Socioeconomic profile of producers and dairy technological of farms in the southern mesoregion of Santa Catarina

This study characterized the socioeconomic profile of milk producers and dairy technological of farms in the southern mesoregion of Santa Catarina. Following a 6.5% sampling of total farms by municipality, 95% confidence level, 5% sampling error, and group heterogeneity, data were collected from 308 farms, 22 of which were excluded due to insufficient data. The farmers were selected randomly, and information extracted from an electronic form, addressing social, economic, technical and technological issues. The data were analyzed using factor, cluster, and discriminant analysis. As farms with the main activity of dairy farming, they have an average area of 20.79 hectares and a production of 12.18 liters per animal per day. I n the factor analysis, the first factor was related to the area and productivity of farms and the second factor to sanitary control and the feed variety of the animals. The cluster analysis formed three clusters; the first and the second were composed of larger farms and areas, and the other consisted of smaller farms, the latter involving more producers. As farms are characterized by low production, there is clearly a deficiency in technical support for producers.

What drives small-scale farmers to adopt conservation agriculture practices in Tanzania?

Conservation Agriculture (CA)-based Sustainable Intensification (CASI) practices in this study comprised minimum soil disturbance, permanent soil cover, intercropping of maize and legumes, and use of improved crop genotypes and fertilizers, and were tested on-farm in different agroecologies in northern and eastern Tanzania. The results for six consecutive years of study indicate increased adoption of CASI practices compared to the baseline year (2010). The major impacts of these practices were reduced production costs, labour savings and overall increased crop and land productivity. The average area allocated to improved maize-legume (ML) intercrop rose during the project period by 5.28 ha per household, of which 15% was under complete CASI practices. Adoption trends show that, on average, 6.5% of adopters across the study and spillover communities started adoption in the 2nd year and about 14% of farmers adopted the practices over the next 3-5 years. Demographic and human capital (family size, education, age and farming experience), on-farm CASI demonstrations, farmer to farmer exchange visits, social capital (farmers' group or a cooperative), access to input and output markets (improved seeds, herbicides, fertilizers, insecticides and equipment) and food security were found to have positive and significant effects on adoption of a range of CASI practices. These results suggest continued and long-term efforts in investments in demonstrations, institutionalizing CASI practices in NARS, and good links to input and output markets, including appropriate machinery, are necessary to achieve sustained adoption.

Insight into Market Supply and Demand of Private Forests in Croatia

Due to their modest 23% share, private forests in Croatia are a resource that is perceived as less important than state-owned forests. One of the basic characteristics of private forests is fragmentation, which is also the biggest obstacle to a successful and, economically speaking, sustainable management of private forests. The cases in which a private forest with its area and integrity can generate a sustainable economic income to its owner are not common. However, from an economic point of view, private forests still have one advantage. Unlike state-owned forests, private forests can be the subject of investment and change hands. Based on this, this paper investigates the supply of private forests on the free market. For private forests that were publicly put for sale in the period from 2010 to 2020, their spatial-temporal distribution and supply dynamics and trends (price and quantity) were analyzed. The data were collected from the leading real estate advertising platform in Croatia (Njuškalo.hr), and a total of 866 advertisements were analyzed, relating exclusively to the sale of raw wood material along with the accompanying forest land. On the other hand, in order to assess the demand, data were collected on the number of potential buyers who viewed the advertisements (period 2020-2021). In the observed ten-year period, a total of 1,890.63 ha of private forests with a total asking value of €32.14 million were offered on the market. The share of advertisements advertised through real estate agencies is 42.1%. The average total annual supply is 170 ha and has a growing trend (in the advertisements in the coastal part of Croatia, the average area is 1.3 ha, while the average area in the continental part is 3 ha). The prices are not constant but rising. According to compound interest, the price increase in the coastal area is 1.57% and 7.49% in the continental area. From the relationship between supply and demand or, more precisely, the relationship between price and the quantity, it was concluded that the market is not well developed and that the price is not affected by the supply/demand quantity of private forests. Furthermore, it was concluded that this market is developing in the direction of a typical real estate market in Croatia due to the fact that forest management and wood processing characteristics of forests do not define the price, but that the price is largely determined by a market with greater financial importance (the market in real estate near the Adriatic coast).

The Effect of Urban Drainage on The Determination The Time of Storage In The City Development Area

Increasing development activities in various fields in Surabaya will impact the occurrence of flooding, where the growth of residential buildings changes the function of the drainage area into runoff land. Therefore, there is a need for regional drainage recommendations. This study aims to provide a reference for a safe number that follows the storage needs and the duration of the peak partial drainage required by the region, following the study of water resources science. The data needed are rainfall data, average area, land function, and land slope maps. This study uses a 5-year return period probability. Moreover, the Nakayasu Hydrograph method is also used. It has a grace period starting from the rain surface to the top of the hydrograph, the area of the watershed, and the length of the main river channel. The comparison of the length of time of concentration (Tc) of the area with the length of waiting for time (Tp) of the urban drainage hydrograph shows that the area’s Tc value is greater than the Tp value of the urban drainage.

Segmentation Scale Effect Analysis in the Object-Oriented Method of High-Spatial-Resolution Image Classification

High-spatial-resolution images play an important role in land cover classification, and object-based image analysis (OBIA) presents a good method of processing high-spatial-resolution images. Segmentation, as the most important premise of OBIA, significantly affects the image classification and target recognition results. However, scale selection for image segmentation is difficult and complicated for OBIA. The main challenge in image segmentation is the selection of the optimal segmentation parameters and an algorithm that can effectively extract the image information. This paper presents an approach that can effectively select an optimal segmentation scale based on land object average areas. First, 20 different segmentation scales were used for image segmentation. Next, the classification and regression tree model (CART) was used for image classification based on 20 different segmentation results, where four types of features were calculated and used, including image spectral bands value, texture value, vegetation indices, and spatial feature indices, respectively. WorldView-3 images were used as the experimental data to verify the validity of the proposed method for the selection of the optimal segmentation scale parameter. In order to decide the effect of the segmentation scale on the object area level, the average areas of different land objects were estimated based on the classification results. Experiments based on the multi-scale segmentation scale testify to the validity of the land object’s average area-based method for the selection of optimal segmentation scale parameters. The study results indicated that segmentation scales are strongly correlated with an object’s average area, and thus, the optimal segmentation scale of every land object can be obtained. In this regard, we conclude that the area-based segmentation scale selection method is suitable to determine optimal segmentation parameters for different land objects. We hope the segmentation scale selection method used in this study can be further extended and used for different image segmentation algorithms.

Typologie des exploitations agricoles productrices du mil et niébé pluvial dans la commune rurale de Karma

Principale activité des ruraux nigériens, l’agriculture fait face à des problèmes récurrents de baisse de rendements conduisant à la paupérisation et à l’insécurité alimentaire des ménages qui l’exercent. Cette étude conduite à Karma vise la caractérisation des systèmes de production du mil et de niébé pluvial en vue de connaître leurs fonctionnements et leurs diverses interactions dans un contexte de changement climatique. Pour cela, une enquête a été conduite sur un échantillon de 90 ménages d’exploitants du mil et niébé pluvial. L’étude a montré que les systèmes de production sont regroupés en trois types selon la méthode d’Analyse en Composantes Principales couplée à la classification de Nuées dynamiques. Il s’agit du système de production agricole pure (Type A), du système agroforesterie (Type B) et du système agropastoral (Type C). Le type (A) occupe une superficie moyenne de 1,5 hectares. Il est scindé en système de cultures sèches simple et système de cultures sèches associé au maraîchage. Le type (B) s’effectue sur 2,18 hectares et le type (C) sur une superficie moyenne de 3,25 hectares. Ainsi, le type (C) est plus performant que le type (B) qui l’est plus que le type (A). English title: Typology of farms producing millet and rain-fed cowpeas in the rural commune of Karma Main activity of nigeriens’ rural, agriculture faces recurring problems drop in yields leading to pauperization and food insecurity of the households that exert it. This study conducted in Karma aims to characterize millet and rain-fed cowpea production systems with a view to understanding their functioning and their various interactions to enable producers to better cope with climate change. For this, a survey was conducted on a sample of 90 households farms of millet and rain-fed cowpea. The study showed that production systems are grouped into three types according to the Principal Component Analysis method coupled with classification. of dynamic clouds. These are the pure agricultural production system (Type A), the agroforestry system (Type B) and the agro-pastoral system (Type C). Type (A) occupies an average area of 1.5 hectares. It is split into a simple dry crop system and a dry crop system associated with market gardening. Type (B) takes place on 2.18 hectares and type (C) on an average area of 3.25 hectares. Thus, type (C) is more efficient than type (B) which is better than type (A).

Copra processing issue of migrant farmers in tidal land of South Sumatra

The study was carried out in the tidal land region of Pendowo Harjo Village, Sungsang District, Banyuasin District, South Sumatra Province, with the goal of calculating the production costs and income gained, as well as determining the financial feasibility of the copra processing business. Simple random selection was used to choose sample farmers, with 45 sample farmers managing the copra processing business chosen from a total of 235 population members. All sample farmers were Bugis ethnic migrant farmers. The analysis results showed that with an average area of 1.15 hectares, an income of IDR 2,530,886.98 was obtained. The production costs incurred were IDR 1,756,328.15 resulting in an income of IDR 774,558.83 per arable area per production process (for a period of 3 months). The NPV value was IDR 102,638,789.00, with the IRR value was 49.92 per cent, and the Net B/C value was 2.28. These figures show that a copra processing business can be developed in the area financially.

Comparative evaluation between the “All on Four” and “Four on Pillars” techniques in 3D virtual planning associated with guided surgery on atrophic jaws

Thorough technical knowledge and anatomical understanding are critical for optimal surgical results. The difficulty of complete maxillary surgery can vary significantly depending on the complexity of the anatomy or bone defect. In this work, we analyze and compare two methods of software-guided planning for the manipulation of dental implants, associated with the All on Four (ALL) and Four on pillars (FOUR) techniques used in patients with atrophic maxillae. Forty-two images of totally edentulous patients were analyzed, and surgical planning was performed using both methods. The average area of the Four on pillars technique is 4.9x (p<0.0001) greater than the average area of the All on four technique, this represents a difference of 489%. This means that, for the same force applied by the jaw, we will have a 4.9x smaller pressure, that is, a better distribution of forces on the jaws. It was not possible to notice a statistical difference between the success proportions (p=0.2542), this means that both techniques have a non-different (similar) success proportion. We conclude that the area of the polygon formed in the Four on pillars surgical plan is larger than in the All on four plan and this results in significantly less pressure on the implants. We also concluded that it was not possible to notice a statistical difference between the proportions of success, which shows that there is no technique with successful performance advantages over the other.

Unveiling the Factors Responsible for Australia’s Black Summer Fires of 2019/2020

The summer season of 2019–2020 has been named Australia’s Black Summer because of the large forest fires that burnt for months in southeast Australia, affecting millions of Australia’s citizens and hundreds of millions of animals and capturing global media attention. This extensive fire season has been attributed to the global climate crisis, a long drought season and extreme fire weather conditions. Our aim in this study was to examine the factors that have led some of the wildfires to burn over larger areas for a longer duration and to cause more damage to vegetation. To this end, we studied all large forest and non-forest fires (>100 km2) that burnt in Australia between September 2019 and mid-February 2020 (Australia’s Black Summer fires), focusing on the forest fires in southeast Australia. We used a segmentation algorithm to define individual polygons of large fires based on the burn date from NASA’s Visible Infrared Imaging Radiometer Suite (VIIRS) active fires product and the Moderate Resolution Imaging Spectroradiometer (MODIS) burnt area product (MCD64A1). For each of the wildfires, we calculated the following 10 response variables, which served as proxies for the fires’ extent in space and time, spread and intensity: fire area, fire duration (days), the average spread of fire (area/days), fire radiative power (FRP; as detected by NASA’s MODIS Collection 6 active fires product (MCD14ML)), two burn severity products, and changes in vegetation as a result of the fire (as calculated using the vegetation health index (VHI) derived from AVHRR and VIIRS as well as live fuel moisture content (LFMC), photosynthetic vegetation (PV) and combined photosynthetic and non-photosynthetic vegetation (PV+NPV) derived from MODIS). We also computed more than 30 climatic, vegetation and anthropogenic variables based on remotely sensed derived variables, climatic time series and land cover datasets, which served as the explanatory variables. Altogether, 391 large fires were identified for Australia’s Black Summer. These included 205 forest fires with an average area of 584 km2 and 186 non-forest fires with an average area of 445 km2; 63 of the forest fires took place in southeast (SE) Australia (the area between Fraser Island, Queensland, and Kangaroo Island, South Australia), with an average area of 1097 km2. Australia’s Black Summer forest fires burnt for more days compared with non-forest fires. Overall, the stepwise regression models were most successful at explaining the response variables for the forest fires in SE Australia (n = 63; median-adjusted R2 of 64.3%), followed by all forest fires (n = 205; median-adjusted R2 of 55.8%) and all non-forest fires (n = 186; median-adjusted R2 of 48.2%). The two response variables that were best explained by the explanatory variables used as proxies for fires’ extent, spread and intensity across all models for the Black Summer forest and non-forest fires were the change in PV due to fire (median-adjusted R2 of 69.1%) and the change in VHI due to fire (median-adjusted R2 of 66.3%). Amongst the variables we examined, vegetation and fuel-related variables (such as previous frequency of fires and the conditions of the vegetation before the fire) were found to be more prevalent in the multivariate models for explaining the response variables in comparison with climatic and anthropogenic variables. This result suggests that better management of wildland–urban interfaces and natural vegetation using cultural and prescribed burning as well as planning landscapes with less flammable and more fire-tolerant ground cover plants may reduce fire risk to communities living near forests, but this is challenging given the sheer size and diversity of ecosystems in Australia.

Microplastics Investigation Using Zooplankton Samples from the Coasts of Cyprus (Eastern Mediterranean)

The Mediterranean Sea has the highest accumulation of microplastics in the world. Although numerous studies about microplastic’s abundance and distribution have been conducted, the majority sampled surface waters. Especially for the Eastern Mediterranean, there is no information concerning the deeper strata. This study fills this gap by studying the microplastic spatial and temporal distribution along the coasts of Cyprus, utilizing zooplankton samples collected from the entire 0–50 m depth layer. The average microplastics’ abundance was 41.31 ± 22.41 items/m3 indicating that the Eastern Mediterranean seems to be much more polluted than the western basin. The fibers outnumbered the abundance of the fragments by a factor of ten. Most fibers were sized between 0.5 and 1.0 mm, and 81.24% were transparent. The average area of the fragments was ≤0.05 mm2, and most of them were hard-rounded (53.38%). The microplastics to zooplankton ratio ranged between 0.021 and 0.241. A positive correlation was found between the abundance of microplastics and the total zooplankton, especially the copepods. Studies of microplastics in zooplankton samples taken from the water column are expected to provide better insights into the role of these pollutants in marine ecosystems.