The production of silage is typically carried out in cylindrical bales covered with polyethylene foils. In this study a novel approach was tested towards obtaining innovative composition of these films.

In the first stage of the experiment six combinations with different composition of additives including microcellulose and nanosilver particles were analyzed. The bales were formed and the forage value was evaluated during the storage after 5, 11 and 17 months based on the analysis of the content of dry matter, total protein, crude fiber, nitrate nitrogen, sugars, acids (lactic, acetic, butyric, and propionic), and determination of pH. In order to assess the microbial forage quality, the abundance of the lactic acid bacteria was determined and compared with the number of aerobic bacteria, yeast and fungi. The foil properties were also analyzed with the appropriate chemical and microbiological methods. The results showed no significant differences (p<0.05) between the standard commercial films and tested formulae. The best characteristics were revealed by the film with the addition of 5% microcellulose.

The second stage of the work was aimed at testing the applicability of a recycled polyethylene (PE) as a film component. Two combinations, each with a nanosilver additive, were prepared: one contained a layer made from a recycled PE, and the second with the conventional PE. Standard methods for the assessment of silage and foil quality were used, as previously. The results revealed no significant differences (p<0,05) between the silages obtained with the use of innovative films and the standard ones. A slightly higher content of acids and elevated pH was observed for the tested formulae compared to the control sample. In addition, a higher number of lactic acid bacteria was observed on the internal surface of film and in the silage for the standard PE foil with the addition of nanosilver than for other variants.

Satellite Earth observation provides timely and spatially explicit information on crop phenology that can support sustainable agricultural land management, in terms of natural resource protection and adaptation to climate and other environmental changes. Accurate classification and mapping of croplands is a primary information for environmental impact assessment in the agricultural sector. This research study presents a digital agriculture approach that integrates Earth observation big data analytics based on machine learning technologies to classify and map main crops types. Two supervised machine learning models were calibrated using Random Forest algorithm from phenological metrics, estimated from NDVI and LAI vegetation indices time series calculated using Copernicus Sentinel-2 MSI satellite acquisitions. Models were calibrated for the Toscana region in Italy, where reliable spatially explicit agricultural data were available. Results show that the proposed method can achieve a satisfactory overall accuracy (~78%) in croplands classification, and that model calibrated using phenological metrics estimated from LAI time series performs slightly better than the model calibrated using NDVI derived phenological metrics. The proposed approach offers a potential to accurately map crop types, offering a simple yet reliable way to derive important agricultural land management information and to support agricultural monitoring systems for large areas at field level over time.

In the Amazon, the Sumaco Biosphere Reserve (SBR) is considered a key point of natural and cultural diversity. It is populated by several indigenous groups, including the Kichwa, who are characterized by their traditional production systems, which are a means of subsistence and socio-ecological integration, The objectives were: a) identify the sociodemographic characteristics at the household level, b) quantify the multitemporal change in land cover and c) determine the sustainability of traditional agroforestry systems Kichwa. The study was carried out in the Sumaco Biosphere Reserve, with the participation of 340 indigenous Kichwa have 157 traditional agroforestry systems distributed in three communities. The sociodemographic structure and distribution was identified through twelve demographic indicators, through the google earth engine platform in 5 consecutive years and distributed in two periods 1) 2015-2017, 2) 2018-2020 and the response-inducing sustainability evaluation (RISE) methodology was used according to the social, economic and ecological dimensions, expressed through 10 indicators of 50 parameters, valued from 0 (worst case) to 100 (best case) , the results are expressed in a polygon, defined by the areas: (1) good performance, (2) medium performance and (3) poor performance. A pyramidal structure of a progressive type characteristic of young populations was identified, as well as the multitemporal change between the different categories of land cover from vegetative to non-vegetative type, and four indicators with low performance were identified: use of materials and environmental protection, energy and climate, economic viability, farm management; which are guidelines for local and regional decision makers

Global climate change has raised serious concerns about food security and the sustainability of agriculture, particularly in developing regions of the world. In response to these concerns, attention should be called to the global importance of conservation of some neglected and underutilized crops, like Lythyrus species, which are nutrient-rich and already adapted to harsh environments and low-input agriculture.

Lathyrus cicera L., known in Morocco as ‘ikiker’, ‘kiker’ or ‘ichicher, is marginally cultivated in the region. Landraces of this crop species, which are maintained locally by traditional agricultural practices, correspond to ecotypes adapted to local agroclimatic conditions. We have surveyed the traditional cultivation sites of this crop to identify specific associated agroecosystems the Middle and High Atlas mountains of Morocco.

We have evaluated the diversity of ecotypes of Lathyrus cicera L. by a set of characters associated with the socioeconomic and agromorphological aspects of their cultivation. The results confirmed that their cultivation is very old in the area, and that its maintenance until today is important as the local farmers have started to master the uses for human and animal food. In addition, from a biology point of view, we have demonstrated the existence of variability depending on the trait considered but which demonstrates a differentiation between the ecotypes. From adaptive potential of these ecotypes with respect to tolerance to aridity and increased temperatures, the ecotypes studied showed promising prospects for selection. Thus, in spite of the limitation of the territory and the regression of the culture, the studied ecotypes have a very interesting germinative and productive capacity. This result can be explained by cultural practices.

These ecotypes are maintained in traditional agroecosystems which play the role of conservatory of neglected resources. The conservation of these genetic resources therefore depends on the conservation of the traditional agroecosystem and local knowledge.

The aim of this study was to evaluate the effect of different irrigation systems on cv. Cobrançosa olive oil main components, in a semiarid region in the Northeast of Portugal (Alfândega da Fé, 2019) - regulated (RDI) and sustained deficit (SDI) against well-irrigated controls (FI). Total polyphenols (Folin) were higher in RDI than SDI and FW treatments. Among the phenolic components, hydroxytyrosol and tyrosol derivatives (HPLC, after acid hydrolysis), were higher in olive oils obtained under SDI, potentially complying with the nutrition allegation allowed in Regulation (EU) No 432/2012, (“polyphenols in olive oil contribute to the protection of blood lipids against undesirable oxidation”), while the amounts in FW and RDI olive oils were 10% lower to the threshold. Olive oil vitamin E (mainly α-tocopherol) was also higher in oils obtained from SDI deficit irrigation treatments while oils from RDI had values very close to FI treatments. Olive oil bitterness, evaluated by K225, was highly positively correlated with TP (r2 = 0.94, p<0.01). The fatty acidy profile was not affect by the irrigation regime. Results are preliminary and need to be continued to extract solid conclusions.

Municipal sewage sludge is a problematic waste that needs to be managed. Modern wastewater treatment plants (WWTPs) generate stabilized sewage sludge with good chemical and biological parameters. Plenty of WWTPs digest sewage sludge in fermentation chambers for two purposes – the use of biogas and thermal sludge stabilization. The fermented sewage sludge can be utilized for organic or organo-mineral fertilizer production. The Central Mining Institute (CMI) in Katowice (Poland) has developed a proprietary technology for production of a granulated organo-mineral fertilizer from the stabilized sewage sludge.
The innovative fertilizer developed by CMI (patent PL 233754), fully complying with the Polish law requirements, is a mixture of municipal dewatered sewage sludge collected from municipal WWTPs, dolomite (50% CaCO3, 40% MgCO3), lime (96% CaO), gypsum, ammonium carbonate and microcrystalline cellulose. Sewage sludge for fertilizer production contained heavy metals at levels lower than: Cr, 100 mg; Cd, 5 mg; Ni, 60 mg; Pb, 140 mg; Hg, 2 mg.
Sewage sludge-based fertilizer made with the CMI technology was free from live eggs of intestinal parasites Ascaria sp., Trichuris sp., and Toxacara sp. as well as from bacteria of the genus Salmonella. The fertilizer was verified to fulfill the environmental safety rules and to have a stimulatory impact on plant growth.
Micro-field tests were conducted at WWTP in Żory (Poland) and carried out on five fields (5m2 each). To evaluate the effectiveness of plant growth, drone photos were made to show field coverage upon vegetation, and the plant dry mass was determined after harvest. Dry mass analyses showed significant changes in biomass chemical composition: the N concentration was 289,6% of the control and 98,2% of commercial fertilizer, whereas the respective P content was 145,1% and 300%. The results prove that the fertilizer produced from municipal sewage sludge is highly competitive with other available commercial products.

Sicily, with its variable pedoclimatic conditions, represents an important source of biodiversity. In this context, over the past centuries, farmers have made a continuous selection that has led to the creation of numerous landraces.The aim of this study was to determinate how different temperature regimes affect seed germinating traits of four conventional varieties of durum wheat most cultivated in Sicily for seed production (Simeto, Core, Antalis and Orizzonte) and eight landraces (Bidì, Capeiti 8, Castiglione glabro, Faricello, Francesa, Perciasacchi, Timilia Reste Bianche e Timilia Reste Nere). Seeds were tested under 3 temperature regimes (10 °C, 20 °C and 30 °C). Experiments were laid out in a two factorial design using a complete randomize design (CRD) with four replications. Nine parameters were measured under laboratory condition: germination, shoot length, root length, roots number, seed vigor index, fresh shoot weight, fresh root weight, dry shoot weight, dry root weight. The data collected were examined using analysis of variance techniques (ANOVA) to identify significant differences among temperatures and genotypes. Duncan’s Multiple Range test was applied at 5% level of probability to compare the mean differences. Pearson’s correlation coefficient between different traits and the main factor was also computed.

Temperature, genotype and their interaction determined highly significative differences in all the germination traits studied. Raise in temperature has determined a specific increasing trend of value for Shoot Length, Seed Vigour Index, Fresh Shoot weight, Dry Shoot Weight and Dry Root Weight. The growth of the root system has decreased to the highest temperature. Correlation study among germination parameters showed a positive and highly significant correlation of Shoot Length with Seed Vigour Index and Fresh Shoot Weight in all temperature regime. No positive and significative correlation between Germination and Shoot length, Root length, Fresh Shoot Weight, Fresh Root Weight, Dry Shoot weight and Dry Root Weight has been shown. Our data indicate that Faricello, Perciasacchi and Timilia R.B show a good resistance to cold temperature and Bidì has a good growth rate of many germination traits that makes this landrace very attractive.

The difficulties in assessing the distinctness characters in lucerne plants have recently led to reject the registration to the EU database of registered plant varieties for several new varieties with valuable agronomic characteristics. The tendency of lucerne plants to grow during winter and its fall dormancy can be efficient discrimination tools for the varieties during registration tests and could be an interesting agronomic characteristic to evaluate cultivar adaptability to different climatic conditions.

The information about the dormancy of lucerne are limited and the dormancy class of many Italian varieties is still unknown. The aim of our study was to validate the method proposed by the International Union for the Protection of New Varieties of Plants (UPOV) for the assessment of the dormancy class and to classify an adequate number of Italian cultivars. The experiment was carried out during three consecutive Distinctness, Uniformity and Stability (DUS) trials, lasting 18 months each, from 2016 to 2019 at the experimental farm of the CREA-DC located in Palermo, Italy. The method was based on the linear regression analysis to evaluate the functional relationship between the fall dormancy class (FDC) and the natural plant height (NPH) measured during the different DUS trials in five growth stages. Seven varieties, representing the fall dormancy classes (FDC) 2, 4, 5, 6, 7, and 9 (UPOV), were used as control varieties and twenty-one varieties under DUS testing were evaluated to assess their dormancy class. A Principal Component Analysis (PCA) was performed using the data matrix varieties x NPH. The models obtained were used to estimate the fall dormancy class of the candidate varieties and the results were compared with the visual dormancy class. The first principal component and the fall dormancy class had a significant linear relationship in all the years of the trial. NPH4 and NPH15 showed to be a useful tool for the discrimination of lucerne cultivars with different dormancy ratings.

Hyperspectral images (HSI) offer detailed spectral reflectance information about sensed objects under favour of hundreds of narrow spectral bands. HSI have a leading role on a broad range of applications, such as forestry, agriculture, geology and environmental sciences. Monitoring and managing of agricultural lands has a great importance on meeting nutritional and other needs of rapidly and continuously increasing world’s population. In this case, classification of HSI is an effective way to creating land use and land cover maps fast and accurately. In recent years, classifying of HSI with convolutional neural networks (CNN) which is a sub-field of deep learning become a very popular research topic and several CNN architectures were developed by researchers. The aim of this study is to investigate the classification performance of CNN model on agricultural HSI scenes. For this purpose, a 3D-2D CNN framework and well-known support vector machine (SVM) model were compared by using Indian Pines and Salinas Scene datasets that contain crop and mixed vegetation classes. As a result of this study, using of 3D-2D CNN has a superior performance on classifying agricultural HSI datasets.

As a result of human activity, the rate of extinction of species is now 100 to 1000 times faster than under natural conditions. According to the FAO, 75% of the genetic diversity of agricultural crops worldwide has been lost since 1990. In Poland, about 100 species of field weeds are in danger of extinction. Archaeophytes growing on heavy calcareous soils, which are characteristic of the Lathyro-Melandrietum noctiflori, Caucalido-Scandicetum, Kicxietum spuriae communities, and weeds associated with the cultivation of flax are particularly endangered. Halting the loss of rural biodiversity is a priority for the EU's protection of environmental strategy.

Research aimed at assessing the weed infestation status of agrophytocoenoses located on rendzinas in the Lublin Province (Poland) has been conducted since 1997. The research was carried out using the Braun-Blanquet phytosociological method. Lublin Province is located in the south-eastern part of Poland. There are good conditions for agricultural production. Agricultural land covers 57.9% of the total area of the voivodship, of which 99.3% is agricultural land in good farming standard. In such favorable environmental conditions, agriculture in the Lublin Province is characterized by an unfavorable structure of farms. 55.6% of over 180 thousand of farms are those with an area not exceeding 5 ha. Such a large fragmentation of farms results in a low profitability of the agricultural sector, which results from extensive farming. Research has shown that low-input agriculture is conducive to the preservation of rare and endangered species of segetal flora. Muscari comosum — a critically endangered (ER) species under strict protection were found on several sites in the study area. Several sites of Caucalis platycarpos and Galium tricornutum, also recognized as ERs, were found in heavy rendzinas. Moreover, numerous sites of such rare species as: Adonis aestivalis, Anthemis tinctoria, Thymelaea passerina, Anagallis foemina, Chaenorhinum minus and Euphorbia exigua were located.

Research on the state of the population of rare species is a big challenge for scientists, because only knowledge about it will provide the basis for future relevant actions aimed at maintaining biodiversity and restoring degraded ecosystems