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Agronomy, Volume 9, Issue 2 (February 2019)

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Cover Story (view full-size image) Our study found that rice husk biochar addition on upland field converted paddy could greatly [...] Read more.
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Open AccessFeature PaperArticle Effects of Temperature and Grafting on Yield, Nutrient Uptake, and Water Use Efficiency of a Hydroponic Sweet Pepper Crop
Agronomy 2019, 9(2), 110; https://doi.org/10.3390/agronomy9020110
Received: 11 January 2019 / Revised: 20 February 2019 / Accepted: 22 February 2019 / Published: 25 February 2019
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Abstract
In areas characterized by mild winter climate, pepper is frequently cultivated in unheated greenhouses in which the temperature during the winter may drop to suboptimal levels. Under low temperature (LT) conditions, the uptake of nutrients may be altered in a different manner than [...] Read more.
In areas characterized by mild winter climate, pepper is frequently cultivated in unheated greenhouses in which the temperature during the winter may drop to suboptimal levels. Under low temperature (LT) conditions, the uptake of nutrients may be altered in a different manner than that of the water and thus their uptake ratio, known as uptake concentration, may be different than in greenhouses with standard temperature (ST) conditions. In the present study, pepper plants of the cultivars “Sammy” and “Orangery”, self-grafted or grafted onto two commercial rootstocks (“Robusto” and “Terrano”), were cultivated in a greenhouse under either ST or LT temperature conditions. The aim of the study was to test the impact of grafting and greenhouse temperature on total yield, water use efficiency, and nutrient uptake. The LT regime reduced the yield by about 50% in “Sammy” and 33% in “Orangery”, irrespective of the grafting combination. Grafting of “Sammy” onto both “Robusto” and “Terrano” increased the total fruit yield by 39% and 34% compared with the self-grafted control, while grafting of “Orangery” increased the yield only when the rootstock was “Terrano”. The yield increase resulted exclusively from enhancement of the fruit number per plant. Both the water consumption and the water use efficiency were negatively affected by the LT regime, however the temperature effect interacted with the rootstock/scion combination. The LT increased the uptake concentrations (UC) of K, Ca, Mg, N, and Mn, while it decreased strongly that of P and slightly the UC of Fe and Zn. The UC of K and Mg were influenced by the rootstock/scion combination, however this effect interacted with the temperature regime. In contrast, the Ca, N, and P concentrations were not influenced by the grafting combination. The results of the present study show that the impact of grafting on yield and nutrient uptake in pepper depend not merely on the rootstock genotype, however on the rootstock/scion combination. Full article
(This article belongs to the Special Issue Nutrition Management of Hydroponic Vegetable Crops)
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Open AccessArticle Optimizing the Sowing Date and Irrigation Strategy to Improve Maize Yield by Using CERES (Crop Estimation through Resource and Environment Synthesis)-Maize Model
Agronomy 2019, 9(2), 109; https://doi.org/10.3390/agronomy9020109
Received: 26 January 2019 / Revised: 11 February 2019 / Accepted: 20 February 2019 / Published: 25 February 2019
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Abstract
Summer maize (Zea mays L.) is a widely cultivated crop in the arid and semi-arid Guanzhong region of China. However, due to the spatial and temporal variation in rainfall, the seasonal maize yield varies substantially and occasionally is not economical for poor [...] Read more.
Summer maize (Zea mays L.) is a widely cultivated crop in the arid and semi-arid Guanzhong region of China. However, due to the spatial and temporal variation in rainfall, the seasonal maize yield varies substantially and occasionally is not economical for poor farmers to produce. Recent water-saving agricultural practices were developed by the government to make it possible to apply supplementary irrigation at optimum sowing dates to maximize maize production under limited rainfall in the region. CERES (Crop Estimation through Resource and Environment Synthesis)-maize model was used to identify the appropriate irrigation strategies, crop growth stages and sowing dates for sustainable maize production. Model calibration process were carried out for full irrigation treatments of four growing seasons, (2012–2015). The data used for calibration included: Crop phenology, grain yield, aboveground biomass and leaf area index. The calibration phase model showed good agreement between simulated and observed values, with normalized root mean square error (nRMSE) ranging from 4.51% to 14.5%. The performance of the calibrated model was evaluated using the field data of grain yield, aboveground biomass, leaf area index and water use efficiency. The performance of the model during evaluation was satisfactory with acceptable nRMSE error ranging from 7% to 10%. Soil moisture content was evaluated for full irrigation treatments for both 2012 and 2013 seasons. With results showing that soil moisture content below 35 cm layer was well simulated with nRMSE, 0.57 to 0.86 respectively. Appropriate simulated sowing dates for higher production and water productivity were from 14 to 24 June. The proper amount and timing of irrigation water application was 100 mm at the flowering stage, and 100 mm at the grain filling stage respectively. Summer maize yield can be improved by adjusting the sowing date and applying supplementary irrigation when precipitation cannot meet the crop water demand in the Guanzhong Plain. Full article
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Open AccessArticle Using Neural Networks to Estimate Site-Specific Crop Evapotranspiration with Low-Cost Sensors
Agronomy 2019, 9(2), 108; https://doi.org/10.3390/agronomy9020108
Received: 31 December 2018 / Revised: 14 February 2019 / Accepted: 19 February 2019 / Published: 23 February 2019
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Abstract
Irrigation efficiency is facilitated by matching irrigation rates to crop water demand based on estimates of actual evapotranspiration (ET). In production settings, monitoring of water demand is typically accomplished by measuring reference ET rather than actual ET, which is then adjusted approximately using [...] Read more.
Irrigation efficiency is facilitated by matching irrigation rates to crop water demand based on estimates of actual evapotranspiration (ET). In production settings, monitoring of water demand is typically accomplished by measuring reference ET rather than actual ET, which is then adjusted approximately using simplified crop coefficients based on calendars of crop maturation. Methods to determine actual ET are usually limited to use in research experiments for reasons of cost, labor and requisite user skill. To pair monitoring and research methods, we co-located eddy covariance sensors with on-farm weather stations over two different irrigated crops (vegetable beans and hazelnuts). Neural networks were used to train a neural network and utilize on-farm weather sensors to report actual ET as measured by the eddy covariance method. This approach was able to robustly estimate ET from as few as four sensor parameters (temperature, solar radiation, humidity and wind speed) with training time as brief as one week. An important limitation found with this machine learning method is that the trained network is only valid under environmental and crop conditions similar to the training period. The small number of required sensors and short training times demonstrate that this approach can estimate site-specific and crop specific ET. With additional field validation, this approach may offer a new method to monitor actual crop water demand for irrigation management. Full article
(This article belongs to the Special Issue Crop Evapotranspiration)
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Open AccessArticle Optimizing Crop Load for New Apple Cultivar: “WA38”
Agronomy 2019, 9(2), 107; https://doi.org/10.3390/agronomy9020107
Received: 24 January 2019 / Revised: 15 February 2019 / Accepted: 17 February 2019 / Published: 22 February 2019
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Abstract
Crop load management is growing increasingly important as a factor related to biennial tendencies, post-harvest disorders, and inconsistent fruit quality in apples like “Honeycrisp”. Washington State University released a new apple cultivar, called “WA38”, in 2017. Limited literature is available about the productive [...] Read more.
Crop load management is growing increasingly important as a factor related to biennial tendencies, post-harvest disorders, and inconsistent fruit quality in apples like “Honeycrisp”. Washington State University released a new apple cultivar, called “WA38”, in 2017. Limited literature is available about the productive characteristics of this new cultivar. An experimental trial evaluating the effect of crop load on leaf area, fruit quality, mineral composition, and return bloom of “WA38” was conducted for two consecutive years (2017 and 2018) to determine an optimal crop load. Trees were trained as a spindle and grafted on Malling-9 Nic29 (Nic29) rootstocks. Crop loads were adjusted to 2, 4, 6, and 8 fruits/cm2 of trunk cross-sectional area (TCSA). Crop load had a significant effect on production, with yields ranging from 28 to 83 MT/ha in 2017. Fruit quality was impacted by increasing crop load, with a reduction in fruit weight, soluble solid content, firmness, dry matter, titratable acidity, and a delay in maturity. Leaf-to-fruit ratios were higher in lower crop loads. Relatively consistent flower bud formation was seen at the 6 and 8 fruits/cm2 categories. A possible threshold for optimal fruit quality and consistent bloom was identified around 6 fruits/cm2 TCSA. Full article
(This article belongs to the Section Horticultural and Floricultural Crops)
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Open AccessArticle Development of Chlorophyll-Meter-Index-Based Dynamic Models for Evaluation of High-Yield Japonica Rice Production in Yangtze River Reaches
Agronomy 2019, 9(2), 106; https://doi.org/10.3390/agronomy9020106
Received: 28 January 2019 / Revised: 15 February 2019 / Accepted: 20 February 2019 / Published: 22 February 2019
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Abstract
Accurate estimation of the nitrogen (N) spatial distribution of rice (Oryza sativa L.) is imperative when it is sought to maintain regional and global carbon balances. We systematically evaluated the normalized differences of the soil and plant analysis development (SPAD) index (the [...] Read more.
Accurate estimation of the nitrogen (N) spatial distribution of rice (Oryza sativa L.) is imperative when it is sought to maintain regional and global carbon balances. We systematically evaluated the normalized differences of the soil and plant analysis development (SPAD) index (the normalized difference SPAD indexes, NDSIs) between the upper (the first and second leaves from the top), and lower (the third and fourth leaves from the top) leaves of Japonica rice. Four multi-location, multi-N rate (0–390 kg ha−1) field experiments were conducted using seven Japonica rice cultivars (9915, 27123, Wuxiangjing14, Wunyunjing19, Wunyunjing24, Liangyou9, and Yongyou8). Growth analyses were performed at different growth stages ranging from tillering (TI) to the ripening period (RP). We measured leaf N concentration (LNC), the N nutrition index (NNI), the NDSI, and rice grain yield at maturity. The relationships among the NDSI, LNC, and NNI at different growth stages showed that the NDSI values of the third and fourth fully expanded leaves more reliably reflected the N nutritional status than those of the first and second fully expanded leaves (LNC: NDSIL3,4, R2 > 0.81; NDSIothers, 0.77 > R2 > 0.06; NNI: NDSIL3,4, R2 > 0.83; NDSIothers, 0.76 > R2 > 0.07; all p < 0.01). Two new diagnostic models based on the NDSIL3,4 (from the tillering to the ripening period) can be used for effective diagnosis of the LNC and NNI, which exhibited reasonable distributions of residuals (LNC: relative root mean square error (RRMSE) = 0.0683; NNI: RRMSE = 0.0688; p < 0.01). The relationship between grain yield, predicted yield, and NDSIL3,4 were established during critical growth stages (from the stem elongation to the heading stages; R2 = 0.53, p < 0.01, RRMSE = 0.106). An NDSIL3,4 high-yield change curve was drawn to describe critical NDSIL3,4 values for a high-yield target (10.28 t ha−1). Furthermore, dynamic-critical curve models based on the NDSIL3,4 allowed a precise description of rice N status, facilitating the timing of fertilization decisions to optimize yields in the intensive rice cropping systems of eastern China. Full article
(This article belongs to the Special Issue Remote Sensing Applications for Agriculture and Crop Modelling)
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Open AccessArticle Microbial Consortia versus Single-Strain Inoculants: An Advantage in PGPM-Assisted Tomato Production?
Agronomy 2019, 9(2), 105; https://doi.org/10.3390/agronomy9020105
Received: 26 January 2019 / Revised: 6 February 2019 / Accepted: 18 February 2019 / Published: 22 February 2019
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Abstract
The use of biostimulants with plant growth-promoting properties, but without significant input of nutrients, is discussed as a strategy to increase stress resistance and nutrient use efficiency of crops. However, limited reproducibility under real production conditions remains a major challenge. The use of [...] Read more.
The use of biostimulants with plant growth-promoting properties, but without significant input of nutrients, is discussed as a strategy to increase stress resistance and nutrient use efficiency of crops. However, limited reproducibility under real production conditions remains a major challenge. The use of combination products based on microbial and non-microbial biostimulants or microbial consortia, with the aim to exploit complementary or synergistic interactions and increase the flexibility of responses under different environmental conditions, is discussed as a potential strategy to overcome this problem. This study aimed at comparing the efficiency of selected microbial single-strain inoculants with proven plant-growth promoting potential versus consortium products under real production conditions in large-scale tomato cultivation systems, exposed to different environmental challenges. In a protected greenhouse production system at Timisoara, Romania, with composted cow manure, guano, hair-, and feather-meals as major fertilizers, different fungal and bacterial single-strain inoculants, as well as microbial consortium products, showed very similar beneficial responses. Nursery performance, fruit setting, fruit size distribution, seasonal yield share, and cumulative yield (39–84% as compared to the control) were significantly improved over two growing periods. By contrast, superior performance of the microbial consortia products (MCPs) was recorded under more challenging environmental conditions in an open-field drip-fertigated tomato production system in the Negev desert, Israel with mineral fertilization on a high pH (7.9), low fertility, and sandy soil. This was reflected by improved phosphate (P) acquisition, a stimulation of vegetative shoot biomass production and increased final fruit yield under conditions of limited P supply. Moreover, MCP inoculation was associated with selective changes of the rhizosphere-bacterial community structure particularly with respect to Sphingobacteriia and Flavobacteria, reported as salinity indicators and drought stress protectants. Phosphate limitation reduced the diversity of bacterial populations at the root surface (rhizoplane) and this effect was reverted by MCP inoculation, reflecting the improved P status of the plants. The results support the hypothesis that the use of microbial consortia can increase the efficiency and reproducibility of BS-assisted strategies for crop production, particularly under challenging environmental conditions. Full article
(This article belongs to the Special Issue Plant Mineral Nutrition: Principles and Perspectives)
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Open AccessArticle Optimization of Offshoot Outgrowth in Globe Artichoke Using a Combination of Chemical and Mechanical Treatments
Agronomy 2019, 9(2), 104; https://doi.org/10.3390/agronomy9020104
Received: 7 January 2019 / Revised: 5 February 2019 / Accepted: 19 February 2019 / Published: 22 February 2019
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Abstract
The application of cytokinins is a good tool to promote axillary buds in many species, but plant decapitation or leaf cut-back are also suitable methods. This research aims to establish a strategy for artichoke cutting production using a combination of chemical and mechanical [...] Read more.
The application of cytokinins is a good tool to promote axillary buds in many species, but plant decapitation or leaf cut-back are also suitable methods. This research aims to establish a strategy for artichoke cutting production using a combination of chemical and mechanical treatments. Two experiments were conducted in Tunisia to investigate the effect of 6-benzylamino purine (BAP) on shoot outgrowth in globe artichoke combined with the leaf cut-back at collar level one week after BAP treatment. The first trial was tested in a spring offshoot nursery and the second one in a field of micro-propagated mother plants grown for two years. Five treatments were tested in both experiments: BAP 0 ppm + no cut-back (T1), BAP 0, 100, 200, and 300 ppm + cut-back (T2, T3, T4, and T5 respectively). Regarding growth aspects, the highest number of offshoots was obtained in T4 for both trials with an increase of 49.2% and 37.8% compared to T2 nursery and field values, respectively. T4 also showed a faster rhythm of shoot emission and the biggest shoot size compared to the other treatments. Significant interactions between BAP treatments and offshoot size were recorded for morphological and weight parameters. Regarding the offshoot mineral composition, relevant differences were observed among BAP treatments; moreover, the higher BAP concentrations induced a significant decrease of NaCl plant uptake. Therefore, the combination of BAP 200 ppm and the leaf cut-back could be a potential method to enlarge the cutting production of globe artichoke also reducing some stressful conditions. Full article
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Open AccessArticle Effect of the Intensity of Weed Harrowing with Spike-Tooth Harrow in Barley-Pea Mixture on Yield and Mycobiota of Harvested Grains
Agronomy 2019, 9(2), 103; https://doi.org/10.3390/agronomy9020103
Received: 30 January 2019 / Revised: 20 February 2019 / Accepted: 21 February 2019 / Published: 21 February 2019
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Abstract
Harrowing is one of the most popular mechanical methods to control weeds. Nevertheless, the relationship between the effect of different harrowing intensities using spike-tooth harrow in barley-pea intercrop on the yield and mycoflora of grains has not yet been studied. Therefore, the aim [...] Read more.
Harrowing is one of the most popular mechanical methods to control weeds. Nevertheless, the relationship between the effect of different harrowing intensities using spike-tooth harrow in barley-pea intercrop on the yield and mycoflora of grains has not yet been studied. Therefore, the aim of this study was to assess the effect of harrow intensity using spike-tooth harrow in barley-pea mixture on the mycological quality of harvested grains, grain yield, as well as influence of barley and pea grain moisture on the abundance of fungi. The field experiment was carried out during 2010–2012, and it was conducted using a randomized complete block design with four replicates. Weed control was mechanical and chemical. In this study, we have shown that harrowing in barley-pea intercrops does not reduce the yield of either mixture components, both with respect to grain quantity or mycological quality after harvest, compared to controls—without harrowing and the herbicide MCPA (2-methyl-4-chlorophenoxyacetic acid). However, increasing the intensity of harrowing did not result in a consistently larger crop yield or reduction in fungal abundance in the grains. The grains’ internal structures and surface of both tested components of the mixture were colonized to a large extent by cosmopolitan fungi, of which Alternaria alternata (Fr.) Keissl. was the most abundant. Full article
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Open AccessArticle 3,4-Dimethylpyrazole Phosphate (DMPP) Reduces N2O Emissions from a Tilled Grassland in the Bogotá Savanna
Agronomy 2019, 9(2), 102; https://doi.org/10.3390/agronomy9020102
Received: 15 January 2019 / Revised: 10 February 2019 / Accepted: 19 February 2019 / Published: 21 February 2019
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Abstract
Grasslands are subject to a wide range of land management practices that influence the exchange of the three main agricultural greenhouse gases (GHGs) that are related to agriculture: carbon dioxide (CO2), nitrous oxide (N2O), and methane (CH4). [...] Read more.
Grasslands are subject to a wide range of land management practices that influence the exchange of the three main agricultural greenhouse gases (GHGs) that are related to agriculture: carbon dioxide (CO2), nitrous oxide (N2O), and methane (CH4). Improving nitrogen fertilization management practices through the use of nitrification inhibitors (NIs) can reduce GHGs emissions. We conducted a field experiment at the Colombian Agricultural Research Corporation with four fertilization treatments: urea (typical fertilizer used in this region), ammonium sulfate nitrate (ASN), ASN plus the NI 3,4-dimethylpyrazole phosphate (ASN+DMPP), and an unfertilized control. The highest grassland yields (1956 and 2057 kg DM ha−1, respectively) and apparent fertilizer nitrogen recoveries (34% and 33%, respectively) were generated by the conventional urea fertilizer and ASN+DMPP. Furthermore, the use of ASN+DMPP reduced the N2O emissions that were related to N fertilization to the level of the unfertilized treatment (ca. 1.5 g N2O-N ha−1), with a significant reduction of N-yield-scaled N2O emissions (ca. 20 g N2O-N kg N uptake−1). These results support the application of DMPP as an alternative strategy to increase grassland yield while simultaneously reducing the environmental impact of N fertilization. Full article
(This article belongs to the Special Issue Strategies for Greenhouse Gas Emissions Mitigation)
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Open AccessArticle Livestock Performance for Sheep and Cattle Grazing Lowland Permanent Pasture: Benchmarking Potential of Forage-Based Systems
Agronomy 2019, 9(2), 101; https://doi.org/10.3390/agronomy9020101
Received: 29 January 2019 / Revised: 15 February 2019 / Accepted: 18 February 2019 / Published: 21 February 2019
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Abstract
Here we describe the livestock performance and baseline productivity over a two-year period, following the establishment of the infrastructure on the North Wyke Farm Platform across its three farmlets (small farms). Lowland permanent pastures were continuously stocked with yearling beef cattle and ewes [...] Read more.
Here we describe the livestock performance and baseline productivity over a two-year period, following the establishment of the infrastructure on the North Wyke Farm Platform across its three farmlets (small farms). Lowland permanent pastures were continuously stocked with yearling beef cattle and ewes and their twin lambs for two years in three farmlets. The cattle came into the farmlets as suckler-reared weaned calves at 195 ± 32.6 days old weighing 309 ± 45.0 kg, were housed indoors for 170 days then turned out to graze weighing 391 ± 54.2 kg for 177 days. Therefore, it is suggested for predominantly grass-based systems with minimal supplementary feeding that target live weight gains should be 0.5 kg/day in the first winter, 0.9 kg/day for summer grazing and 0.8 kg/day for cattle housed and finished on silage in a second winter. The sheep performance suggested that lambs weaned at 100 days and weighing 35 kg should finish at 200 days weighing 44 to 45 kg live weight with a killing out percentage of 44%. Good levels of livestock production are possible with grass and forage-based systems using little or no additional supplementary concentrate feeds. Full article
(This article belongs to the Section Grassland and Pasture Science)
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Open AccessArticle Evaluation of Evapotranspiration from Eddy Covariance Using Large Weighing Lysimeters
Received: 31 December 2018 / Revised: 12 February 2019 / Accepted: 14 February 2019 / Published: 20 February 2019
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Abstract
Evapotranspiration (ET) is an important component in the water budget and used extensively in water resources management such as water planning and irrigation scheduling. In semi-arid regions, irrigation is used to supplement limited and erratic growing season rainfall to meet crop water demand. [...] Read more.
Evapotranspiration (ET) is an important component in the water budget and used extensively in water resources management such as water planning and irrigation scheduling. In semi-arid regions, irrigation is used to supplement limited and erratic growing season rainfall to meet crop water demand. Although lysimetery is considered the most accurate method for crop water use measurements, high-precision weighing lysimeters are expensive to build and operate. Alternatively, other measurement systems such as eddy covariance (EC) are being used to estimate crop water use. However, due to numerous explicit and implicit assumptions in the EC method, an energy balance closure problem is widely acknowledged. In this study, three EC systems were installed in a field containing a large weighing lysimeter at heights of 2.5, 4.5, and 8.5 m. Sensible heat flux (H) and ET from each EC system were evaluated against the lysimeter. Energy balance closure ranged from 64% to 67% for the three sensor heights. Results showed that all three EC systems underestimated H and consequently overestimated ET; however, the underestimation of H was greater in magnitude than the overestimation of ET. Analysis showed accuracy of ET was greater than energy balance closure with error rates of 20%–30% for half-hourly values. Further analysis of error rates throughout the growing season showed that energy balance closure and ET accuracy were greatest early in the season and larger error was found after plants reached their maximum height. Therefore, large errors associated with increased biomass may indicate unaccounted-for energy stored in the plant canopy as one source of error. Summing the half-hourly data to a daily time-step drastically reduced error in ET to 10%–15%, indicating that EC has potential for use in agricultural water management. Full article
(This article belongs to the Special Issue Crop Evapotranspiration)
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Open AccessArticle Effect of Irrigation Regimes and Soil Texture on the Potassium Utilization Efficiency of Rice
Agronomy 2019, 9(2), 100; https://doi.org/10.3390/agronomy9020100
Received: 4 January 2019 / Revised: 2 February 2019 / Accepted: 18 February 2019 / Published: 20 February 2019
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Abstract
Understanding the effects of irrigation regime and soil texture on potassium-use efficiency (KUE) of rice (Oryza sativa. L) is essential for improving rice productivity. In this regard, experiments were conducted from July to October in 2016 and 2017 by using a [...] Read more.
Understanding the effects of irrigation regime and soil texture on potassium-use efficiency (KUE) of rice (Oryza sativa. L) is essential for improving rice productivity. In this regard, experiments were conducted from July to October in 2016 and 2017 by using a randomized complete block design in a factorial arrangement with four replications. The rice plants were grown in three soils, with clay contents of 40%, 50%, and 60%, which were marked as S (40%), S (50%), and S (60%), respectively. For each soil type, irrigation regimes, namely, R (F, S100%), R (F, S90%), and R (F, S70%), were established by setting the lower limit of irrigation to 100%, 90%, and 70% of saturated soil water content, respectively, and the upper limit of irrigation with 30 mm of flooding water above the soil surface for all irrigation regimes. Results showed that the responses of the roots and shoots and the potassium accumulation (KA) and KUE of rice were significantly affected by the water regime and soil texture. In the same irrigation regime, increasing the soil clay content improved the K utilization of rice. Under the same soil type, R (F, S100%) was the optimal water management practice for growing rice. The R (F, S100%) S (60%) treatment presented the highest KUE, which was 56.4% in 2016 and 68.1% in 2017. The R (F, S70%) S (40%) treatment showed the lowest KUE, which was 13.8% in 2016 and 14.9% in 2017. These results enrich knowledge regarding the relationship among soil, water, and rice, and provide valuable insights on the effect of irrigation regime and soil texture on the KA and KUE of rice. Full article
(This article belongs to the Section Water Use and Irrigation)
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Open AccessArticle Szarvasi-1 and Its Potential to Become a Substitute for Maize Which Is Grown for the Purposes of Biogas Plants in the Czech Republic
Received: 21 January 2019 / Revised: 11 February 2019 / Accepted: 17 February 2019 / Published: 19 February 2019
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Abstract
The domestic biogas market has been developing rapidly, and legislation (The Act) supporting the use of renewable energy sources has come into force. In light of this act and investment support from national programs co-financed by the European Union (EU), the total number [...] Read more.
The domestic biogas market has been developing rapidly, and legislation (The Act) supporting the use of renewable energy sources has come into force. In light of this act and investment support from national programs co-financed by the European Union (EU), the total number of biogas plants has recently increased from a few to 600. The total capacity of electricity generation of those 600 installed plants exceeds 360 Megawatts (MW) (as of mid-2018). Such dynamic growth is expected to continue, and the targets of the National Renewable Energy Action Plan are projected to be met. The use of waste material, which was urgently needed, was the original aim of biogas plants. However, in certain cases, the original purpose has transformed, and phytomass is very often derived from purpose-grown energy crops. Maize is the most common and widely grown energy crop in the Czech Republic. Nevertheless, maize production raises several environmental issues. One way to potentially reduce maize’s harmful effects is to replace it with other suitable crops. Perennial energy crops, for example, are possible alternatives to maize. A newly introduced species for the conditions of the Czech Republic, Elymus elongatus subsp. ponticus cv. Szarvasi-1, and some other well-known species—Phalaris arundinacea L. and Miscanthus × giganteus—are suitable for Czech Republic climate conditions. This paper presents the findings of the research and evaluation of environmental, energy-related, and economic aspects of growing these crops for use in biogas plants. These findings are based on 5-year small-plot field trials. The energy-related aspects of producing Elymus elongatus subsp. ponticus cv. Szarvasi-1, Phalaris arundinacea L., and Miscanthus x giganteus are reported on the basis of experiments that included measuring the real methane yield from a production unit. The economic analysis is based on a model of every single growing and technological operation and costs. The environmental burden of the individual growing methods was assessed with a simplified life cycle assessment (LCA) using the impact category of Climate Change and the SimaPro 8.5.2.0 software tool, including an integrated method called ReCiPe. The research findings show that Szarvasi-1 produces 5.7–6.7 Euros (EUR) per Gigajoule (GJ) of energy, depending on the growing technology used. Szarvasi-1 generates an average energy profit of 101.4 GJ ha−1, which is half of that produced by maize (214.1 GJ ha−1). The environmental burden per energy unit of maize amounts to 16 kg of carbon dioxide eq GJ−1 compared with the environmental burden per energy unit of Szarvasi-1, which amounts to 7.2–15.6 kg of CO2 eq GJ−1, depending on the yield rate. On the basis of the above-mentioned yield rate of Szarvasi-1, it cannot be definitively recommended for the purpose of biogas plants in the Czech Republic. Full article
(This article belongs to the Special Issue Forage and Bioenergy Crops)
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Open AccessArticle Effect of Vermicompost Application on Bioactive Properties and Antioxidant Potential of MD2 Pineapple Fruits
Received: 25 January 2019 / Revised: 13 February 2019 / Accepted: 14 February 2019 / Published: 19 February 2019
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Abstract
Vermicompost is an organic waste produced from earthworms that can enhance the soil condition and is rich with essential plant nutrients, thus increasing produce quality and shelf life. In this study, a one-year field trial was conducted to elucidate the effects of vermicompost [...] Read more.
Vermicompost is an organic waste produced from earthworms that can enhance the soil condition and is rich with essential plant nutrients, thus increasing produce quality and shelf life. In this study, a one-year field trial was conducted to elucidate the effects of vermicompost supplementation on the composition of bioactive compounds and antioxidant activities of pineapple (Ananas comosus var. MD2) fruits, compared to control and application of chemical fertilizer. Based on the results, pineapple fruits produced from plants supplemented with chemical fertilizer showed the strongest radical scavenging properties against 2,2-Diphenyl-1-picrylhydrazyl (DPPH) and 2,2′-azinobis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS), followed by vermicompost and control plants. Application of chemical fertilizer and vermicompost also produced fruits with a very high content of chlorophylls and β-carotene compared to control plants. However, the amounts of bioactive compounds present in fruits produced with chemical fertilizer are higher than in fruits produced with vermicompost. Total phenolics content and Ferric Reducing Antioxidant Power (FRAP) reducing power were lowest in fruit extracts produced from pineapple plants supplemented with vermicompost. These results suggested that vermicompost cannot completely replace chemical fertilizer for the production of fruits with a high content of phytoconstituents but could be used as an additional supplement to reduce environmental pollution and ensure agricultural sustainability. Full article
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Open AccessArticle An Automated Plot Heater for Field Frost Research in Cereals
Received: 23 January 2019 / Revised: 12 February 2019 / Accepted: 13 February 2019 / Published: 19 February 2019
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Abstract
Frost research to improve genetics or management solutions requires a robust experimental design that minimizes the effects of all other variables that can cause plant damage except for the treatment (frost). Controlled environment facilities cannot faithfully replicate field radiative frost processes, but field [...] Read more.
Frost research to improve genetics or management solutions requires a robust experimental design that minimizes the effects of all other variables that can cause plant damage except for the treatment (frost). Controlled environment facilities cannot faithfully replicate field radiative frost processes, but field studies are limited by the reliability of field methods to exclude frost. An effective field frost exclusion method needs to prevent frost damage while not impacting growing microclimate or yield, and be automatic, modular, mobile, and affordable. In this study, we designed an effective prototype treatment with these features for field frost research that uses diesel heating. The effectiveness of the plot heater to provide an unfrosted control is evaluated by monitoring canopy temperature (CT) and air temperature during frost events, showing that these remain above zero in the heated plots when ambient temperature drops below zero. We find that the plot heater method can prevent potential frost damage at the plot-scale, while not appearing to have an impact on either plant development or yield components. This offers a potential new tool for frost field crop researchers to incorporate a plot-scale control into their experimental design. Full article
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Open AccessReview Genomic Selection in Cereal Breeding
Received: 21 December 2018 / Revised: 13 February 2019 / Accepted: 14 February 2019 / Published: 19 February 2019
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Abstract
Genomic Selection (GS) is a method in plant breeding to predict the genetic value of untested lines based on genome-wide marker data. The method has been widely explored with simulated data and also in real plant breeding programs. However, the optimal strategy and [...] Read more.
Genomic Selection (GS) is a method in plant breeding to predict the genetic value of untested lines based on genome-wide marker data. The method has been widely explored with simulated data and also in real plant breeding programs. However, the optimal strategy and stage for implementation of GS in a plant-breeding program is still uncertain. The accuracy of GS has proven to be affected by the data used in the GS model, including size of the training population, relationships between individuals, marker density, and use of pedigree information. GS is commonly used to predict the additive genetic value of a line, whereas non-additive genetics are often disregarded. In this review, we provide a background knowledge on genomic prediction models used for GS and a view on important considerations concerning data used in these models. We compare within- and across-breeding cycle strategies for implementation of GS in cereal breeding and possibilities for using GS to select untested lines as parents. We further discuss the difference of estimating additive and non-additive genetic values and its usefulness to either select new parents, or new candidate varieties. Full article
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Open AccessArticle Description and Preliminary Simulations with the Italian Vineyard Integrated Numerical Model for Estimating Physiological Values (IVINE)
Received: 23 December 2018 / Revised: 11 February 2019 / Accepted: 14 February 2019 / Published: 18 February 2019
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Abstract
The numerical crop growth model Italian Vineyard Integrated Numerical model for Estimating physiological values (IVINE) was developed in order to evaluate environmental forcing effects on vine growth. The IVINE model simulates vine growth processes with parameterizations, allowing the understanding of plant conditions at [...] Read more.
The numerical crop growth model Italian Vineyard Integrated Numerical model for Estimating physiological values (IVINE) was developed in order to evaluate environmental forcing effects on vine growth. The IVINE model simulates vine growth processes with parameterizations, allowing the understanding of plant conditions at a vineyard scale. It requires a set of meteorology data and soil water status as boundary conditions. The primary model outputs are main phenological stages, leaf development, yield, and sugar concentration. The model requires setting some variety information depending on the cultivar: At present, IVINE is optimized for Vitis vinifera L. Nebbiolo, a variety grown mostly in the Piedmont region (northwestern Italy). In order to evaluate the model accuracy, IVINE was validated using experimental observations gathered in Piedmontese vineyards, showing performances similar or slightly better than those of other widely used crop models. The results of a sensitivity analysis performed to highlight the effects of the variations of air temperature and soil water potential input variables on IVINE outputs showed that most phenological stages anticipated with increasing temperatures, while berry sugar content saturated at about 25.5 °Bx. Long-term (60 years, in the period 1950–2009) simulations performed over a Piedmontese subregion showed statistically significant variations of most IVINE output variables, with larger time trend slopes referring to the most recent 30-year period (1980–2009), thus confirming that ongoing climate change started influencing Piedmontese vineyards in 1980. Full article
(This article belongs to the Special Issue Viticulture and Winemaking under Climate Change)
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Open AccessArticle Morphological and Biochemical Responses of Glycine max (L.) Merr. to the Use of Seaweed Extract
Received: 21 December 2018 / Revised: 14 February 2019 / Accepted: 15 February 2019 / Published: 18 February 2019
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Abstract
Currently, modern agriculture aims to improve the quantity and quality of crop yield, while minimizing the negative impact of treatments on the natural environment. One of the methods to increase plant yield and quality, especially after the occurrence of both abiotic or biotic [...] Read more.
Currently, modern agriculture aims to improve the quantity and quality of crop yield, while minimizing the negative impact of treatments on the natural environment. One of the methods to increase plant yield and quality, especially after the occurrence of both abiotic or biotic stress factors, is the application of biostimulants. The aim of the study was to determine the effect of Ecklonia maxima extract on plant growth, and the yield, nutritional, and nutraceutical properties of soybean seeds. A field experiment was conducted in three growing seasons (2014–2016). Soybean seeds of Atlanta cultivar were sown in the third 10-day period of April. Ecklonia maxima extract was applied in the form of single or double, spraying in the concentrations of 0.7% and 1.0%. Determinations were conducted for: biometric traits, seed yield, seed number, thousand seeds weight, contents of lipids, and proteins in seeds. Further analyses included the contents of total polyphenols, flavonoids, anthocyanins, and reducing power. The number of seaweed extract applications and its concentration modified biometric traits, yield, and quality of crop, while also also altering the nutraceutical and antioxidative potential of soybean. The application of this preparation improved the growth and yield of soybean without any negative effect on the nutritive value of seeds. Full article
Open AccessArticle Selection of Salicylic Acid Tolerant Epilines in Brassica napus
Received: 21 December 2018 / Revised: 18 January 2019 / Accepted: 14 February 2019 / Published: 18 February 2019
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Abstract
Two of the major pathways involved in induced defense of plants against pathogens include the salicylic acid (SA)- and jasmonic acid (JA)-mediated pathways that act mainly against biotrophs and necrotrophs, respectively. However, some necrotrophic pathogens, such as Botrytis cinerea, actively induce the [...] Read more.
Two of the major pathways involved in induced defense of plants against pathogens include the salicylic acid (SA)- and jasmonic acid (JA)-mediated pathways that act mainly against biotrophs and necrotrophs, respectively. However, some necrotrophic pathogens, such as Botrytis cinerea, actively induce the SA pathway, resulting in cell death that allows the pathogen to proliferate in the plant. Starting from an isogenic canola (Brassica napus) line, epilines were selected with a reduced sensitivity to SA. The genes belonging to the SA pathway had an altered transcription profile in the SA-tolerant lines, when treated with SA. Besides the already known genes of the SA pathway, new SA target genes were identified, creating possibilities to better understand the plant defense mechanism against pathogens. The SA-tolerant line with the lowest SA-induced gene expression is tolerant to Botrytis cinerea. When treated with SA, this line has also a reduced histone modification (histone H3 lysine 4 trimethylation) at the genes at the start of the SA pathway. Full article
(This article belongs to the Special Issue The Regulatory Functions of Epigenetic Mechanisms in Plants)
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Open AccessArticle Unsupervised Greenhouse Tomato Plant Segmentation Based on Self-Adaptive Iterative Latent Dirichlet Allocation from Surveillance Camera
Received: 16 January 2019 / Accepted: 1 February 2019 / Published: 16 February 2019
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Abstract
It has long been a great concern in deep learning that we lack massive data for high-precision training sets, especially in the agriculture field. Plants in images captured in greenhouses, from a distance or up close, not only have various morphological structures but [...] Read more.
It has long been a great concern in deep learning that we lack massive data for high-precision training sets, especially in the agriculture field. Plants in images captured in greenhouses, from a distance or up close, not only have various morphological structures but also can have a busy background, leading to huge challenges in labeling and segmentation. This article proposes an unsupervised statistical algorithm SAI-LDA (self-adaptive iterative latent Dirichlet allocation) to segment greenhouse tomato images from a field surveillance camera automatically, borrowing the language model LDA. Hierarchical wavelet features with an overlapping grid word document design and a modified density-based method quick-shift are adopted, respectively, according to different kinds of images, which are classified by specific proportions between fruits, leaves, and the background. We also utilize the feature correlation between several layers of the image to make further optimization through three rounds of iteration of LDA, with updated documents to achieve finer segmentation. Experiment results show that our method can automatically label the organs of the greenhouse plant under complex circumstances, fast and precisely, overcoming the difficulty of inferior real-time image quality caused by a surveillance camera, and thus obtain large amounts of valuable training sets. Full article
(This article belongs to the Section Horticultural and Floricultural Crops)
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Open AccessArticle Estimating Body Condition Score in Dairy Cows From Depth Images Using Convolutional Neural Networks, Transfer Learning and Model Ensembling Techniques
Received: 28 December 2018 / Revised: 5 February 2019 / Accepted: 12 February 2019 / Published: 16 February 2019
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Abstract
BCS (Body Condition Score) is a method to estimate body fat reserves and accumulated energy balance of cows, placing estimations (or BCS values) in a scale of 1 to 5. Periodically rating BCS of dairy cows is very important since BCS values are [...] Read more.
BCS (Body Condition Score) is a method to estimate body fat reserves and accumulated energy balance of cows, placing estimations (or BCS values) in a scale of 1 to 5. Periodically rating BCS of dairy cows is very important since BCS values are associated with milk production, reproduction, and health of cows. However, in practice, obtaining BCS values is a time-consuming and subjective task performed visually by expert scorers. There have been several efforts to automate BCS of dairy cows by using image analysis and machine learning techniques. In a previous work, an automatic system to estimate BCS values was proposed, which is based on Convolutional Neural Networks (CNNs). In this paper we significantly extend the techniques exploited by that system via using transfer learning and ensemble modeling techniques to further improve BCS estimation accuracy. The improved system has achieved good estimations results in comparison with the base system. Overall accuracy of BCS estimations within 0.25 units of difference from true values has increased 4% (up to 82%), while overall accuracy within 0.50 units has increased 3% (up to 97%). Full article
(This article belongs to the Special Issue Deep Learning Techniques for Agronomy Applications)
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Open AccessArticle Soil Amendment with Raw Garlic Stalk: A Novel Strategy to Stimulate Growth and the Antioxidative Defense System in Monocropped Eggplant in the North of China
Received: 24 January 2019 / Revised: 12 February 2019 / Accepted: 13 February 2019 / Published: 15 February 2019
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Abstract
Garlic (Allium Sativum L.) is a vegetable with known medicinal value. It is not only rich in nutrients, but also has the ability to combat different microbial infections. This is, however, the first study to investigate the effect of soil incorporation of [...] Read more.
Garlic (Allium Sativum L.) is a vegetable with known medicinal value. It is not only rich in nutrients, but also has the ability to combat different microbial infections. This is, however, the first study to investigate the effect of soil incorporation of the raw garlic stalk (RGS) on the growth and antioxidative defense system of eggplant. The experiments were conducted in pots using soil amendments of RGS in different ratios (RGS1 1:100; RGS2 3:100; RGS3 5:100 and control (CK) 0:100 of RGS: Soil w/w) and repeated in two consecutive years (2016 and 2017). A dose-dependent response of RGS amendment was observed in the growth and physiology of the eggplant. RGS1 and RGS2 significantly enhanced the plant height, root/shoot weight, stem diameter, leaf area, root length, root activity, pigment contents (chlorophyll a, chlorophyll b, and total chlorophyll), and photosynthetic parameters, but reduced intracellular CO2 (Ci) and enhanced fruit yield as compared with the respective controls. Consistently, RGS also enhanced activities of antioxidative enzymes of eggplant reported as a defense against stress indicators. RGS in its higher ratios (RGS3), however, caused a reduction in all of the growth and physiological parameters and increased stress indicators such as hydrogen peroxide (H2O2) and malondialdehyde (MDA). Overall, RGS2 was found to be the most efficient for regulation of plant defense systems, reducing H2O2 and MDA and enhancing superoxide dismutase (SOD), peroxidase (POD), and phenylalanine ammonia–lyase (PAL) activity. It can be concluded that the appropriate ratio of RGS could efficiently promote plant growth and regulate the reactive oxygen-based plant defense system. Full article
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Open AccessArticle Aggressiveness and Fumonisins Production of Fusarium Subglutinans and Fusarium Temperatum on Korean Maize Cultivars
Received: 31 January 2019 / Revised: 11 February 2019 / Accepted: 12 February 2019 / Published: 15 February 2019
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Abstract
Fusarium root rot and stalk rot are becoming a threat to maize production worldwide. However, there is still limited information about the aggressiveness of Fusarium subglutinans Edwards and Fusarium temperatum and their relationship with fumonisin production. In this study, for the first time, [...] Read more.
Fusarium root rot and stalk rot are becoming a threat to maize production worldwide. However, there is still limited information about the aggressiveness of Fusarium subglutinans Edwards and Fusarium temperatum and their relationship with fumonisin production. In this study, for the first time, the reaction of seven Korean maize cultivars to F. subglutinans and F. temperatum was investigated. The results showed that among the maize cultivars, Hik-chal and Miheung-chal had the highest Fusarium-induced root rot and stalk rot severity, while De Hack-chal had the lowest disease severity regardless of the Fusarium species. Furthermore, the disease resistant cv. De Hack-chal accumulated low levels of fumonisins (FUM) in the infected stalk, while cv. Hik-chal and Miheung-chal had the highest level of FUM. It is worth to note that, plants infected with F. temperatum had a higher FUM concentration compared to cultivars infected with F. subglutinans. The present study shows a significant correlation between stalk rot ratings and FUM levels and it also presents new information about the potential risk of FUM contamination of maize stalk with F. subglutinans and F. temperatum in South Korea. In addition, enzyme activities like polyphenol oxidase (PPO), peroxidase (POD), and the amount of total phenol content (TPC) were studied in selected susceptible cultivar Miheung-chal and resistant cultivar De Hack-chal. The activity of PPO, POD and concentration of TPC were generally higher in the roots of the resistant cultivar than the susceptible cultivar. Moreover, following inoculation of either F. subglutinans or F. temperatum, there was a significant increase in PPO and POD activity in the roots of both cultivars. Hence, the information provided in this study could be helpful to better understand the mechanisms of resistance response to infection of Fusarium root rot pathogens. Full article
(This article belongs to the Special Issue Genetics and Genomics of Disease Resistance in Crops)
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Open AccessReview Agronomic Basis and Strategies for Precision Water Management: A Review
Received: 26 January 2019 / Revised: 9 February 2019 / Accepted: 11 February 2019 / Published: 14 February 2019
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Abstract
Agriculture faces the challenge of feeding a growing population with limited or depleting fresh water resources. Advances in irrigation systems and technologies allow site-specific application of irrigation water within the field to improve water use efficiency or reduce water usage for sustainable crop [...] Read more.
Agriculture faces the challenge of feeding a growing population with limited or depleting fresh water resources. Advances in irrigation systems and technologies allow site-specific application of irrigation water within the field to improve water use efficiency or reduce water usage for sustainable crop production, especially in arid and semi-arid regions. This paper discusses recent development of variable-rate irrigation (VRI) technologies, data and information for VRI application, and impacts of VRI, including profitability using this technology, with a focus on agronomic factors in precision water management. The development in sprinkler systems enabled irrigation application with greater precision at the scale of individual nozzle control. Further research is required to evaluate VRI prescription maps integrating different soil and crop characteristics in different environments. On-farm trials and whole-field studies are needed to provide support information for practical VRI applications. Future research also needs to address the adjustment of the spatial distribution of prescription zones in response to temporal variability in soil water status and crop growing conditions, which can be evaluated by incorporating remote and proximal sensing data. Comprehensive decision support tools are required to help the user decide where to apply how much irrigation water at different crop growth stages to optimize water use and crop production based on the regional climate conditions and cropping systems. Full article
(This article belongs to the Special Issue Agricultural Water Management)
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Open AccessArticle Effect of Large-Scale Cultivated Land Expansion on the Balance of Soil Carbon and Nitrogen in the Tarim Basin
Received: 23 January 2019 / Accepted: 12 February 2019 / Published: 14 February 2019
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Abstract
Land reclamation influences the soil carbon and nitrogen cycling, but its scale and time effects on the balance of soil carbon and nitrogen are still uncertain. Taking the Tarim Basin as the study area, the impact of land reclamation on the soil organic [...] Read more.
Land reclamation influences the soil carbon and nitrogen cycling, but its scale and time effects on the balance of soil carbon and nitrogen are still uncertain. Taking the Tarim Basin as the study area, the impact of land reclamation on the soil organic carbon (SOC), total nitrogen (TN), and carbon to nitrogen (C:N) ratio was explored by the multiple temporal changes of land use and soil samples. Remote sensing detected that cropland nearly doubled in area from 1978 to 2015. Spatial analysis techniques were used to identify land changes, including the prior land uses and cultivation ages. Using land reclamation history information, a specially designed soil sampling was conducted in 2015 and compared to soil properties in ca. 1978. Results found a decoupling characteristic between the C:N ratio and SOC or TN, indicating that changes in SOC and TN do not correspond directly to changes in the C:N ratio. The land reclamation history coupled with the baseline effect has opposite impacts on the temporal rates of change in SOC, TN and C:N ratios. SOC and TN decreased during the initial stage of conversion to cropland and subsequently recovered with increasing cultivation time. By contrast, the C:N ratio for soils derived from grassland increased at the initial stage but the increase declined when cultivated longer, and the C:N ratio decreased for soils derived from forest and fluctuated with the cultivation time. Lower C:N ratios than the global average and its decreasing trend with increasing reclamation age were found in newly reclaimed croplands from grasslands. Sustainable agricultural management practices are suggested to enhance the accumulation of soil carbon and nitrogen, as well as to increase the C:N ratio to match the nitrogen deposition to a larger carbon sequestration. Full article
(This article belongs to the Special Issue Remote Sensing Applications for Agriculture and Crop Modelling)
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Open AccessArticle Agroecological Practices and Agrobiodiversity: A Case Study on Organic Orange in Southern Italy
Received: 27 December 2018 / Revised: 5 February 2019 / Accepted: 11 February 2019 / Published: 14 February 2019
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The integration of Agroecological Service Crops (ASCs) into agroecosystems can provide several ecological services, such as nutrient cycling and disease and weed management. A two-year experiment on an organic orchard was carried out to compare barley (B) and horse bean (HB) ASCs with [...] Read more.
The integration of Agroecological Service Crops (ASCs) into agroecosystems can provide several ecological services, such as nutrient cycling and disease and weed management. A two-year experiment on an organic orchard was carried out to compare barley (B) and horse bean (HB) ASCs with a control without ASC (Cont) in combination with fertilizers. Their effects on soil fertility and weed- and soil-borne fungi communities were evaluated by direct measurements, visual estimation, and indicators computation. A Principal Component Analysis (PCA) was used to identify latent patterns and redundancy among variables, whereas a correlation analysis was used to discriminate the compared systems within the PCA matrix. The empirical results of this study put in evidence the correlation among soil, weed, and fungal variables. A slight contribution of fertilizers on the system’s variability was observed, whereas a clear effect of ASCs was highlighted. The systems differed in weed communities, with the lowest density associated to B and the highest to Cont. B showed the highest fungal diversity, with changes in community compared to HB. HB showed a contribution on soil fertility, being associated to organic matter increase and N availability, and evidencing mixed impacts on soil quality and ecosystem functioning. Overall, the above-ground diversity and below-ground community results were inter-correlated. Full article
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Open AccessArticle An Automatic Non-Destructive Method for the Classification of the Ripeness Stage of Red Delicious Apples in Orchards Using Aerial Video
Received: 22 January 2019 / Revised: 5 February 2019 / Accepted: 12 February 2019 / Published: 14 February 2019
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Abstract
The estimation of the ripening state in orchards helps improve post-harvest processes. Picking fruits based on their stage of maturity can reduce the cost of storage and increase market outcomes. Moreover, aerial images and the estimated ripeness can be used as indicators for [...] Read more.
The estimation of the ripening state in orchards helps improve post-harvest processes. Picking fruits based on their stage of maturity can reduce the cost of storage and increase market outcomes. Moreover, aerial images and the estimated ripeness can be used as indicators for detecting water stress and determining the water applied during irrigation. Additionally, they can also be related to the crop coefficient (Kc) of seasonal water needs. The purpose of this research is to develop a new computer vision algorithm to detect the existing fruits in aerial images of an apple cultivar (of Red Delicious variety) and estimate their ripeness stage among four possible classes: unripe, half-ripe, ripe, and overripe. The proposed method is based on a combination of the most effective color features and a classifier based on artificial neural networks optimized with genetic algorithms. The obtained results indicate an average classification accuracy of 97.88%, over a dataset of 8390 images and 27,687 apples, and values of the area under the ROC (receiver operating characteristic) curve near or above 0.99 for all classes. We believe this is a remarkable performance that allows a proper non-intrusive estimation of ripening that will help to improve harvesting strategies. Full article
(This article belongs to the Section Innovative Cropping Systems)
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Open AccessArticle Research into the E-Learning Model of Agriculture Technology Companies: Analysis by Deep Learning
Received: 18 November 2018 / Revised: 28 December 2018 / Accepted: 30 December 2018 / Published: 13 February 2019
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Abstract
With the advancement of technology, the traditional e-learning model may expand the realm of knowledge and differentiate learning by means of deep learning (DL) and augmented reality (AR) scenarios. These scenarios make use of interactive interfaces that incorporate various operating methods, angles, perceptions, [...] Read more.
With the advancement of technology, the traditional e-learning model may expand the realm of knowledge and differentiate learning by means of deep learning (DL) and augmented reality (AR) scenarios. These scenarios make use of interactive interfaces that incorporate various operating methods, angles, perceptions, and experiences, and also draw on multimedia content and active interactive models. Modern education emphasizes that learning should occur in the process of constructing knowledge scenarios and should proceed through learning scenarios and activities. Compared to traditional “spoon-feeding” education, the model learning scenario is initiated with the learner at the center, allowing the person involved in the learning activity to solve problems and further develop their individual capabilities through exploring, thinking and a series of interactions and feedback. This study examined how students in the agriculture technological industry make use of AR digital learning to develop their industry-related knowledge and techniques to become stronger and more mature so that they unconsciously apply these techniques as employees, as well as encouraging innovative thought and methods to create new value for the enterprise. Full article
(This article belongs to the Special Issue Deep Learning Techniques for Agronomy Applications)
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Open AccessReview Reframing the Debate Surrounding the Yield Gap between Organic and Conventional Farming
Received: 28 December 2018 / Revised: 7 February 2019 / Accepted: 11 February 2019 / Published: 13 February 2019
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In this article, we review the literature regarding the yield gap between organic and conventional agriculture and then reflect on the corresponding debate on whether or not organic farming can feed the world. We analyze the current framework and highlight the need to [...] Read more.
In this article, we review the literature regarding the yield gap between organic and conventional agriculture and then reflect on the corresponding debate on whether or not organic farming can feed the world. We analyze the current framework and highlight the need to reframe the yield gap debate away from “Can organic feed the world?” towards the more pragmatic question, “How can organic agriculture contribute to feeding the world?”. Furthermore, we challenge the benchmarks that are used in present yield comparison studies, as they are based on fundamentally distinct paradigms of the respective farming methods, and then come up with a novel model to better understand the nature of yield gaps and the benchmarks that they are premised on. We thus conclude that, by establishing appropriate benchmarks, re-prioritizing research needs, and focusing on transforming natural resources rather than inputs, organic systems can raise their yields and play an ever-greater role in global sustainable agriculture and food production in the future. Full article
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Open AccessArticle Screening Tolerance to Phosphorus Deficiency and Validation of Phosphorus Uptake 1 (Pup1) Gene-Linked Markers in Thai Indigenous Upland Rice Germplasm
Received: 2 January 2019 / Revised: 28 January 2019 / Accepted: 11 February 2019 / Published: 12 February 2019
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Phosphorus (P) deficiency is a major factor limiting rice yield throughout the world. Fortunately, some rice accessions are tolerant and can thrive well, even in soils with low P content. The ability to uptake P is heritable, and thus can be incorporated into [...] Read more.
Phosphorus (P) deficiency is a major factor limiting rice yield throughout the world. Fortunately, some rice accessions are tolerant and can thrive well, even in soils with low P content. The ability to uptake P is heritable, and thus can be incorporated into rice cultivars through standard breeding methods. The objective of this study was to screen for tolerance to phosphorus deficiency and validate the tolerant accessions with phosphorus uptake 1 (Pup1) gene-linked markers in Thai indigenous upland rice germplasm. One hundred sixty-eight rice varieties were screened in a solution culture and assigned a phosphorus deficiency tolerance index and plant symptom score. Eleven upland rice accessions (ULR026, ULR031, ULR124, ULR145, ULR180, ULR183, ULR185, ULR186, ULR213, ULR260, and ULR305), together with the lowland rice cultivar (PLD), were classified as tolerant. They were each validated by nine markers linked to the Pup1 locus and observed for the expected polymerase chain reaction (PCR) product of 0 to 9 markers. The presence or absence of the tolerant allele at the Pup1 locus showed only a slight relationship with the tolerance. Moreover, some lines such as ULR183 and ULR213 expressed high tolerance without the Pup1-linked gene product. Both accessions are useful for the exploration of novel genes conferring tolerance to phosphorus deficiency. Full article
(This article belongs to the Special Issue Soil Phosphorus Dynamics: Agronomic and Environmental Impacts)
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