The Effect of Tillage on Faba Bean (Vicia faba L.) Nitrogen Fixation in Durum Wheat ((Triticum turgidum L. subsp. Durum (Desf))-Based Rotation under a Mediterranean Climate

Biological nitrogen fixation (BNF) is a sustainable approach to improving soil fertility that not only provides nitrogen to subsequent crops but also reduces the impacts of synthetic fertilizers. Here, a field experiment was established within the faba bean (Vicia faba L.), cv Prothabat 69-durum wheat (Triticum turgidum L. subsp. Durum (Desf)), cv Iride rotation framework of a long-term experiment in southern Italy to quantify BNF over two consecutive years (2012/13–2013/14). The effect of tillage systems (reduced, conventional, and no tillage) on faba bean N2 fixation was estimated at the flowering and maturity stages via the natural abundance technique, using wheat as a reference crop. The effect of tillage on the percentage of nitrogen fixation from the atmosphere (Ndfa) and the amount of N2 fixed (kg ha−1) were higher under a no-tillage system in both years and at both growth stages, with values of 66.5% at flowering and 81.7% at maturity. The same trend was reported for the amount of N2 fixed (kg N ha−1) at both faba bean growth stages. The N balance was positive in both years, with a mean value of 40.4 kg N ha−1, across all tillage systems; this value was greater in the no-tillage systems (45.7 kg N ha−1) with respect to the others. The values for the organic matter content and stability index were higher under the no-tillage system, which provided favourable conditions that improved N2 fixation by faba beans. The overall results indicate that no-tillage soil management represents a sustainable strategy for improving soil quality and fertility, therefore reducing the dependency of agriculture on synthetic fertilizers

A comparison of the energy consumption of rainfed durum wheat under different management scenarios in southern Italy

An energy consumption analysis comparing 12 management scenarios of durum wheat grown in southern Italy was carried out in order to identify the most energy efficient system with regard to productivity. The results showed that yield parameters were significantly affected by the tillage system and revealed that conservation tillage entailed the fewest field operations and lowest energy requirements with higher yield.Nitrogen rates had slight effects on yield parameters, whereas a linear relationship was found between increasing energy input and increasing nitrogen fertilizer. The highest proportion of energy input came from diesel fuel, followed by nitrogen fertilizer.Total input energy used per hectare increased with the increase in management intensity. However, per 1kg of grain, energy intensity was directly linked to grain yield. The lowest average of 1.8MJkg-1 was for conservation tillage, followed by intensive tillage with 2.9MJkg-1, whereas reduced tillage was the most energy intense with 3.1MJkg-1.Conservation tillage of durum wheat in southern Italy can be used to maintain or increase productivity with only a minimum energy input

Different Suitability of Olive Cultivars Resistant to Xylella fastidiosa to the Super-Intensive Planting System

Until today, only Leccino and Fs-17 (=Favolosa®) olive cultivars proved resistant to Xylella fastidiosa subsp. pauca (Xfp) due to a low presence of bacteria in the xylem. Integrated disease management in olive growing areas threatened by the spread of Xfp is crucial to overcoming the environmental, economic and social crisis. Since the EU Decision allows for the plantation of resistant olive cultivars in infected areas, there is a need to define a suitable plantation system for these cultivars. The adoption of new planting systems, such as intensive and super-intensive (SHD), could compensate for the economic losses and restore the olive agroecosystem. The aim is to ascertain the suitability of the available Xfp-resistant cultivars to SHD planting systems that demonstrate the best economic and environmental sustainability. Hence, a five-year study was established in an experimental SHD olive orchard (Southern Italy) in order to analyse the main vegetative and productive traits of Leccino and Fs-17, together with four other Italian cultivars (Cipressino, Coratina, Frantoio and Urano), compared with the well-adapted cultivars to SHD orchards (Arbequina and Arbosana), by means of the von Bertalanffy function. The results indicated that cv. Fs-17 showed sufficient suitability for SHD planting systems, giving the best-accumulated yield despite some canopy growth limitations, whereas cv. Leccino did not show satisfactory results in terms of both vegetative and yield parameters, confirming its suitability for intensive planting systems. These results are useful for optimizing integrated resistance management in Xfp-infected areas by planting resistant host plants

Influence of nitrogen application on wheat crop performance, soil properties, greenhouse gas emissions and carbon footprint in central Bhutan

In Bhutan, wheat (Triticum aestivum L.) is an important staple crop and its productivity is low due to poor soil fertility and inadequate external inputs. Hence, effects of four levels of nitrogen (N) [0, 50, 80 and 100 kg N ha−1] on wheat crop and soil properties were examined for two consecutive years (2012 and 2013) in a rice-wheat rotation. The experiment was set up in a randomized complete block design and the treatments replicated three times. In addition, greenhouse gas (GHG) emission was analyzed both per unit area and per kilogram of wheat grain to determine the emission-intense sources. Data were subjected to analysis of variance. Among the treatments, 100 kg N ha−1 had the largest effect on grain yield and dry biomass and on plant height. Significant correlations were detected for the N rates vs. dry biomass. However, correlations between N rates vs. soil N, C:N ratio and pH were significant for 2013 only. The average GHG emissions were 1114.2 kg CO2e ha−1 and 0.533 kg CO2e kg−1 grain and the emissions per hectare were highly influenced by N rates whereas the emissions per kilogram of grain were influenced by grain yield. We concluded that, in Bhutan, the application of N-fertilizer significantly enhanced wheat productivity and soil health at N rates of ≥50 kg N ha−1. Further, the results indicated potentials to increase wheat yield with lower GHG emissions through improved N management

Utilizing transfer learning and a customized loss function for optic disc segmentation from retinal images

Accurate segmentation of the optic disc from a retinal image is vital to extracting retinal features that may be highly correlated with retinal conditions such as glaucoma. In this paper, we propose a deep-learning based approach capable of segmenting the optic disc given a high-precision retinal fundus image. Our approach utilizes a UNET-based model with a VGG16 encoder trained on the ImageNet dataset. This study can be distinguished from other studies in the customization made for the VGG16 model, the diversity of the datasets adopted, the duration of disc segmentation, the loss function utilized, and the number of parameters required to train our model. Our approach was tested on seven publicly available datasets augmented by a dataset from a private clinic that was annotated by two Doctors of Optometry through a web portal built for this purpose. We achieved an accuracy of 99.78% and a Dice coefficient of 94.73% for a disc segmentation from a retinal image in 0.03 s. The results obtained from comprehensive experiments demonstrate the robustness of our approach to disc segmentation of retinal images obtained from different sources