widely between cultivar pairs. Selecting top important root traits (Timp) provided a significant improved classification compared to using all available traits or randomly selected trait sets. The most frequent Timp of mature pea cultivars was total surface area of lateral roots originating from tap root segments at 0-5cm depth. The high classification rate implies that culturing did not lead to a major loss of variability in root system architecture in the studied pea cultivars. Our results illustrate the potential of machine learning approaches for unbiased (root) trait selection and cultivar classification based on rather small, complex phenotypic data sets derived from pot experiments. Powerful statistical approaches are essential to make use of the increasing amount of (root) phenotyping information, integrating the complex trait sets describing crop cultivars

Prospects of selection for barley seed vigour as a precondition for stand emergence under dry condition.

Study evaluated a segregating population of doubled-haploid lines and malting varieties for seed vigour tested at a low temperature of 10°C and under drought stress of -0.2 MPa and -0.5 MPa. The vigour of the dihaploid lines from six variants (3 years × 2 localities) was compared with four germination parameters obtained under the optimum thermal and moisture conditions The vigour of seeds of four spring varieties of malting barley and their mutual 12 combinations was assessed in two variants (1 year × 2 locations). Higher precipitation sums in June and July, i.e. shortly before harvest, were reflected in a decreased vigour (r = -0.777 and r = -0.721). Higher air temperatures during the period of April - July increased the vigour significantly (r = 0.741). Correlation between the vigour and the germination parameters (r = 0.454 - 0.539) was higher than in case of these germination parameters and the germination capacity (r = 0.266 - 0.351). The relationship between the vigour of parents and their progenies (r = 0.894) was significant. The results showed that barley seed vigour is a polygenic trait affecting the field emergence and malting quality. The increased vigor can be successfully achieved with traditional breeding methods.(In English

Management of crop water under drought: a review

International audienceDrought is a predominant cause of low yields worldwide. There is an urgent need for more water efficient cropping systems facing large water consumption of irrigated agriculture and high unproductive losses via runoff and evaporation. Identification of yield-limiting constraints in the plant–soil–atmosphere continuum are the key to improved management of plant water stress. Crop ecology provides a systematic approach for this purpose integrating soil hydrology and plant physiology into the context of crop production. We review main climate, soil and plant properties and processes that determine yield in different water-limited environments. From this analysis, management measures for cropping systems under specific drought conditions are derived. Major findings from literature analysis are as follows. (1) Unproductive water losses such as evaporation and runoff increase from continental in-season rainfall climates to storage-dependent winter rainfall climates. Highest losses occur under tropical residual moisture regimes with short intense rainy season. (2) Sites with a climatic dry season require adaptation via phenology and water saving to ensure stable yields. Intermittent droughts can be buffered via the root system, which is still largely underutilised for better stress resistance. (3) At short-term better management options such as mulching and date of seeding allow to adjust cropping systems to site constraints. Adapted cultivars can improve the synchronisation between crop water demand and soil supply. At long term, soil hydraulic and plant physiological constraints can be overcome by changing tillage systems and breeding new varieties with higher stress resistance. (4) Interactions between plant and soil, particularly in the rhizosphere, are a way towards better crop water supply. Targeted management of such plant–soil interactions is still at infancy. We conclude that understanding site-specific stress hydrology is imperative to select the most efficient measures to mitigate stress. Major progress in future can be expected from crop ecology focussing on the management of complex plant (root)–soil interactions

Hyperspectral imaging: a novel approach for plant root phenotyping

Abstract Background Root phenotyping aims to characterize root system architecture because of its functional role in resource acquisition. RGB imaging and analysis procedures measure root system traits via colour contrasts between roots and growth media or artificial backgrounds. In the case of plants grown in soil-filled rhizoboxes, where the colour contrast can be poor, it is hypothesized that root imaging based on spectral signatures improves segmentation and provides additional knowledge on physico-chemical root properties. Results Root systems of Triticum durum grown in soil-filled rhizoboxes were scanned in a spectral range of 1000–1700 nm with 222 narrow bands and a spatial resolution of 0.1 mm. A data processing pipeline was developed for automatic root segmentation and analysis of spectral root signatures. Spectral- and RGB-based root segmentation did not significantly differ in accuracy even for a bright soil background. Best spectral segmentation was obtained from log-linearized and asymptotic least squares corrected images via fuzzy clustering and multilevel thresholding. Root axes revealed major spectral distinction between center and border regions. Root decay was captured by an exponential function of the difference spectra between water and structural carbon absorption regions. Conclusions Fundamentals for root phenotyping using hyperspectral imaging have been established by means of an image processing pipeline for automated segmentation of soil-grown plant roots at a high spatial resolution and for the exploration of spectral signatures encoding physico-chemical root zone properties

Identification of Water Use Strategies at Early Growth Stages in Durum Wheat from Shoot Phenotyping and Physiological Measurements

Modern imaging technology provides new approaches to plant phenotyping for traits relevant to crop yield and resource efficiency. Our objective was to investigate water use strategies at early growth stages in durum wheat genetic resources using shoot imaging at the ScreenHouse phenotyping facility combined with physiological measurements. Twelve durum landraces from different pedoclimatic backgrounds were compared to three modern check cultivars in a greenhouse pot experiment under well-watered (75% plant available water, PAW) and drought (25% PAW) conditions. Transpiration rate was analyzed for the underlying main morphological (leaf area duration) and physiological (stomata conductance) factors. Combining both morphological and physiological regulation of transpiration, four distinct water use types were identified. Most landraces had high transpiration rates either due to extensive leaf area (area types) or both large leaf areas together with high stomata conductance (spender types). All modern cultivars were distinguished by high stomata conductance with comparatively compact canopies (conductance types). Only few landraces were water saver types with both small canopy and low stomata conductance. During early growth, genotypes with large leaf area had high dry-matter accumulation under both well-watered and drought conditions compared to genotypes with compact stature. However, high stomata conductance was the basis to achieve high dry matter per unit leaf area, indicating high assimilation capacity as a key for productivity in modern cultivars. We conclude that the identified water use strategies based on early growth shoot phenotyping combined with stomata conductance provide an appropriate framework for targeted selection of distinct pre-breeding material adapted to different types of water limited environments