Hydroponic systems, which use commercial hydroponics technologies, are cheaper and easier to maintain than traditional farming methods in soil. The objective of this study was to evaluate various salinity ranges (E.C.i from 1 dS/m to 14 dS/m) in water enriched with nanobubbles (NBs) for the growth and productivity of lettuce plants in a floating disk hydroponic system. This research study investigated how using floating disks in a greenhouse with a nanobubble (NB) generator may affect lettuce’s (Lactuca sativa L.) morphological and physiological responses to salt stress. The goal of this experiment was to examine the results of the influence of NB and non-NB treatments on agronomic traits and yield. The results indicated that the NB device is an innovative and very effective technology for sustainable lettuce production under a high-salinity nutrient solution. This device presents a valuable solution to the global issue of the increased salinity of irrigation water.

BACKGROUND Nutritional quality in bell pepper is related to the ripening stage of the fruit at harvest and postharvest storage. Its determination requires time-consuming, tissue-destructive, analytical laboratory techniques. The objective of this study was to investigate the effect of ripening stage and of postharvest storage period on fruit nutritional quality, and whether it is feasible to develop reliable models for assessing the nutritional components in peppers using non-destructive methods. The dry matter, soluble solids, ascorbic acid, phenolics, chlorophylls, carotenoids and the total antioxidant capacity were determined in bell pepper fruits at six ripening stages, from green to full red, during storage at 10 degrees C for 8 days. Color, chlorophyll fluorescence, visible/near infrared (Vis/NIR) spectroscopy, red-green-blue (R-G-B) and red-green-near infrared (R-G-NIR) digital imaging were tested for assessing the nutritional quality of peppers. RESULTS The nutritional composition was mainly affected by the ripening stage of bell pepper fruits at harvest and only to a small degree by the storage period. Indeed, the more advanced ripening stage of fruit at harvest resulted in superior nutritional quality. Most of the non-destructive techniques reliably predicted the internal quality of the fruit. The genetic algorithm (GA), the variable importance in projection (VIP) scores, and the variable inflation factor (VIF) tests identified nine distinct regions and four specific wavelengths on the whole visible/NIR electromagnetic spectrum that exhibited the most significant effect in the assessment of the nutritional components. CONCLUSION It is possible to predict individual nutritional components in bell pepper fruit reliably and non-destructively, and irrespective of the ripening stage of fruits at harvest. (c) 2021 Society of Chemical Industry.

Background: Quality and safety of potato is both cultivar and postharvest management dependent. The precise assessment of freshness and cultivar are complex tasks requiring time-consuming, expensive, and destructive techniques. Method: Potatoes from three commercial cultivars were stored for 5 months at 5 °C. Color and chlorophyll fluorescence were recorded, Red-Green-Blue (R-G-B), Red-Green-Near infrared (R-G-NIR) and Red-Blue-Near infrared (R-B-NIR) digital images, as well as hyperspectral images were acquired both on the external periderm of the tuber and in the inner flesh part. Partial least square regression (PLSR) and discriminant analysis, combined with feature selection techniques were implemented, in order to assess the potato freshness and to classify them into the respective genotypes. Results: The PLSR analysis of visible/near infrared (Vis/NIR) spectra reflectance most reliably predicted potato freshness, with a cross-validated regression coefficient equal to 0.981 and 0.947, as determined by external or internal measurements, respectively. Variance inflation factor, variable importance scores, and genetic algorithms identified specific wavelength regions that mostly affected the accuracy of the model in terms of strongest regression and lowest collinearity and root mean cross validation error. Conclusions: Vis/NIR spectra reflectance data from the skin of the potato tubers may be reliably used in the assessment of postharvest storage life, as well as in the cultivar discrimination process.

The use of conventional ground spraying systems (tractor assisted or manual/backpack types) in tree spraying varies among farmers, depending on crop species grown, farm size, soil relief characteristics and machinery or man-labor available. Most farmers use their sprayers without any precise estimation of the coverage percent, uniformity, drifting and other important issues on spraying materials and safety regulations. The recent developments of aerial spraying, using Unmanned Aerial Vehicles–UAVs or Systems UASs (a.k.a. drones) offer unique new application capabilities. However, very limited information exist in spraying systems comparative studies. Therefore, the purpose of this study is to investigate the spraying characteristics of the most commonly used ground type sprayers, equipped with conventional and electrostatic nozzles and a spraying drone, for spraying in a high-density olive grove in Greece. Water Sensitive papers (WSP) and two scanning software (DepositScan and SnapCard) were used to quantify spraying coverage percent and other droplet characteristics. Amount of spray solution used and operation time along with spraying configuration, were also recorded for each trial. The results revealed significant differences among the used systems in spraying characteristics and also between the electrostatic and conventional nozzles. The quantities used by the conventional ground systems were up to 45 times more than the drones, while the operation time for ground systems was up to 6 times more than the drones. The findings supported the potential of spraying drones as a tool to increase spraying efficiency and precision of agrochemical applications. The main current limitation in EU for aerial application by drones remains the current legislation in EU which is expected to be updated and clarify the use in agricultural applications.

The optimal quality, the marketability and the shelf-life of pepper fruit often depend on the ripening stage at harvest. Moreover, it is necessary to estimate the process of ripening in various steps of the supply chain. The potential of four non-destructive techniques as rapid tools for discriminating the process of ripening was investigated. Chlorophyll fluorescence, Vis/NIR spectroscopy, two commercial digital imaging cameras- one R-G-B dslr and a modified R-G-NIR compact camera were assessed as alternatives to color measurements in classifying pepper fruit according to their ripening stage. Freshly harvested mature bell pepper fruit 'cv. Denver' were sorted in six distinct ripening stages (S1-S6), from green to full red (mature green 100% green-S1, green to brown-S2, brown-S3, orange-S4, red-S5 and full red-S6 stage), by visually assessing their color. From the results, it is concluded that the a* /b* color parameter that was determined using a colorimeter was proven to be the most accurate descriptor in ripening stage classification, either at harvest or during storage, as confirmed by che-mometrics, such as principal component (PCA), partial least square (PLS) and support vector machine (SVM) analyses and mean comparisons, as well. Therefore, the increase of a* /b* ratio can be used as an indicator to estimate the degree of fruit ripeness. The a* /b* ratio was strongly correlated with fruit spectral reflectance and chlorophyll fluorescence data, as well as with two imaging indices generated by digital R-G-B and R-G-NIR imaging techniques that are reported for the first time on fruit in this study. The above results indicate that it is possible to estimate the a* /b* ratio and simultaneously the ripening stage of pepper fruit with high accuracy and consistency, by using individually several non-destructive techniques. However, freshness status of bell pepper fruit can be reliably assessed, irrespectively of the ripening stage at harvest, only by spectral reflectance data and indeed even by processing only specific wavelengths that were identified after implementing the genetic algorithm.

Safety and quality of agricultural products with better management and conservation of natural resources has become a significant issue worldwide and it constantly raises awareness in Greece, especially within the last decade.Latest advancements of the evolving agricultural sector towards applications of Precision Agriculture and Smart/Digital Farming and the "greening" of the agriculture based on the latest directives of Common Agricultural Policy (CAP) of the European Union (EU) for the current and the upcoming period (>2022) and the Green Deal , constitute a rigid framework of promising future opportunities and transformations.Additionally, new and emerging cultivation practices, like soilless farming (e.g., Hydroponics, Aquaponics, Aeroponics, vertical agriculture) and intensive, Integrated Agriculture and minimum tillage cropping systems, constitute high-tech solutions of production in Greece.However, as they require significant agrochemical inputs, high energy consumption vehicles and expensive infrastructures, they keep on polluting and exhausting the natural resources.An alternative, sustainable solution, based in latest technological advancements, is urgently needed.In this chapter, an approach is presented for the convergence of Smart Farming, Agricultural Robotics with Geospatial Technologies, providing solutions of their efficient collaboration towards farming practices.Focus will be given to the accumulated promises and opportunities which arise and they may constitute a new, innovative, and sustainable model of agriculture for Greece.

The effect of previous cultivation of sugarbeet, legume, cotton and corn on the subsequent crops of cotton and corn was studied in a two year rotation cycle at two Greek locations in 1994 and 1995. This paper only discusses the two cultivation systems, 1) sugarbeet cotton and 2) cotton cotton. The effect of sugarbeet in cotton cultivation is considered negative based on various field observations and the personal experience of farmers. Some of the supposed causes of this effect are evaluated. Growth analysis in cotton grown after sugarbeet showed that plants had a significant delay in appearance of squares, flowers and bolls, delayed weight development of vegetative and reproductive parts, delayed Leaf Area development and reduced chlorophyll, compared to cotton grown after cotton. This difference gradually declined or disappeared during plant life cycle. Thus although cotton grown after sugarbeet yielded less in the first picking, total yield was not inferior. Soil analytical data during the second year were not found to be influenced by the previous cultivation. Heavy rainfall in October 1994 and spring 1995 possibly leached residual N and balanced the differences between crops. In addition, no sugarbeet residues were left in the soil and it was hand harvested, possibly explaining the lack of effect on the C/N ratio and soil mycoflora. The increased soil compaction observed in plots planted to sugarbeet, combined with delayed cotton growth, support the hypothesis that the swollen sugarbeet roots increase soil compaction, prohibiting root penetration of the following cotton crop.

Important weather parameters and their impact on cotton productivity were investigated in three main regions of Greek cotton production. Daily values of air temperature, solar radiation and precipitation for the period 1994-1997 were used, recorded on data loggers in fully automatic meteorological stations installed in the three study areas. The total global radiation data were transformed to sunshine duration in hours. Crop development was assessed with the accumulated heat units method above a threshold temperature (10oC). It was found that the year-to-year fluctuations in cotton productivity could be estimated with this method, but only at a given area with similar management practice. Additionally, sharp drops in temperature during critical stages of cotton growth may result in appreciable reduction in crop productivity, even if the actual air temperature does not fall below the threshold levels for cotton growth.

Modern approaches in sustainable agricultural production management require holistic approaches and evaluation of the water use efficiency and water footprint. The irrigation water scarcity due to overuse and quality deterioration due to increased salinity levels, represent significant obstacles in sustainable agricultural systems. Systems that promote and evaluate less-inputs and more efficient production are strongly considered lately. This study presents results of two years from an olive grove, planted in high density linear systems adapted for mechanical harvesting. The grove was established in 2011 in Thessaloniki, Greece, for long term evaluation of the effects of major production inputs in olive yield and olive oil quantity and quality. The experimental design includes three planting densities (medium, high and super high density; 500, 1000 and 1670 trees/ha, correspondingly), two commonly used worldwide olive oil varieties/clones adapted for mechanical harvesting (Koroneiki and Arbequina), grown under two irrigation levels (conventional and 50% less) and two fertility levels (conventional and 50% less) with a foliar split application in the fertility treatments. Results from the two years (2015 and 2016) on water use efficiency (WUE) and water footprint (WF) are presented in this paper. The results indicated that increase in WUE and decrease in WF was achieved with management approaches such as planting density at least for the measured period and tree age. Additional efforts to minimize water use and increase WUE are in progress.

The main objective of this study was to examine if the degree and direction of soil heterogeneity in an experimental field would affect yield performances of 10 different maize hybrids (Zea mays L.). Analyses for soil reaction (pH), electrical conductivity (ECs) and soil organic carbon (SOC) were conducted following a sampling grid; bare soil spectral response in the infra-red (IR) range was also recorded in the same locations using a handheld sensor. Geostatistical analyses showed that there was significant variability in soil conditions among strips of maize hybrids (especially for EC), as well as along most of the strips; and also, several hot spots of high or low values were detected for all measured properties. As a result, the experimental design and statistical analysis followed for comparing yield performances of the hybrid varieties was expected to be biased due to differentiated soil conditions. Therefore, a more sophisticated analysis is suggested to be designed, with a view to identifying management zones within the experimental field.

Irrigation water quality became worst in terms of increasing its salinity and causes severe problems in many cultivated crop species, resulting in lower yield. In addition, the scarcity of irrigation water due to overuse or runoff is another limitation for increasing food and feed production. Saline water treatment technology offers potential solutions; however this technology is yet expensive and not cost effective for large scale. This study evaluates a water treatment technology (MAXGROW) using ultra sound for treating saline water, for its potential to minimize effects of saline irrigation water and its possible effects of crop productivity. A greenhouse study in pots was undertaken using two substrates (a sandy loam soil and a mixture of pumice and a composted material), four vegetable species (green onions, spinach, radishes and arugula) which were irrigated with two qualities of irrigation water (a highly saline and a regular irrigation water) treated and untreated with the MAXGROW technology. The results showed an increased yield caused by the treated saline water in almost all species and in both growth substrates. The potential of this device was shown to be promising and it is currently under continuous evaluation using more species and higher salinity level irrigation water. Irrigation water efficiency is a potential deliverable from the system.

Cover crops are essential in agricultural management and especially in organic farming for protecting the soil from erosion, competing with weeds, preventing evaporative losses and improving soil quality and fertility. The choice of cover crop species is crucial in achieving the highest level of weed suppression and soil fertility enhancement. Cover crop systems with rye or mixtures of legumes and grasses were set up in a randomized complete block design in Northern Greece. A hand held sensor was used to measure Normalized Difference Vegetation Index (NDVI) of the cover crop plots with parallel measurements of light interception with a PAR sensor, and destructive biomass determination. Weed biomass was also determined for each cover crop mixture. Multi-species cover crops produced higher total biomass than single-species cover crop systems. All cover crop systems evaluated were able to suppress weeds. Remote sensing results showed that NDVI could be used to estimate the total biomass of single cover crops but not cover crop mixtures.

Worldwide olive production recently has undergone major changes in terms of harvesting technologies and planting densities. A new educational, research and exhibition olive grove was established at Perrotis College, Greece in 2010 to evaluate new production systems under a variety of planting densities and major input treatments for two of the most commonly used olive varieties globally, under high density palnting systems adapted for mechanical harvesting. Precision agriculture practices were used in this olive grove, to identify possible “zones of variation” for yield, crop reflectance using the handheld GreenSeeker® NDVI sensor and for soil moisture and electrical conductivity. The results are presented herein for the second year after planting and they indicated distinctive zones of variability for the measured characteristics. These zones will be considered and further validated in the current season, to provide alternative management practices for optimization of olive production and combined with additional soil and agronomic parameters.