Kiwi Orchards Research Articles

Image detection model construction of Apolygus lucorum and Empoasca spp. based on improved YOLOv5.

The polyphagous mirid bug Apolygus lucorum (Meyer-Dür) and the green leafhopper Empoasca spp. Walsh are small pests that are widely distributed and important pests of many economically important crops, especially kiwis. Conventional monitoring methods are expensive, laborious and error-prone. Currently, deep learning methods are ineffective at recognizing them. This study proposes a new deep-learning-based YOLOv5s_HSSE model to automatically detect and count them on sticky card traps. Based on a database of 1502 images, all images were collected from kiwi orchards at multiple locations and times. We trained the YOLOv5s model to detect and count them and then changed the activation function to Hard swish in YOLOv5s, introduced the SIoU Loss function, and added the squeeze-and-excitation attention mechanism to form a new YOLOv5s_HSSE model. Mean average precision of this model in the test dataset was 95.9%, the recall rate was 93.9% and the frames per second was 155, which are higher than those of other single-stage deep-learning models, such as SSD, YOLOv3 and YOLOv4. The proposed YOLOv5s_HSSE model can be used to identify and count A. lucorum and Empoasca spp., and it is a new, efficient and accurate monitoring method. Pest detection will benefit from the broader applications of deep learning. © 2024 Society of Chemical Industry.

Analyzing On-Farm Spatiotemporal Distribution of Halyomorpha halys (Stål) (Hemiptera: Pentatomidae) Populations from a Precision Agriculture Perspective.

The brown marmorated stink bug, Halyomorpha halys Stål (Hemiptera: Pentatomidae), is native to Japan, China, Taiwan, and Korea. Its dispersion from Asia to the United States of America and Europe caused serious damage to fruit, vegetables, and high-value crops. In Greece, damages are reported in kiwi orchards in the regions of Pieria and Imathia, which are the main production areas of kiwifruit. Greek kiwifruit production is expected to increase twofold within the next years. The aim of this research is to study the terrain and canopy properties that may have an impact on the development of H. halys populations. Thus, five kiwi orchards in total were selected in the regions of Pieria and Imathia. Τen traps were installed from early June to late October within each selected kiwi orchard-two types of traps at every side of the orchards and the center. The installed traps were examined weekly and the number of the captured H. halys was recorded. During the same days, sentinel satellite images were analyzed to calculate the vegetation index, NDVI (Normalised Difference Vegetation Index), and NDWI (Normalised Difference Water Index). The results showed population variability within the kiwi orchards since the population of H. halys was higher in areas with high NDVI and NDWI values. Additionally, our research revealed that H. halys prefers to develop populations at higher altitudes at both regional and field scales. The results of this research can be used to reduce damages by H. halys in kiwi orchards using different rates of pesticides depending on the prediction of the population size. There are multiple benefits of the proposed practice, such as a reduction in the production cost of kiwifruits, an increase in farmers' profit, and environmental protection.

Model Application for Estimation of Agri-Environmental Indicators of Kiwi Production: A Case Study in Northern Greece

Due to the sensitivity of kiwifruit to soil water and nutrient availability, kiwi production is often associated with over-watering and over-fertilization, especially with nitrogen (N), resulting in increased environmental risks. Crop models are powerful tools for simulating crop production and environmental impact of given management practices. In this study, the CropSyst model was applied to estimate soil N budget and environmental effects of kiwi production, with particular regard to N losses, in two grower-managed kiwi orchards in northern Greece, involving two seasons and different management practices. Management options included N fertilization and irrigation. Model estimates were compared with yield and soil mineral N content (0–90 cm depths) measured three times within the growing season. Agri-environmental indicators were calculated based on the N budget simulation results to assess the environmental consequences (focusing on N losses and water use efficiency) of the different management practices in kiwi production. According to model simulation results, kiwifruit yield and N uptake were similar in both orchards. N losses to the environment, however, were estimated on average to be 10.3% higher in the orchard with the higher inputs of irrigation water and N fertilizer. The orchard with the lower inputs showed better water and N use efficiency. N leaching losses were estimated to be higher than 70% of total available soil N in both study sites, indicating potential impact on groundwater quality. These findings demonstrate the necessity for improved irrigation and N fertilization management in kiwi production in the area.

Occurrence and Distribution of Root-Knot Nematodes in Kiwifruit Orchard

The study was conducted to investigate the infestation and distribution of plant-parasitic nematodes on kiwi orchards in Korea. Plant parasitic nematodes genus and densities were investigated at a total of 102 sites in Jeollanam-do, Gyeongsangnam-do, and Jeju-do, which are the main production areas of domestic kiwi orchards. Plant parasitic nematodes detected were of 9 genera, including root-knot nematodes (Meloidogyne spp.), spiral nematodes (Helicotylenchus spp.), and needle nematodes (Paratylenchus spp.), and 56% of the 102 plantations were infected with root-knot nematodes. Root-knot nematodes were found to be the most important plant parasitic nematode in domestic kiwi orchards. The average density of root-knot nematodes is 97 per 300 cm<sup>3</sup> soil, and there is concern about the kiwi yield reduction. As a result of identifying the root-knot nematode species: M. arenaria, M. hapla, M. incognita, and M. javanica. Among them, M. arenaria is the most dominant. As the plant parasitic nematode infection route in fruit trees is often spread through the transplantation of infected seedlings, attention should be paid to the production of nematode-free plants during the production and supply of kiwifruit plants.

Multi-criteria sustainability performance assessment of horticultural crops using DEA and ELECTRE IV methods

AbstractThis paper presents a novel approach to multi-criteria sustainability performance assessment of horticultural crops. The crops are ranked by the decision-making method ELECTRE IV with environmental, energy and technological criteria. In total eight indicators are taken into consideration and calculated based on primary data collected from over 260 farms in northern Iran. Additionally, Data Envelopment Analysis is used to calculate the technical efficiency and potential for energy saving by different management of the production units. The novel contribution of this study is the comparison of several horticultural products (oranges, kiwis, persimmons and tangerines), when most of the previous studies have focused on one product. Moreover, novel calculations of the carbon footprint are presented for oranges, tangerines and persimmons. This paper also includes the first study on the environmental impact of persimmon fruit's production. The obtained results show that energy efficiency for orange, tangerine, kiwi and persimmon products: 1.1, 0.84, 0.53 and 1.22, respectively. In each hectare of kiwi orchards, the amount of CO2 emissions of 1219 kg and the ecological footprint of 3.21 hectares have been calculated, which is statistically significant compared to orange, tangerine and persimmon. The chemical and fuel inputs have the greatest potential for reducing energy consumption in the studied products. Results of ELECTRE IV showed that kiwi is the most sustainable selection for the studied region followed by orange, persimmon and tangerine, respectively. Kiwi has also relatively low technical efficiency. This means that this product has the greatest potential for a reduction of energy consumption, while maintaining the same amount of crop. It is recommended to include the development of kiwi orchards in the policies of Guilan, but with more careful management of the production inputs.

Kiwi Plant Canker Diagnosis Using Hyperspectral Signal Processing and Machine Learning: Detecting Symptoms Caused by Pseudomonas syringae pv. actinidiae.

Pseudomonas syringae pv. actinidiae (Psa) has been responsible for numerous epidemics of bacterial canker of kiwi (BCK), resulting in high losses in kiwi production worldwide. Current diagnostic approaches for this disease usually depend on visible signs of the infection (disease symptoms) to be present. Since these symptoms frequently manifest themselves in the middle to late stages of the infection process, the effectiveness of phytosanitary measures can be compromised. Hyperspectral spectroscopy has the potential to be an effective, non-invasive, rapid, cost-effective, high-throughput approach for improving BCK diagnostics. This study aimed to investigate the potential of hyperspectral UV–VIS reflectance for in-situ, non-destructive discrimination of bacterial canker on kiwi leaves. Spectral reflectance (325–1075 nm) of twenty plants were obtained with a handheld spectroradiometer in two commercial kiwi orchards located in Portugal, for 15 weeks, totaling 504 spectral measurements. Several modeling approaches based on continuous hyperspectral data or specific wavelengths, chosen by different feature selection algorithms, were tested to discriminate BCK on leaves. Spectral separability of asymptomatic and symptomatic leaves was observed in all multi-variate and machine learning models, including the FDA, GLM, PLS, and SVM methods. The combination of a stepwise forward variable selection approach using a support vector machine algorithm with a radial kernel and class weights was selected as the final model. Its overall accuracy was 85%, with a 0.70 kappa score and 0.84 F-measure. These results were coherent with leaves classified as asymptomatic or symptomatic by visual inspection. Overall, the findings herein reported support the implementation of spectral point measurements acquired in situ for crop disease diagnosis.

Energy budget, carbon and water footprint in perennial agro and natural ecosystems inside a Natura 2000 site as provisioning and regulating ecosystem services.

Energy flows in perennial agro and natural ecosystems are essential and could be related to greenhouse gas emissions and increasing water demands. Energy indices and carbon and water footprint are useful tools in assessing the interaction between production systems and environmental impact inside Natura 2000 sites and enhancing ecosystem services. The main aims of this study were to determine and compare energy indices, carbon and water footprint of olive groves, orange and kiwi orchards, and grasslands within and between 2 years, located in a Natura 2000 site, using an adjusted life cycle assessment (LCA) method; and to illustrate the importance of farming systems to ecosystem services. Proportional stratified sampling was used to select 36 farm types (12 olive groves, 12 oranges, and 12 kiwi orchards) and 12 grasslands from the municipality of Amfilochia, western Greece, during 2018 and 2019. Descriptive data analysis, correlational analysis, ANOVA, and hierarchical cluster analysis (HCA) were used to summarize and analyze the data. The main energy contributors for the three farm types were fertilizers and fuel consumption. The only input for the grasslands was animal manure. Energy efficiency showed the highest performance in olive groves followed in descending order by kiwi orchards, grasslands, and orange orchards. Concerning carbon-footprint, the values were the highest for orange orchards, followed in descending order by kiwi orchards, olive groves, and grasslands. Total water footprint values were the highest for grasslands and the lowest for olive groves. For both years, regarding HCA, each cluster consisted of the same ecosystems. According to the abovementioned indices, olive groves and grasslands are the most environmental friendly ecosystems. They could contribute in the environmental protection of the Amvrakikos Gulf, a Natura 2000 site. Kiwi orchards, although they are intensive along with the orange ones, seem to be more friendly to the environment than them and their cultivation in this Natura 2000 area is recommended. Energy indices and carbon and water footprint could be used, in order to highlight the related ecosystem (dis)services.

Emergence of multiple Diaporthe species causing kiwifruit rot and occurrence of resistance to a methyl benzimidazole carbamate fungicide in South Korea

In recent years, new fungal diseases in kiwifruits have emerged worldwide. This study is the first report of a postharvest kiwifruit rot in South Korea caused by Diaporthe eres and related fungal pathogens. After single spore isolation of Diaporthe-like fungi isolated from rotten kiwifruits, isolates were identified based on the multi-locus phylogeny using the nuclear rDNA internal transcribed spacer and three nuclear protein-coding loci. Among the 41 single-spore isolates, a majority of the isolates (75%) were identified as D. eres, followed by D. unshiuensis, D. phaseolorum, D. cf. pseudomangiferae and D. caryae. We evaluated fungicide resistance of the 41 isolates and confirmed that a significant fraction of the isolates (15%) was resistant to thiophanate-methyl, raising a concern on overuse of this type of fungicide in kiwi orchards. By sequencing a region of β-tubulin gene, we identified two point mutations altering amino acid sequences correlated with the observed resistance. For effective diagnosis of incidence of the fungicide resistance in the fields, we developed allele-specific PCR analyses detecting the point mutations that confer reduced sensitivity to thiophanate-methyl. Genetic structure of the 41 isolates suggested that there were at least five independent mutational events for acquiring the fungicide resistance. Unexpectedly, there was no clear distinction in the genetic structure between the 41 kiwifruit isolates and Chinese isolates that caused grapevine dieback disease, suggesting these Diaporthe species are non-host-selective pathogens that could damage different horticultural crops of economic importance. This study will help develop a discerned protection program to cope with the ongoing and upcoming threats of these genetically diverse kiwifruit rot pathogens.

Multi-sensor profiling for precision soil-moisture monitoring

Controlling soil moisture is crucial in optimizing watering and crop performance. Traditional monitoring systems rely on a single sensor or on a column of sensors that do not allow farmers to properly capture soil moisture dynamics in the soil volume occupied by roots. In this paper we propose PLUTO, an original approach that builds fine-grained 2D and 3D soil moisture profiles by relying on a grid of sensors. Profiles are computed using both interpolation-based and machine learning approaches. Besides the technical description of the approach, the paper reports a set of original visualizations and a large set of tests computed, over two years, on real Kiwi orchards. PLUTO proved to largely overcome the accuracy of profiles obtained with traditional sensor layouts. Considering that the cost of sensors is progressively decreasing, PLUTO provides a cost-effective, operative, and precise solution to moisture monitoring.

Population Dynamics, Effective Soil Factors, and LAMP Detection Systems forPhytophthoraSpecies Associated with Kiwifruit Diseases in China

China has the largest area of kiwifruit production in the world. Pathogens associated with root diseases of kiwi trees have not been investigated extensively. In this research, three Phytophthora species, Phytophthora cactorum, Phytophthora cinnamomi, and Phytophthora lateralis, which are pathogenic to kiwi trees in the main planting areas of China, were studied. The population densities of these species in 128 soil samples from 32 kiwi orchards in 2017 and 2018 were measured using multiplex real-time quantitative PCR based on the ras-related protein gene Ypt1. P. cactorum was the most widely distributed of the three species in orchards of the Zhouzhi and Meixian prefectures. We used redundancy analysis to examine soil factors in the kiwi orchards to understand their effects on the population densities of the Phytophthora species. The redundancy analysis indicated that soil temperature and pH were significantly correlated with the abundance of P. cactorum and P. cinnamomi. In addition, two loop-mediated isothermal amplification detection systems for P. cactorum were developed based on the tigA gene. The color-change detection system proved to be accurate, sensitive, and faster than quantitative PCR. The results of this study, along with the loop-mediated isothermal amplification detection systems, will be of great use in the control of Phytophthora diseases for the production of kiwifruits in China.

Sino–EU Earth Observation Data to Support the Monitoring and Management of Agricultural Resources

Novel approaches and algorithms to estimate crop physiological processes from Earth Observation (EO) data are essential to develop more sustainable management practices in agricultural systems. Within this context, this paper presents the results of different research activities carried out within the ESA-MOST Dragon 4 programme. The paper encompasses two research avenues: (a) the retrieval of biophysical variables of crops and yield prediction; and (b) food security related to different crop management strategies. Concerning the retrieval of variables, results show that LAI, derived by radiative transfer model (RTM) inversion, when assimilated into a crop growth model (i.e., SAFY) provides a way to assess yields with a higher accuracy with respect to open loop model runs: 1.14 t·ha−1 vs 4.42 t·ha−1 RMSE for assimilation and open loop, respectively. Concerning food security, results show that different pathogens could be detected by remote sensing satellite data. A k coefficient higher than 0.84 was achieved for yellow rust, thus assuring a monitoring accuracy, and for the diseased samples k was higher than 0.87. Concerning permanent crops, neural network (NN) algorithms allow classification of the Pseudomonas syringae pathogen on kiwi orchards with an overall accuracy higher than 91%.

Could energy equilibrium and greenhouse gas emissions in agroecosystems play a key role in crop replacement? A case study in orange and kiwi orchards.

The development of agriculture is linked to energy resources. Consequently, energy analysis in agroecosystems could be a useful tool for monitoring some measures in the agricultural sector to mitigate greenhouse gas emissions. The objectives of this study were to (a) evaluate differences of energy indices in orange and kiwi orchards, and (b) point out whether inputs, outputs, efficiency, productivity, and carbon footprint can play a key role in crop replacement. Proportional stratified random sampling was used to select 26 orchards (10 oranges, 16 kiwis) from the Prefecture of Arta, western Greece, during 2015 and 2016. Univariate statistical methods were combined with multivariate ones. Nitrogen, Mg, Zn, herbicides, insecticides, fungicides, renewable energy inputs, fruit production, total outputs, and energy efficiency and productivity were statistically significantly high in the orange orchards. Phosphorus, Ca, irrigation, machinery, total inputs, intensity, non-renewable energy consumption, and carbon footprint were statistically significantly high in the kiwi orchards. The most important energy inputs for both fruit crops were fertilizers, fuels, irrigation, machinery, and herbicides. The orange orchards seem to be more friendly to the environment than the kiwi orchards by having low total energy inputs 32,210.3 MJ ha-1, intensity 1.4, consumption of non-renewable energy 0.7 MJ kg-1 and CO2 equivalent/fruit production 0.08 kg kg-1, and high energy outputs 105,120.0 MJ ha-1 and fruit production 53,648.0 kg ha-1. The findings of the present study show a relation between climate change and the production of farming systems, which can be a tool for decision makers. The correlation of the abovementioned parameters ensure higher profits and could help in achieving the best possible sustainable management of the agricultural ecosystems.

Estimation of kiwifruit yield by leaf nutrients concentration and artificial neural network

AbstractThere is a fundamental concern regarding the prediction of kiwifruit yield based on the concentration of nutrients in the leaf (2–3 months before fruits harvesting). For this purpose, the current study was designed to employ an artificial neural network (ANN) to evaluate the kiwi yield of Hayward cultivar. In this regard, 31 kiwi orchards (6–7 years old) in different parts of Rudsar, Guilan Province, Iran, with 101 plots (three trees in every plot) were selected. The complete leaves of branches with fruits were harvested, and the concentration of nitrogen, potassium, calcium, and magnesium measured. After fruit harvesting in late November, the fruit yield of each plot was evaluated along with the fresh and dry weights of the fruit. The ANN analyses were carried out using a multi-layer perceptron with the Langburge-Marquardt training algorithm. Using calcium (Ca) as input data (Ca-model) was more accurate than using nitrogen (N-model). The maximum R2and the lowest root mean square error was obtained when all nutrients and related ratios were considered as input variables. Since the difference between the proposed model and the model fitted by the calcium variable (Ca-model) was only about 6%, the Ca-model is recommended.

Seasonal population fluctuations of white peach scale, Pseudaulacaspis pentagona (Hemimptera: Diaspididae) and its parasitation in kiwi orchards of northern Iran

The economic importance of white peach scale (WPS) Pseudaulacaspis pentagona Targioni-Tozzetti, 1886 (Diaspididae: Hemiptera) is ascribed to its high reproductive potential. The number of generations per year varies in different places of the world. Seasonal population fluctuations of different life stages of WPS were studied from April 30, 2015, to April 29, 2017, on kiwi fruit trees in the Mazandaran province of Iran. In the first year the total population of P. pentagona had five peaks: April, June, August, October, and November. In the second year, the total population of P. pentagona had four peaks: May, August, October and November. The pre-adult stages had four high infestation periods in May, July, August, and October in the first season and also in the second year occurred on May, Jun, September and October. The gravid females began to appear and laying of eggs started from late March in both years. The maximum period of infestation was reached during May. Significant differences were observed among samples in different directions of the tree and most pests were found in the South. The rate of parasitization also varied with the month from 12 to 84% on branches of kiwi fruits. The highest percentage of the parasitation was observed in North and West. Thus, the present results may help in planning a successful control program of WPS on kiwi fruit trees in the Mazandaran province of Iran.

Biodiversity and population fluctuations of parasitoids of the white peach scale, Pseudaulacaspis pentagona (Targioni-Tozzetti) (Hemiptera: Diaspididae), in kiwifruit orchards in Northern Iran

Summary The white peach scale, Pseudaulacaspis pentagona Targioni-Tozzetti (Hemiptera: Diaspididae), is one of the most important and destructive polyphagous pests of the Rosaceae family trees. Population fluctuations and biodiversity of the hymenopteran parasitoid species associated with the pest were studied in six kiwi orchards in Iran, during one-year period. Parasitoid species abundance, species diversity indices and evenness indices were calculated. Most of the parasitoid species were dominant or eudominant. Based on the alpha diversity indices, the Najarkola region had high diversity and the Kharatkola region had low diversity. The Paeendasteh region (based on Simpson’s Diversity on Camargo evenness indices) and the Samnakola region (based on the modified Nee, and on Smith and Wilson evenness indices) were less uniform. Among the recorded parasitoids, Encarsia berlesei Howard (Hymenoptera: Aphelinidae), followed by Aphytis proclia Walker (Hymenoptera: Aphelinidae), had the highest population in all orchards.

Reducing nitrogen fertilization of intensive kiwifruit orchards decreases nitrate accumulation in soil without compromising crop production

Excessive nitrogen (N) fertilization of high value horticultural crops is a common problem that not only increases the cost to farmers, but also negatively affects crop growth and the environment. A three-year field experiment was conducted in an intensive kiwifruit orchard in Shaanxi Province, China to compare the effects of reduced N fertilization applied as urea (U), and controlled release urea (CRU) on the N nutrition of kiwi vines, fruit yield and quality, and nitrate-N accumulation in the soil profile. The three treatments included a conventional N application rate (CF-U, 900 kg N ha−1 yr−1 as urea), two reduced N fertilization treatments where the amount of N fertilizer applied as U and CRU was reduced by 25% in 2013 and 2014, and by 45% in 2015. The 25 and 45% reduced N treatments had no adverse effects on the N concentrations in leaves and pruning branches and the fruit yield and quality of kiwi vines. However, they significantly enhanced the partial factor productivity of applied N (PFPN) and the economic benefits, and reduced nitrate accumulation in the 0–200 cm soil profile. The same benefits of reduced N fertilization were observed for both the U and CRU treatments, but the CRU treatment had the added benefit of decreasing the loss of nitrate through leaching. We concluded that the current level of N fertilization in kiwi orchards is very excessive, and reducing the N fertilizer rate by 25–45% could not only guarantee fruit yield, but also reduce N accumulation and loss.

Energy flow, carbon and water footprints in vineyards and orchards to determine environmentally favourable sites in accordance with Natura 2000 perspective

Abstract The assessment of energy flow in agroecosystems can help to select the best management strategies for cultivated species. Conventional and organic vineyards and kiwi orchards along with conventional, integrated and organic apple orchards were selected from sites located both in and out Natura 2000 network to (a) determine energy efficiency of the farming systems, (b) estimate gas emissions along with carbon and water footprint, (c) reveal groups of farming systems on the basis of their similarities to energy efficiency, carbon and water footprint. Forty one farms (ten conventional and five organic vineyards; five conventional and three organic kiwi orchards; six conventional, four organic and eight integrated apple orchards) were selected during the years 2010–2013 in the Prefecture of Pella, northern Greece. Hierarchical Cluster Analysis (HCA) revealed three main Groups of farms. In descending order, the contributors in cluster formation were CO2-equivalent, energy efficiency, and water footprint. Group 3 had the highest CO2-equivalent per fruit production. The vineyards of Group 3 located at the highest altitude resulted in highest labor, diesel, branch shoring, intensity, energy consumption and greenhouse gas emissions (CO2, CH4, and N2O). They showed the lowest irrigation, total water consumption, energy outputs, and energy productivity. Group 2 had the highest water consumption per fruit production. Group 1 showed high environmental advantages since it had the lowest CO2-equivalent, the highest energy efficiency, and intermediate water footprint. The above indices are useful to decision makers for seeking crops and farming systems in order to regulate the fragile balance between Natura 2000 network and agriculture.

Determination of Weed Species in Kiwifruit Orchards of Ordu Province-Turkey

This study was conducted to determine weed species, their frequencies (%), coverage areas (%) and their densities (plant/m²) in kiwifruit orchards of Ordu province in 2015. As a method Ordu was divided into four parts of the research area; Altınordu-Gülyalı, Ulubey-Kabadüz, Perşembe-Fatsa-Çamaş, İkizce-Ünye-Çaybaşı. The study was carried out in two different periods which are April-May and September-October in the year of 2015. Study was started from the center of Ordu and stopped for every 5 km to make four different examinations of randomly selected 1 m² area of 1 da the kiwifruit orchard. During examinations weed species, their frequencies (%), coverage area (%) and their densities (plant/m²) were determined. Eighyt six weed species belonging to 32 families were determined in the survey which was carried out in 26 kiwi orchards. At the end of this survey which is conducted in two different periods, general weed coverage is found out to be 82.27 % for the first period (April-May) and 80.12 % for the second period (September-October). Among these families the largest family was found to be Asteraceae having 18 species. In the first period (April-May) 71 species were identified belonging to 30 families and the most frequently encountered weed species was Convolvulus arvensis L. (field bindweed) by 69.23 %. In the second period (September-October) 67 species were identified belonging to 30 families and the most frequently encountered weed species was C. arvensis L. by 53.85 %.

Could energy flow in agro-ecosystems be used as a “tool” for crop and farming system replacement?

Energy flow in orchards can be used to determine first the best management practices and second the possibility of using those which have best environmental advantages. Conventional and organic peach and kiwi orchards were selected in order to (a) determine energy flow of the farming systems, and (b) reveal the importance of energy inputs in crop and farming system replacement. Fifteen farms (four conventional and three organic kiwi orchards; four conventional and four organic peach orchards) were selected with proportional stratified random sampling during the years 2010–2013. The Hierarchical Cluster Analysis (HCA) method was applied using nine production coefficients' variables (fertilizers, fungicides, insecticides, weed control, diesel, labor, irrigation, branches shoring, and machinery) and revealed three groups of the studied orchards. The highest contributors in cluster formation were weed control, branches shoring, labor, and machinery. The effect of the production coefficients on the grouping of the studied orchards reveals their importance for these crops and farming systems. Most of the production coefficients showed their lowest values in organic kiwi orchards (Group 3), so it could be said that they can play a key role in the replacement of the peaches, and conventional kiwi orchards. It seems that production coefficients can be used as a “tool” for decision makers who are seeking for crops and farming systems with low energy inputs and best environmental advantages in order to use them in crop replacement in agro-ecosystems.

Determining an Appropriate Fertilization Planning to Increase Qualitative and Quantitative Characteristics of Kiwifruit (Actinidia deliciosa L.) in Astaneh Ashrafieh, Gilan, Iran

The lack of balanced use of fertilizers is one of the reasons for the low yield and the low quality of kiwifruits in Gilan Province, Iran. In order to determine a suitable fertilization planning for kiwi orchards ( Actinidia deliciosa L. cv. Hayward) in Astaneh Ashrafieh, an experiment was performed in 10 treatments with 3 replications based on a randomized complete block design with different amounts of fertilizers in different fertilizing methods. Treatments include different amounts of macro- and micronutrient fertilizers with foliar spraying of calcium, zinc, and potassium in different stages. In this study, the yield of each tree, the fruit firmness, sugar, pH, wet weight, percentage of dry matter, and the content of macronutrients (nitrogen, phosphorus, and potassium) and micronutrients (iron, zinc, and manganese) in the fruit were measured. The results showed that the treatment of 350 g urea, 500 g potassium sulfate, 500 g superphosphate, 80 g iron sulfate sprayed foliarly with 5 parts per thousand of zinc chelate and iron chelate, and foliar spraying with 0.5% of calcium during several stages for each tree has the highest effect on the yield of each tree, the fruit firmness, the fruit pH, and the percentage of the fruit dry matter, so such a yield of this treatment showed a difference of 7.9 kg with control.