Session 41 - Agroforestry, Forest and Agricultural Sustainability

Nitrogen fixation is a beneficial microbial process that greatly contribute to sustainable agricultural production and environment protection. Soil bacteria, collectively named rhizobia, are characterized by their unique ability to induce the formation of root nodules in which they convert molecular nitrogen into a usable form for plants. Soybean plants require a large amount of nitrogen for their development and achievement of high seed yields. The use of high quality rhizobial inoculants strives to optimize nitrogen nutrition of soybean with minimal environmental impacts. Selection of the most suitable Bradyrhizobium japonicum strains is of great importance for successful soybean inoculation as well as optimal nitrogen fertilization. The aim of the present study was to determine the impact of fertilization with different rates of mineral nitrogen on nodulation and symbiotic efficiency of indigenous B. japonicum strains. In the vegetation pot experiment two indigenous and one reference B. japonicum strain as well as different rates of mineral nitrogen were tested. Application of increased rates of mineral nitrogen reduced number of nodules and nodule dry weight. The highest nitrogen content was determined in plants grown without any mineral nitrogen fertilization but inoculated with indigenous B. japonicum strains.

Session: 41, Room: E, at Sat, 09/07/2019 - 10:30 to 10:33
Flash presentation in Agroforestry, Forest and Agricultural Sustainability

Valonia oak is the most widespread tree species found in the Aegean island of Kea - Cyclades. It forms traditional agroforestry systems since intensive agriculture is not easily practiced in the island due to the xerothermic climate and the rough terrain with steep slopes. This system has traditionally supported the local economy by its multiple products while respecting the environment. In almost all the cases, it is found in traditional terraces which were constructed since ancient times by local farmers. Even if these systems have been threatened by abandonment and change of land use (mainly for touristic purposes), there has been an increasing interest lately motivated by the higher price gained by valonia oak acorns trade and demand for agrotouristic activities. An experimental plot was established under the framework of the AGFORWARD (FP7) research project, where two commercial pasture mixes were tested for their productive capacity under shade. Soil properties were evaluated at the end of the experiment to evaluate the effect of intercropping on the economy of certain nutrients. The importance of the environmental and economic function of this system is highlighted and suggestions are made for its preservation.

Session: 41, Room: E, at Sat, 09/07/2019 - 10:15 to 10:30
Oral presentation in Agroforestry, Forest and Agricultural Sustainability

The characterization of soil properties is critical for optimizing farming for sustainable agriculture. All the existing techniques for soil quantification do not take advantage of the sequential nature of Hyperspectral Data. This work focuses on proposing a Hybrid Framework that can quantitatively assess the soil properties from Hyperspectral data by extracting the essential features via Principal Component Analysis and Locality Preserving Projections. The extracted features are combined to form the Hybrid dataset which is then given as input to Long Short-Term Memory Networks, a deep learning-based framework which is typically used for sequential problems. The effectiveness of the Hybrid Framework is shown by comparing it with the existing regression models.

Session: 41, Room: E, at Sat, 09/07/2019 - 09:45 to 10:00
Oral presentation in Agroforestry, Forest and Agricultural Sustainability

The organic carbon percentage is concomitant indicating the mineralization of nutrients and the ability of the soil to hold nutrients cations, structural stability, and water holding capacity. It is necessary to know the quantity of carbon for healthy soil and avoid the production related problems which can affect the sustainable agriculture model. In existing approaches, to quantitively calculate soil carbon, sample collection and in-situ laboratory testing are performed. In this work, a novel framework is proposed which is based on Partial Least Square Regression and Long Short-Term Memory networks to quantify soil organic carbon from the LUCAS dataset. Samples of LUCAS dataset are used as input to this framework. The samples are pre-processed by PLS to reduce their dimensions. These pre-processed samples are then passed to the LSTM, a Deep learning framework to build an efficient prediction model. The proposed framework performed more accurately, and its effectiveness is shown by comparing it with existing regression models.

Session: 41, Room: E, at Sat, 09/07/2019 - 10:00 to 10:15
Oral presentation in Agroforestry, Forest and Agricultural Sustainability

Commercial Microwave Links (CMLs), that provide the underlying framework for data transfer between cellular network base stations have been found effective for monitoring rainfall. Wireless infrastructure of this kind is deployed widely by communication providers across Africa and can be used as a complementary monitoring device to the sparse proprietary resources that exist currently, and at minimal cost, or as a substitute tool in the many cases where alternatives do not exist. Here we focus on the potential that lies in this novel approach to acquire valuable information required for agricultural needs over the poverty-stricken countries of Africa.

Session: 41, Room: E, at Sat, 09/07/2019 - 09:30 to 09:45
Oral presentation in Agroforestry, Forest and Agricultural Sustainability

Inhomogeneities of soil properties are responsible for within-field variations on the growth and final yield of crops. In this paper the variations of a Normalized Difference Vegetation Index (NDVI) field map, obtained through a camera mounted on an Unmanned Aerial Vehicle, were correlated with soil and plant properties measured in a typical maize cultivated field. Subsequently, the perspective of organizing the field into differential management zones through the NDVI was evaluated. The coefficient of variation for sand, silt, clay and soil organic matter content at five points was found to exceed 11% while the corresponding value for biomass and yield were greater than 14%, indicating significant spatial field soil heterogeneity and variations on plant growth. When correlated to NDVI, sand content exhibited a negative correlation (r=-0.86), while in the case of silt, clay, organic matter content, biomass and yield the correlation was positive (r>0.8). Lastly, the NDVI confirmed to be a powerful tool for the delineation of deferential management zones.

Session: 41, Room: E, at Sat, 09/07/2019 - 09:15 to 09:30
Oral presentation in Agroforestry, Forest and Agricultural Sustainability

Moringa oleifera (Lam) is a fast growing tree that is gradually getting more attention for it numerous uses. It is often called "natural gift" or "miracle tree" because of its many nutritional, forage, medicinal and industrial potentialities. Moringa oleifera appears to be a promising multipurpose species for use under a changing climate. To test possible adaptation potential and / or tolerance of Moringa oleifera to water stress, an experiment was conducted under semi controlled conditions. Stress was induced in the semi-controlled experiment by the application of different concentrations of polyethylene glycol (PEG-6000), to cause different levels of water potential stress for twenty days. The effect of water stress to plant growth was evaluated based on chlorophyll (a and b) and carotenoid compared to controls. Water stress resulted to a 70% gain in chlorophylls b, 44% losses in chlorophyll a and 45% in carotenoids. These results testify the tolerance ability of Moringa oleifera plants to water stress.

Session: 41, Room: E, at Sat, 09/07/2019 - 09:00 to 09:15
Oral presentation in Agroforestry, Forest and Agricultural Sustainability