جستجوی مقالات مرتبط با کلیدواژه "مدیریت مزرعه" در نشریات گروه "زراعت"

Over the past four decades, pod anormaly disorder has been one of the most important factors affecting soybean seed yield and production in Golestan province in Iran. To assess the role of crop management factors on soybean pod anormaly and seed yield, 80 soybean fields were selected randomly during 2018 and 2019 in Gorgan and Aliabad in Glestan province. Stepwise regression analysis showed that seed yield model (Yield = -442.5 + 6.9 X1 + 180.2 X2 + 866.2 X3) was determined with three factors of potassium fertilizer (X1), number of irrigation (X2) and insect pest management (X3). Potassium fertilizer, number of irrigation and insect pest management explained 19.2%, 18.7% and 62.1% of the yield gap components, respectively, and reflected the importance of these factors for increasing soybean seed yield. Among 80 soybean fields, 15 and 18 fields had full and partial pod anomaly disorder symptoms, respectively. The mean soybean seed yield for fields without and partial pod anomaly disorder was 3039 and 848 kg ha-1, respectively. The results of this study showed the importance of optimum insect pest management to prevent and control the incidence of soybean pod anomaly disorder in Goletan province in Iran.

Over the past four decades, pod anomaly disorder has been one of the most important factors affecting soybean seed yield and production in Golestan province in Iran (Payghamzadeh, 2017; Malek Shahkouei et al., 2019; Faraji et al., 2023). This conditions has led to disorders in the flower and pod system of the soybean plant which ultimately causes no or low pod set, modified of pods shape, stay-green plants, and so called by the farmers, fodder plants In fact, in the affected plants, a mechanism prevents the transfer of assimilates from leaves to seeds, hence the leaves remain green and the plants continue vegetative growth. In 2015, about 13765 hectares out of the total of 35107 hectares (about 39% of the soybean growing areas) suffered from this disorder. Due to luck of adequate quantitative information on the role of each of the factors in the incidence of this disorder and seed yield reduction, it would be necessary to investigate the effect of each of these factors on reduction of the soybean seed yield to enable farmers to overcome these limiting disorders by adopting appropriate crop management strategies.
 

In order to investigate the role of management factors affecting the seed yield and incidence of pod abnormality disorder in soybean, during the years 2018 and 2019, 80 soybean fields in the two cities of Gorgan and Aliabad, were determined and investigated. These fields included good, medium and poor fields and even seed production ones. Soybean variety cultivated in all investigated fields was Katul. During the growing season, the stages of development, including the date of planting, emergence, beginning and end of flowering, podding, seed filling, physiological maturity and harvest maturity were determined (Fehr et al., 1971). For data analysis, the collected information was normalized (SAS, 1997). To determine the yield model, qualitative variables were coded as zero and one. Then, the relationship between all quantitative and qualitative measured variables with yield was investigated through step wise regression method and data analysis was performed using the statistical method of yield comparison analysis (Soltani et al., 2009). Finally, using the yield model and parameter values, potential yield, yield gap and the contribution of each factor causing the yield gap were determined.
 

Out of 80 studied soybean fields, 47 fields had completely normal soybean plants and no pod anomaly disorder, 18 fields had moderate pod anomly disorder and 15 fields had completely affected by pod anomaly disorder. Mean seed yield in fields without disorder, with moderate disorder and complete disorder was 3039, 848 and 0 kg ha-1, respectively, indicating considerable sedd yield reduction of 72% and 100% in fields with moderate and complete disorder in comparison with fields without disorder. These results reflected the importance of pod anomaly disorder in reducing soybean seed yield. The seed yield model estimated the average and maximum seed yields as 2003 and 4792 kg ha-1, respectively. The estimated yield gap was 2789 kg ha-1 that with approperiate crop management particularly effective insect pest control, adequate potassium fertilizers application and adequate number of irrigations can be narrowed and even closed. The results of this two-year field study showed that under the conditions of Golestan province, it is possible to significantly increase soybean seed yield by application and adoption of appropriate crop management startegies and techniques.

To quantify the role of crop management practices on seed yield of soybean in Gorgan, 120 soybean farmers’ fields with different sowing dates and different management practices were randomly selected in Gorgan region in the north of Iran, in 2016, 2017 and 2018. Qualitative information was transformed to quantitative data. By using stepwise regression analysis a seed yield model was selected with two parameters including; delay in sowing date and number of irrigation during soybean growing season. The selected model explained 81% of the variation for seed yield. The model showed the importance of sowing date and irrigation for increasing seed yield of soybean in farmers’ fields in Gorgan region. There was negative significant linear relationship between biological and seed yield with delay in sowing date that explained 64% and 70% of the variation for these two characteristics, respectively. Each day delay in sowing date from May 22, biological and seed yield decreased 130 and 56 kg ha-1, respectively. The mean seed yield of farmers’ fields, with 0, 1, 2, 3, 4, 5 and 6 irrigation during growing season, was 955, 883, 1066, 1995, 1990, 2665 and 3769 kg ha-1, respectively. In Goragan region, soybean is planted usually from late may following harvest of winter crops such as wheat and canola. Under these environmental conditions, optimum crop management practices are required in soybean farmers’ fields to achieve high seed yield and sustainable production.

Rice (Oryza sativa L.) is the staple food of more than half of the world’s population and has an important role in feeding, income and job creation in the world, especially Iran. Yield gap analysis provides little estimation of increased production capacity which is an important component in designing food-providing strategy in regional, national and global scales. The existing heated discussions regarding food security have increased the number of necessary studies that estimate the quantity of yield gap and the reasons behind it through appropriate statistical methods in Iran and the rest of the world. It seems that by defining the effectiveness of each management parameter regarding the amount of presented yield gap and, consequently, the farmer’s knowledge on that matter the distance between actual yield and attainable yield can be reduced. In this research, estimation of potential yield, yield gap, and determining yield restricting factors and each of their portions in creating rice yield gap have been investigated.

Research was done in 100 paddy fields in Amol and Rasht regions in 2016 and 2017. All managerial practices from nursery preparation to harvest for local rice cultivars were recorded through fields monitoring. Field selection was done in a way that included all main production procedures with variation in management viewpoint. To define yield model, the relationship between all measured variables and the final model was designed by controlled trial and error method, which could quantify the effect of yield limitations. The average yield was calculated by placing the observed average variables (Xs) in the fields under study in the yield model. Thereafter, by putting the best observed value of the variables in the yield model the maximum obtainable yield was calculated. The difference between these two has been considered yield gap. Different procedures of the software SAS version 9.1 were used for analysis.

Data analysis revealed that from 155 variables under study, the final model in Amol and Rasht regions with seven and six independent variables was chosen. In Amol yield model, maximum and average yield were 4798 and 6505 kg ha-1, respectively that estimated yield gap was 1707 kg ha-1. In Rasht yield model, maximum and average yield were 4443 and 6377 kg ha-1, respectively, which estimated that yield gap was 1934 kg ha-1. In Amol region, the amount of increased yield related to transplanting date, top-dressing and nitrogen after flowering variable was 364, 292 and 416 kg ha-1 which equals to 21, 17 and 24 percent of total yield increase. In Rasht region, the yield increase related to the effect of potassium and nitrogen before transplanting, and N after flowering was 644, 325 and 730 kg ha-1 which equals to 33, 17 and 38 percent.

According to the findings, we suggest that the model precision is appropriate and can be applied for both estimating the quantity of yield gap and determining the portion of each constraints yield variables. Furthermore, considering the fact that the calculated yield potential is reached through actual data in each paddy field, it is suggested that this yield potential is attainable.

Field weed identification is considered as the most important step in weed management of crops. Based on the area under cultivation and the area of the farms in the city of Eshtehard, during 5 years , weeds were counted by weed number by species and species in each area at the sampling points. In each area of latitude and longitude, and altitude from the sea level, the place of measurement was recorded by the GPS device. The results showed that there are 47 weed species in Eshtehard. The most abundant species of weeds in this city, respectively, include: Syrian beancaper ,Mouse barley , Camel thorn ,Black bindweed ,Russian thistle ,Common lambsquarter ,Woodsorrel ,Bermudagrass ,Barley grass .In addition to the most important weeds, the uninvited guests of the city of Eschidar are Wimmer ryegrass (Lolium rigidum), Prickly lettuce ,Russian knapweed,Corn cockle (Vaccaria grandiflora), Common yarrow (Achillea wilhelmsii), Sophora (Sophora alopecuroides), Burdock (Xanthium strumarium) and other weeds with a lower frequency. The most noticeable point in this experiment was the increase in the prevalence of weed and goatmeat (11 and 9%) over the past five years, which gives rise to the concern that, due to the climatic conditions and soil and soil conditions,These weeds are prone becoming the dominant weed of the region.New species of Creeping thistle (Circium arvense), Swallow wort (Cynanchum acutum) and Prickly lettuce (Lactuca scariola), although found at low densities in the area, could be a serious threat to the city's farms, which could further expand to adjacent areas.

Field bindweed is a deep rooted prenial weed that is resistant to drought in Iran. Herbicide applications indicates the low control of this weed. However, little data are available to verify efficacy with repeated treatments in flowering stage in the orchards in Iran. These experiments were conducted in the completely randomized designe with four replications and 13 treatments in Tehran and Isfahan. Treatments were post emergence applications of glyphosate (Roundup, SL 41%) at 2%, 3% and 4% plus amonium sulphate, new glyphosate (Weedmaster, SC 35%) at 0.75% and 1%, amitrol+ ammonium thiocyanate+ glyphosate (Illico, Sl 30.9%) at 4%, 5% and 6%, triclopyr (Garlon, EC 60%) at 1% and 1.5%, fluroxypyr (Starane, EC 25%) at 0.5% and 0.75% and control (without herbice). Treatments in Tehran reduced field bindweed growth 100%. However, 3 to 4 months after the treatments, stem regrowth was 0%. In Isfahan, fluroxypyr and triclopyr controlled field bindweed by 94 -97% on visual injury estimation. Furthermore, some herbicides reduced up to 93% field bindweed stem biomass and densities at the end of second year.

Soybean pod abnormality is a kind of growth in which soybean plant accompanied with growth disorders including sever pod and flower abscission as well as leaves and pod morphological modifications. In an acute status, these kinds of plants stays green; therefore, the yield decreases and harvest time delay, dramatically. To investigate the reasons of pod distortion abnormality in Katul cultivar, a field assay based on roving method was performed. In the field experiment based on roving method 40 fields of Katul were selected randomly and traits like yield and yield component as well as managemental and climatic parameters were recorded in two successive growing years, 2015 and 2016. Result indicated that all field management factors didnot have any effect on PDS, except frequency of irrigation. In such a way that decreasing frequency of watering increased incidence of PDS significantly. Furthermore, percent of flower abscissions as well as shoot dry weight were increased; meanwhile, number of pod per plant, number of grain per pod, number of grain per plant, 1000-grain weight, harvest index, biological yield and grain yield dwindled extraordinary in PDS plants. Taken together, these results indicated that abiotic stresses such as heat and drought stresses as well as undesirable field irrigation might play an important role in soybean pod distortion abnormality incidence. In addition, interpreting of mineral nutrient indicated that well nutrition plants might decrease damage percentage of soybean pod abnormality.