Cotton production is highly vulnerable to climate change, and heat stress is a major constraint in the cotton zone of Punjab, Pakistan. Adaptation is perceived as a critical step to deal with forecasted and unexpected climatic conditions. The objective of this study was to standardize and authenticate a cotton crop model based on climate and crop husbandry data in order to develop an adaptation package for cotton crop production in the wake of climate change. For the study, the data were collected from the cotton-growing areas of Punjab, viz. Bahawalpur and Khanewal. After the calibration and validation against field data, the Cropping System Model CSM–CROPGRO–Cotton in the shell of the decision support system for agro-technology transfer (DSSAT) was run with a future climate generated under two representative concentrations pathways (RCPs), viz. RCPs 4.5 and 8.5 with five global circulation models (GCMs). The whole study showed that a model is an artistic tool for examining the temporal variation in cotton and determining the potential impact of planting dates on crop growth, phenology, and yield. The results showed that the future climate would have drastic effects on cotton production in the project area. Reduction in seed cotton yield (SCY) was 25.7% and 32.2% under RCPs 4.5 and 8.5, respectively. The comparison of five GCMs showed that a hot/wet climate would be more damaging than other scenarios. The simulations with different production options showed that a 10% and 5% increase in nitrogen and plant population, respectively, compared to the present would be the best strategy in the future. The model further suggested that planting conducted 15 days earlier, combined with the use of water and nitrogen (fertigation), would help to improve yield with 10% less water under the future climate. Overall, the proposed adaptation package would help to recover 33% and 37% of damages in SCY due to the climate change scenarios of RCP 4.5 and 8.5, respectively. Furthermore, the proposed package would also help the farmers increase crop yield by 7.5% over baseline (current) yield.

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Recently chickpea is being grown in more than 50 countries of the world (Tsehaye et al., 2020). Pakistan ranks 3 rd in chickpea producing countries but far below than world's average chickpea productivity per Abstract | Genetic variation occurring naturally in germplasm is highly valuable resource of alleles that can be deployed for genetic improvement of a species. Screening of available genetic stock for detection of most diverse and high yielding genotypes is a pre requisite for a successful crop breeding program. For this purpose, a research experiment comprising of sixty-eight elite chickpea germplasm genotypes along with two commercial varieties were sown under tri-replicate randomized complete block design during the winter season of 2020-21. D 2 statistics, principle component analysis and cluster analysis were employed to detect the most genetically variable and high yielding chickpea genotypes. D 2 statistics extracted higher values for standard deviation and coefficient of variation indicating that the studied genotypes possess considerable amount of genetic variation in performance of studied different traits. Principle component analysis distinguished the traits into eight components. Results revealed that PC1 and 2 extracted >1 Eigen values explaining that these components have major contribution in genetic variability. Cluster analysis distributed the genotypes into four distinguished clusters. Agglomerative dendrogram of genotypes was constructed by Ward's method. On the basis of Euclidean distance it was observed that members of cluster 3 (G.

The current study was designed to introduce the new Chickpea cultivar Bittal-2022, an outcome of hybridization (90156 X 05014) followed by pedigree method of selection. This variety was tested in a series of trials on Research Stations throughout the chickpea growing areas of Pakistan. It out-yielded check variety Bittal-2016 in Station and Adaptation yield trials. In National Uniform Yield Trials (NUYT), it surpassed check variety Bittal-2016 and stood 3 rd during 2019-20 whereas in 2020-21, it surpassed check variety by 7%. Its maximum yield potential of 3958 kg/ha was achieved in CYT (Co-operative Yield Trials) during 2018-19 at RARI, Bahawalpur. The cultivar Bittal-2022 produced an overall 10% higher yield than check varieties in different yield trials conducted from 2016-17 to 2020-21. This variety is suitable for mechanical harvesting and exhibited resistance to shattering at maturity. It is moderately resistant against Ascochyta blight & Fusarium wilt and exhibited tolerance against insect pests. In addition, this approved variety needs no special production technology and fit in a better way with the existing agronomic practices. So approved cultivar Bittal-2022 is suitable for both irrigated and rain-fed chickpea cultivated areas of the Punjab province.

Pleurotusostreatus mushroom was cultivated on cotton gin waste amended with wheat bran in order to judge its growth potential. Two substrates (cotton gin waste and wheat bran) were employed alone and with different combinations. Experiment consisted of four treatments T0 (100 % cotton gin waste), T1(97% cotton gin waste + 3% wheat bran), T2(94% cotton gin waste + 6% wheat bran) and T3(91% cotton gin waste + 9% wheat bran). Data about time needed for commencement of spawn run, time needed for completion of mycelial growth, time needed for initiation of pinheads, time needed for harvesting of 1st, 2nd and 3rd flush, fresh weight of 1st, 2nd and 3rd flush harvested, total yield, pH of mushroom, total soluble solids of mushroom, acidity and ascorbic acid contents, reducing sugars, non-reducing sugars and total sugars of mushroom, total nitrogen, phosphorus and potassium contents of mushroom was recorded. T0 (100 % cotton gin waste) performed better as compared to other treatments.