The development of high-yielding heat-tolerant cotton cultivars harboring plastic phenotypes across warming climatic regions is prime objectives of today’s cotton breeding programs. We evaluated eight parents and 15 F₁ hybrids under normal and heat stress conditions. Agronomic and biochemical characters were analyzed using standard least square, correlation, principal component analysis (PCA), and hierarchical clustering. The results explained a significant reduction in all traits except hydrogen peroxide contents, catalase, and peroxidase activities with a prominent increase under heat stress. A significant positive correlation was observed among all agronomic and biochemical traits. POD was found to have a maximum positive correlation with CAT (0.947) and minimum with boll weight (0.050). PCA showed first two components accounting for 78.64% of the total variation, with 55.83% and 22.80% of the total variation, respectively. Based on multivariate analyses methods 23 genotypes have been placed in 3 groups: tolerant (cluster-3), moderately tolerant (cluster-2), and susceptible (cluster-1). In a general perspective hybrids have better performance across normal and heat stress supports the idea of hybrid adaptability across stress environments. In specific FH-458 × FH-313 cross performed best across both conditions for yield and physiological traits. Hence, the generated information from the present study would support breeders in developing heat-resilient cultivars to endure the prevailing extreme environmental conditions.

Deforestation is a common threat to the environment that has a substantial impact on the forest’s distribution across territorial boundaries. It is simply defined as the loss of forest cover, which most commonly occurs as a result of deforestation for various reasons. Pakistan is among those countries which have a very high deforestation rate. This paper analyzes the various socioeconomic factors which cause deforestation in northern Pakistan and the existing economic incentive tools for reducing deforestation. Data collected from 602 respondents were analyzed using descriptive statistics and a logistic regression model, while the Likert scale was used to determine the mean socioeconomic factor score encouraging deforestation and the economic incentives used to reduce deforestation. Gender distributions showed that the majority (65.9%) of the respondents were male while 34.1% were female. On family size, the majority of the respondents (66.8%) had a family size of 5–8. On age, between 21–25 years (46.0%) recorded the highest number. The average age of the respondents was 24 years. Educationally, 13.8% had a master’s education, 11.1% a bachelor’s education, 4.3% no formal education, 5.6% a higher education level, meaning master’s or PhD students, 56.1% had a primary education, and 9.0% had a secondary education. On occupation, the majority (50.4%) of the respondents were involved in farming as their main occupation. On income, the major income recorded a mean of 25,000 net, while the minor income recorded a mean of 15,500 net. Setting the forest ablaze, increasing farming activities, low level of literacy, increasing timber mafia, growing population, and poverty were the socioeconomic factors found. The economic incentives listed were for forest crop subsidies, an enhanced system of taxes on exploited forest products, the acquisition of well-monitored hunting licenses, alternative job opportunities, credit provision, and a limited ban on round log exports. The results of the logit regression established that rewarding socioeconomic factors were statistically significant variables at (p < 0.05). Conclusively, if adequately controlled and applied, economic incentives can be an important instrument for reducing deforestation. Therefore, deforestation activities cannot be entirely eradicated but they can be reduced to the barest minimum by properly enforcing forest policies in terms of efficient forest policing. The goals of this study are to help with the implementation of appropriate policies and decision-making in forest management, as well as to provide a foundation for future scenario analysis of deforestation potential or to investigate potential environmental and human implications.

Food security is directly coupled with enhanced production under optimized cropping intensity. Intercropping is a diversified and sustainable agricultural technique with optimized cropping intensity. Intercropping is used to obtain a higher yield and more balanced products per unit area. This study was performed at Aidyn Research Institute, Nur Sultan, Kazakhstan, in 2018 and 2019 to identify the effects of different sowing patterns on maize-white bean (Zea mays–Phaseolus vulgaris) sowing systems. The field experiment was arranged in a randomized complete block design with three replications. Göynük-98 was used for white beans, and SY Miami was used for maize, with 20 cm and 40 cm row spaces for maize, and 10 cm and 20 cm row spaces for white bean and sole maize, sole white bean, maize-white bean-maize-white bean, maize-white bean-white bean-maize and white bean-maize-maize-white bean sowing systems. The results showed that wide row spacing was better than narrow row spacing in terms of land equivalent ratio (LER) for both maize and white beans, but grain yield was higher in narrow row spacing. Yield items for both maize and white beans showed higher values in intercropping. Grain yield was higher in sole sowing. The maize-white bean-white bean-maize sowing system for maize and the white bean-maize-maize-white bean sowing system for white beans were determined as the best sowing systems according to the yield components.

Development of Source Independent Micropropagation System in Dalbergia sissoo Roxb, as a basis for Germplasm Conservation and Disease Free Plants Production