Global warming has increased the temperature significantly over a large extent both spatially and temporally. The threat of heat stress during the germination and seedling establishment stages in the wheat crop is now more prevalent than ever before. The present experiment assessed the effect of elevated temperature on the germination and early seedling growth of wheat genotypes. The seeds were sown under four temperatures, viz., 20 °C, 25 °C, 30 °C and 35 °C; the germination, seedling vigor and enzyme activities in 8-day-old seedlings were assessed. The temperature significantly influenced germination and early seedling growth. The germination percentage at 20 and 25 °C was statistically on par with and higher than at 30 and 35 °C. The seedling vigor parameters were maximum at 25 °C and showed a reduction at higher temperatures. Genotypic differences were observed for early heat stress as the genotypes WH 730, WH 1123 and HD 2967 showed tolerance towards heat stress during germination, whereas the genotypes PBW 725 and WH 1105 were susceptible. Antioxidant enzyme activities in seedlings increased with the rise in temperature. Catalase, peroxidase and superoxide dismutase enzymes showed increased activities at higher temperature levels.

Seed priming is a simple and cost effective method to obtain a better plant stand under diverse environmental conditions. The current study was designed to determine the optimal priming duration and water volume for wheat seed. For this experiment, three wheat genotypes with distinct genetic and adaptive backgrounds were chosen. Seeds of each genotype were hydroprimed for 7 durations, i.e. 1, 2, 4, 8, 12, 16, and 20 hours, in three different water volumes, i.e. half, equal, and double volume with respect to seed weight and then surface dried for 1 hour. The control was unprimed (dry) seed. The germination characteristics and seedling vigour potential of hydroprimed seeds were evaluated in the lab by recording several parameters such as germination percentage and speed, seedling growth, and vigour indices at two different temperature levels. The results showed that optimal duration for hydropriming of wheat seed is 12 hours with an equal volume with respect to original seed weight, closely followed by 8 hours with double volume. Reduction in seed performance was observed at 16 and 20 hours priming particularly at double volume treatment. Effect of temperature on seed germination showed improvement in seedling vigour at 25°C when compared to 20°C, although effect on germination percentage was non-significant. Volume of water and priming duration showed significant interactive effects demonstrating that a higher volume can give equivalent results at a shorter duration and vice versa. Another experiment was also conducted to compare the on-farm priming (surface dried seed) with conventional priming (seed re-dried to original moisture) taking 3 potential durations i.e. 8, 12 and 16 hours. Results revealed that both priming methods were statistically at par in terms of germination percentage, while, surface drying resulted in better seedling vigour and speed of germination.

Mixed data is a combination of continuous and categorical variables and occurs frequently in fields such as agriculture, remote sensing, biology, medical science, marketing, etc., but only limited work has been done with this type of data. In this study, data on continuous and categorical characters of 452 genotypes of cotton (Gossypium hirsutum) were obtained from an experiment conducted by the Central Institute of Cotton Research (CICR), Sirsa, Haryana (India) during the Kharif season of the year 2018–2019. The machine learning (ML) classifiers/models, namely k-nearest neighbor (KNN), Classification and Regression Tree (CART), C4.5, Naïve Bayes, random forest (RF), bagging, and boosting were considered for cotton genotypes classification. The performance of these ML classifiers was compared to each other along with the linear discriminant analysis (LDA) and logistic regression. The holdout method was used for cross-validation with an 80:20 ratio of training and testing data. The results of the appraisal based on hold-out cross-validation showed that the RF and AdaBoost performed very well, having only two misclassifications with the same accuracy of 97.26% and the error rate of 2.74%. The LDA classifier performed the worst in terms of accuracy, with nine misclassifications. The other performance measures, namely sensitivity, specificity, precision, F1 score, and G-mean, were all together used to find out the best ML classifier among all those considered. Moreover, the RF and AdaBoost algorithms had the highest value of all the performance measures, with 96.97% sensitivity and 97.50% specificity. Thus, these models were found to be the best in classifying the low- and high-yielding cotton genotypes.

Coriander (Coriandrum sativum L.) is an important seed spices crop of family Apiaceae (Umbelliferae) and possess 2n=22 chromosomes with cross-pollination as mode of reproduction. A field experiment was conducted at CCS Haryana Agricultural University, Hisar to study the effect of foliage cuttings on seed yield and quality of Coriander. The Research material comprised of four genotypes viz. DH-5, DH-36, DH-228 and DH-246 was grown with three replications in factorial RBD. The foliage cutting was taken to make different treatments i.e. C₀ (without cutting), C₁ (one cutting at 45 days after sowing) and C₂ (two cuttings at 45 days and 60 days after sowing). The investigation resulted that number of foliage cuttings reduced the plant growth, seed yield and quality of coriander. The crop without cutting of foliage gave the maximum plant growth along with highest seed yield which was followed by one cutting and lowest performance was observed after two cuttings. The increase in number of foliage cuttings of coriander significantly reduced the growth parameters of plant such as plant height, number of branches per plant, number of umbels per plant, number of seeds per umbel, number of seeds per umbellate, foliage and seed yield. The increase in number of foliage cutting also influenced the seed quality of coriander seed. The best quality seed with highest value of seed quality parameters such as test weight, standard germination, seedling length, seedling dry weight, vigour index-I, vigour index-II, field emergence index and seedling establishment, seed was harvested from without foliage cutting followed by one cutting at 45 days and two cuttings at 45 and 60 days after sowing. The genotype Hisar Anand (DH-5) was found best seed producing genotype. Whereas, Hisar Bhoomit (DH-228) was found best genotype both for foliage yield and seed yield.

A study of uniformity trial for assessing the nature and magnitude of soil variability and to determine the optimum size and shape of plots was conducted on 66A507 Pioneer hybrid of Sunflower crop at Research Farm of CCS Haryana Agricultural University, Hisar, Haryana during the February 2014 to June 2014, on a field of size 35 m × 40 m which after eliminating border effects reduced to 32 m × 36 m. The total area (1152 m²) divided into 1152 basic units, each have size 1 m × 1 m and yield data of all the basic units was recorded separately for further investigations. The coefficient of variation of yield of individual harvested units was observed to be as high as 13.92 per cent indicating high degree of soil heterogeneity. The coefficient of variation decreased with increase in plot size in both the directions i.e. when plots were elongated in N-S direction or elongated in E-W direction and the decrease was near about same for both the directions but was more when plots were elongated in N-S direction (96.48 per cent decrease). The long-narrow plots elongated in N-S direction were found to be more useful than the compact and square plots. It was observed that the smallest plot has the maximum efficiency and the optimum plot size was estimated to be 2 m².