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Using Grounded Theory methodology, this research was carried out with aim of explaining cooperative-based social entrepreneurship in the form of saffron cultivation chain in rural areas of Golestan province. In order to collect qualitative field data, a semi-structured deep interview was used. The research target group included those stakeholders involved in the development of saffron cultivation in the Tilabad watershed of Azadshahr County of Golestan province. Purposefully, to select the interviewees as key informants, the reputational sampling technique in the first stage and snowballing sampling in the second stage were used. The sample size and data collection process continued to the level of theoretical saturation or usefulness threshold of available information and 22 people were interviewed, totally. The process of data analysis consisted of a three-step chain of open, axial, and selective coding. Nvivo10 QSR software was used to extract the concept map of the codes. The research findings were summarized in the form of a paradigm model of cooperative-based social entrepreneurship. This model was formed from five components: causal conditions (demographic contexts, socio-economic constraints, agricultural-based livelihoods, and economic incentives towards income generation), contextual conditions (capacities and emerging challenges), intervening conditions (intervening agents, interventions, and intervention consequences), strategies (development of saffron value chain and serial entrepreneurship), and consequences (job and income diversification to achieve livelihood sustainability, the transformation of production arrangements based on the transition from independent family farming systems to the cooperative production system, increasing socio-economic resilience and in general, the realization of an entrepreneurial rural community).

Since saffron is a triploid crop, it does not generate seed when selfed or crossed and is passed down through the generations by daughter corms produced from the mother corms. As a result, agro-technology development is the only viable alternative for bringing this crop to its full potential. Saffron does not have any specific habitat preferences, as evidenced by discovering numerous unknown saffron farmed areas during the current study. The plant grows as a mixed crop under apple (Malus domestica Borkh), almond (Prunus amygdalus Batsch.), populus (Populus alba L.), and walnut (Juglans regia L.) trees, as well as in plains, undulated soils, hills, and rice fields. It can be found growing between 1585 and 2050 m above sea level. Different agro-techniques were standardized, among which compost soil (compost 250 gms per pot with 2 kgs of soil; 500 gms per tray with 4 kgs of soil; 10 kgs per bed) was found to be best for early flower production. Soil and farmyard manure (1:3), UDP 0.25 gms/pot (N-115.511+ K130.952+P-58.496 mg), soil DAP 650 mg/2 kg of soil (@P = 152.0899 mg), soil MOP 350 mg/2 kg (@ K = 183.37 mg) of soil was preeminent of procured in vitro raised cormlets in terms of their sprouting and survival of shoots. Corm density was also checked in the offseason of the crop, with growth activity of only saffron corms. Significant negative correlation was recorded with r = 0.82; n = 100; P ≤ 0.001. But the reverse trend was observed in the crop's growing season when most de-weeding and field preparations are accomplished. The study will benefit people in near future as it emphasized the imperative proofs and picture of saffron cultivation in Kashmir valley, reflects the realities of saffron cultivation and trounces the earlier myths.

Saffron is a strategic product. It is necessary to manage the programming principles in order to estimate acreage and production. Therefore, the speed and accuracy of such assessments is very important. Using remote sensing techniques for providing updated data and high functionality as well as the possibility of studying a wide range of image analyses with an acceptable precision can help in the assessment. In the present research, the area under cultivation of saffron in the city of Torbat Heydarieh was evaluated using Landsat 8 sensor data. After applying the primary processing on satellite images with using conventional techniques, satellite imagery processing including false color band combination, principal component analysis, vegetation index (NDVI, SAVI, EVI, DVI, RVI and TSAVI) and supervised classification of land under saffron cultivation were identified. Map production was done due to the fact that the earth was assessed via GPS in order to assess the classification. Kappa coefficient and overall accuracy were %88 and %98, respectively. The area under cultivation of saffron in this study was estimated to be 19503.4572 hectares. The results indicated that Landsat 8 satellite images have a high potential for rapid separation and identification of the area under cultivation of saffron in the region with relatively good accuracy and are appropriate tools to be used on a regional scale.