جستجوی مقالات مرتبط با کلیدواژه « irrigated » در نشریات گروه « کشاورزی »

The application of soil quality (SQ) in sustainable land management is evolving. However, despite their considerable importance, the inclusion of biological properties in soil quality assessments is limited due to the challenges and high costs associated with measuring these attributes. This study was carried out on the contribution of biological properties to soil quality. In this research, 22 physical, chemical, and biological properties of 90 surface soil samples (0-30 cm) were analyzed to determine the soil quality index (SQI) in the Honam region of Lorestan. Analyzed properties included pH, electrical conductivity (EC), organic carbon (OC), total neutralizing value, clay and silt content, microbial biomass carbon (MBC), basal microbial respiration (MR), the total fungal and bacterial populations, the populations of Azotobacter and Pseudomonas species, as well as the activities of urease, acid and alkaline phosphatase, the available potassium and phosphorus concentrations, the total nitrogen, and the content of manganese, iron, copper, and zinc. Principal component analysis (PCA) to select a minimum data set (MDS) revealed that eight principal components, each with eigenvalues greater than one, accounted for 89.83% of the total variance. Of the 22 soil properties 12 were selected for the MDS, with biological properties (5 properties) making a more significant contribution than the physical and chemical properties. The spatial distribution of the SQI underlines the significant influence of biological properties on soil quality. These results underline the importance of including biological properties in the assessment of soil quality.

Remote sensing methods for mapping farms and crops have been widely used in the last three decades. This method is applied to identify irrigated areas around the world (Alipour et al., 2014), although most of these studies are in areas with semi-arid climates and low rainfall or lack of rainfall which has a significant effect on the spectral characteristics of plants. In this study, Landsat 8 and MODIS satellite images were used to identify and separate two irrigated and rain-fed wheat farms in Hamadan province. Two algorithms of support vector machine (SVM) and minimum distance (MD) were used simultaneously to classify irrigated and rain-fed farms. In the next step, the area under cultivation of rain-fed and irrigated wheat was predicted in the whole cultivated area of Hamadan province. Finally, the cultivation area of rain-fed and irrigated crops was calculated in the province using Sentinel 3 satellite images based on the random forest algorithm in 2016.

The study area is Hamedan province, which is located between 59◦ 33′ and 49◦ 35′ north latitude and also from 34◦ 47′ to 34◦ 49′ east longitude of the Greenwich meridian. A 50-hectare rain-fed wheat farm in Amzajerd was used as a sample to extract the properties of rain-fed wheat. Also, irrigated indices were extracted from a 100-hectare irrigated wheat farm located in Kaboudrahang. Satellite images were applied to separate irrigated and rain-fed wheat in Hamadan province. NDVI, EVI and NDWI indices were extracted from 16-day images of Landsat, MODIS, and Sentinel 3 sensors in the five-year period (2015-2019). Google Earth Engine (GEE) system was the environment for performing image processing calculations and extracting indices and maps.

The NDVI and EVI of irrigated and rain-fed wheat farms were calculated in 2015-2019. A small peak was observed in the rain-fed and irrigated NDVI trend in November due to the early germination of wheat leaves in winter, and the larger peak in May and June showed the maximum greenness of irrigated and rain-fed wheat, respectively. The ascending or descending trend of NDVI / EVI had no constant slope. This can be due to changes in meteorological parameters, which sometimes cause a sudden increase or decrease in the values of these indices. Despite the non-linearity of the NDVI / EVI trend over time, the maximum greenness was recorded just a month before the wheat harvest, which was seen in the third decade of May to the first decade of June. One of the cases is the sharp drop of NDVI / EVI after its final peak, which was definitely due to yellowing wheat and harvesting. Since the distinction between rain-fed and irrigated crops was difficult only based on NDVI, NDWI was also used to determine the water content of wheat so that irrigated wheat could be identified. However, the difference between rain-fed and irrigated wheat in terms of NDWI spectral density was insignificant; the maximum and minimum occurrence times of NDWI and NDVI of rain-fed and irrigated wheat were chosen for their separation. In order to map the cultivation area, in addition to the MODIS sensor, Sentinel 3 was used due to its ability to detect chlorophyll accurately. Due to the fact that the imaging of the Sentinel 3 satellite started since 2016, the map of rain-fed and irrigated cultivation as well as the cultivation area and their separation was done based on the random forest algorithm in 2016.

The results of this study showed that the appropriate method for distinguishing between rain-fed and irrigated wheat is the simultaneous use of several indices. Also, the greatest difference is in the maximum greenness, which happened almost one month before harvest. MD and SVM classification algorithms could distinguish irrigated and rain-fed wheat from other crops with 90% and 80% accuracy, respectively. Distinguished maps of irrigated and rain-fed crops based on the random forest algorithm were obtained using Sentinel 3 satellite imagery which can show the fertility of agricultural lands in the province.

Fusarium head blight of wheat with causal agent of fungus Fusarium graminearum is one of the most common diseases affecting wheat. Fusarium as one of the major wheat diseases makes a significant loss on wheat yield and quality globally. Northern Iran, due to the distinct conditions of humidity and temperature is susceptible to Fusarium head disease. One of the most efficient ways to control this disease is the use of resistant, genetically modified cultivars. The annual screening of plant cultivars offers useful information on resistance of cultivars to Fusarium head disease for researchers.

In this study 21 cultivars of common wheat including irrigated and rainfed plus three resistant cultivars and susceptible in a complete block design with three repeat in two different environment were cultivated in Gorgan University educational farm in 2016. One of the settings was the disease-induced and the other was not disease-induced. In the stressed setting artificial contamination was induced with spore suspension and in the non-stressed setting Falcon fungicide was used to control the disease. Each wheat cultivar was planted on a 4.5 meter line. Lines had a 30 cm distance from each other and seeds had a distance of five cm. In this experiment, fresh fungi suspensions with a concentration of 1×108 macroconidia per milliliter were used. Fusarium spore suspension was applied to spikes at the beginning of the flowering period at the onset of the emergence of anthers. After spore suspension application, the disease indices including, the incidence of disease, severity of disease and disease index, and after harvesting, the percentage of infected seeds and performance indicators were measured.

Based on the results of analysis of variance, a significant difference between the cultivars tested at the probability level of 1% for incidence, severity of disease and percentage of contaminated grains was observed. Analysis of yield data using analysis of combined experiments showed that the cultivars Qaboos, Aftab and Layn 17 among the rainfed wheat cultivars, and Morvarid in irrigated cultivar, were the best cultivars in response to Fusarium head blight. Among the cultivars studied, Qaboos and Aftab had the least yield loss and were suitable for cultivation in areas with Fusarium head blight epidemy.

The results of this study showed that the occurrence of a biotic stress such as Fusarium head blight negatively affects the grain yield, the more resistant cultivars have lower yield loss. The results of this research can be used as a source for resistant genotypes for corrective actions. Qaboos and Aftab cultivars are introduced as resistant cultivars in areas with high risk of Fusarium epidemy. The Ehsan cultivar is a coarse grain cultivar and has a good yield in a disease-free environment, perhaps it can be found to be suitable for cultivation in areas with low humidity

Due to the large diversity of weeds in irrigated and rain fed wheat fields in East Azerbaijan province, Determining dominant specific weeds and prepare their distribution map, wheat fields were survey based on identical approach. During 9 years (from 2000 to 2009), in 231 wheat fields based on their sizes from 19 counties were selected and abundance of weed species were studied. The results showed that there were more than 112 and 137 species of weeds in irrigated and rain fed field belonging to 101 genera of 28 families. The most important dominant broad leaf weeds in rain fed and irrigated fields were: Galium tricornatum, Chenopodium album, Descurania Sophia, Polygonium aviculare, Geranium tuberosum, Goldbachia laevigata. Grass leaves weeds are Eremopyrum bonaepartis, Alopecurus myosuroides, Bromus tectorum. In addition weed genuses like Acroptilon repens, convolvulus arvensis, Salsola kali, cardaria draba, Lactuca serriola, arethemost prevalent weeds at harvesting time in the wheat fields of province. The results also showed that controlling measures of weeds in wheat fields of province is not satisfactory and their management methods prior to harvesting are even worse.