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Climate change is the key challenge to agriculture in the XXI century. Future agricultural techniques in the Russian Federation should involve the optimization of land utilization. This optimization should apply algorithms for smart farming and take into consideration possible climate variations. Due to timely risk assessment, this approach would increase profitability and production sustainability of agricultural products without extra expenditures. Also, we should ground farming optimization not on available empirical data encompassing limited time intervals (month, year) or human personal evaluations but on the integral analysis of long-term information bodies using artificial intelligence. This article presents the results of a multivariate analysis of meteorological extremes which caused crop failures in Eastern and Western Europe in last 2600 years according to chronicle data and paleoreconstructions as well as reconstructions of heliophysical data for the last 9000 years. This information leads us to the conclusion that the current global warming will last for some time. However, subsequent climate changes may go in any direction. And cooling is more likely than warming; thus, we should be prepared to any scenario. Plant breeding can play a key role in solving food security problems connected with climate changes. Possible measures to adapt plant industry to the ongoing and expected climate changes are discussed. It is concluded that future breeding should be based on the use of highly adapted crops that have already been produced in pre-breeding programs, ready to meet future challenges caused by potential climate change.

Wheat is one of three main food crops around the world, which has the largest distribution area due to its adaptation to the different environments. This review considers polymorphisms and allelic variation of the vernalization response genes Vrn controlling the major adaptation traits in wheats (the genus Triticum L.): growth habit (spring vs. winter) and length of vegetative period (earliness). The review summarizes available information on the allelic diversity of the Vrn genes and discusses molecular-level relationships between Vrn polymorphisms and their effect on growth habit (spring vs. winter) and earliness (length vegetative period in spring plants) in di-, tetra- and hexaploid wheat species. A unique attempt has been made to relate information on mutations (polymorphisms) in dominant Vrn alleles to the values of the commercially most important trait “length of plant vegetative period (earliness)”. The effects of mutations (polymorphisms) in the recessive vrn genes on vernalization requirement in winter wheats are considered, and this trait was formalized. The evolution of the winter/spring growth habit in the genus Triticum species is discussed. A scheme of phylogenetic interactions between Vrn alleles was constructed on the basis of these polymorphisms; the paper considers the possibilities to enhance the diversity of polymorphisms for the dominant Vrn genes and their alleles using wheat related species and rarely used alleles and discusses the prospects of breeding for improved earliness for concrete agroecological zones.

This article presents two combinatorial genetic algorithms (GA), unequal earliness tardiness-GA (UET-GA) and job-dependent earliness tardiness-GA (JDET-GA) for the single-machine scheduling problem to minimize earliness tardiness (ET) cost. The sequence of jobs produced in basic UET and JDET as a chromosome is added to the random population of GA. The best sequence from each epoch is also injected as a population member in the subsequent epoch. The proposed improvement seeks to achieve convergence in less time to search for an optimal solution. Although the GA has been implemented very successfully on many different types of optimization problems, it has been learnt that the algorithm has a search ability difficulty that makes computations NP-hard for types of optimization problems, such as permutation-based optimization problems. The use of a plain random population initialization results in this flaw. To reinforce the random population initialization, the proposed enhancement is utilized to obtain convergence and find a promising solution. The cost is further significantly lowered offering the due date as a decision variable with JDET-GA. Multiple tests were run on well-known single-machine benchmark examples to demonstrate the efficacy of the proposed methodology, and the results are displayed by comparing them with the fundamental UET and JDET approaches with a notable improvement in cost reduction.

The present study was aimed to identify potential Yellow Mosaic Virus (YMV) resistant donors and YMV linked markers for easy and efficient screening of germplasm. Forty - six blackgram genotypes were screened for Yellow Mosaic Virus (YMV) tolerance and yield traits under natural field conditions during summer, 2020 at Dryland farm, S.V.Agricultural College, Tirupati along with molecular validation with 15 SSR (Simple Sequence Repeats) markers associated with YMV tolerance. The genotypes viz., LBG-884, LBG-946, TBG-141, TBG-129, TBG-138, TBG-139, TBG-130 and GBG-1 displayed zero YMV incidence. TBG-104 and VBN-6 were identified as ideal cultivars for yield, earliness and YMV tolerance. The markers viz., CEDG 097, CEDG 180, CEDG 044, and CEDG 139 were adjudged as informative markers as evident indicated by their high PIC scores and Nei’s diversity index values. On scrutiny of the selection efficiency of all the alleles, CEDG 180 was found to be more efficient in differentiating resistant and susceptible genotypes. Visual comparison of trait profiles using genotype by trait (GT) biplot analysis identified the genotypes viz., TBG-104 and VBN-6 as ideal cultivars that serve as most desirable parents in breeding programs aimed at developing short duration, high-yielding varieties with YMV tolerance.

Early maturity and simultaneous increase in yield of cotton are pivotal for increasing the productivity of cropping systems involving cotton. Current two-year study was performed to simultaneously enhance the earliness and yield of cotton by modulating plant population (PP) (5.3 and 8.8 plants m−2), foliar boron (B) (0, 0.6 and 1.2 g/L B) and 0.07 g/L mepiquat chloride (MC) solution (at squaring and flowering stages) application. Internodes length was exalted at high PP (8.8 plants m-2) and B (1.2 g/L B), while declined by MC. Nevertheless, nodes above the white flower and cracked boll were decreased at high PP, and the application of B and MC indicated earlier cutout. Similarly, high PP, and application of 1.2 g/L B and MC at squaring reduced calendar and thermal time needed for flowering and boll opening. The boll maturation period was not affected by the application of B and MC but declined at high PP. Earliness index, production rate index (PRI) and seed cotton yield were increased at high PP, application of 1.2 g/L B and MC at squaring. In crux, increasing PP and B concentration, and MC application at squaring resulted in early maturity and enhanced seed cotton yield by modulating plant structure and time required for various phenophases. [ABSTRACT FROM AUTHOR]

Yellow mosaic disease (YMD) remains a major constraint in mungbean (Vigna radiata (L.)) production; while short-duration genotypes offer multiple crop cycles per year and help in escaping terminal heat stress, especially during summer cultivation. A comprehensive genotyping by sequencing (GBS)-based genome-wide association studies (GWAS) analysis was conducted using 132 diverse mungbean genotypes for traits like flowering time, YMD resistance, soil plant analysis development (SPAD) value, trichome density, and leaf area. The frequency distribution revealed a wide range of values for all the traits. GBS studies identified 31,953 high-quality single nucleotide polymorphism (SNPs) across all 11 mungbean chromosomes and were used for GWAS. Structure analysis revealed the presence of two genetically distinct populations based on ΔK. The linkage disequilibrium (LD) varied throughout the chromosomes and at r2 = 0.2, the mean LD decay was estimated as 39.59 kb. Two statistical models, mixed linear model (MLM) and Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway (BLINK) identified 44 shared SNPs linked with various candidate genes. Notable candidate genes identified include FPA for flowering time (VRADI10G01470; chr. 10), TIR-NBS-LRR for mungbean yellow mosaic India virus (MYMIV) resistance (VRADI09G06940; chr. 9), E3 ubiquitin-protein ligase RIE1 for SPAD value (VRADI07G28100; chr. 11), WRKY family transcription factor for leaf area (VRADI03G06560; chr. 3), and LOB domain-containing protein 21 for trichomes (VRADI06G04290; chr. 6). In-silico validation of candidate genes was done through digital gene expression analysis using Arabidopsis orthologous (compared with Vigna radiata genome). The findings provided valuable insight for marker-assisted breeding aiming for the development of YMD-resistant and early-maturing mungbean varieties.

Machine scheduling problems (MSP) are considered as one of the most important classes of combinatorial optimization problems. In this paper, the problem of job scheduling on a single machine is studied to minimize the multiobjective and multiobjective objective function. This objective function is: total completion time, total lead time and maximum tardiness time, respectively, which are formulated as are formulated. In this study, a mathematical model is created to solve the research problem. This problem can be divided into several sub-problems and simple algorithms have been found to find the solutions to these sub-problems and compare them with efficient solutions. For this problem, some rules that provide efficient solutions have been proved and some special cases have been introduced and proved since the problem is an NP-hard problem to find some efficient solutions that are efficient for the discussed problem 1// and good or optimal solutions for the multi-objective functions 1// ,, and emphasize the importance of the dominance rule (DR), which can be applied to this problem to improve efficient solutions.

Developing early maturing lentil has the potential to minimize yield losses, mainly during terminal drought. Whole-genome resequencing (WGRS) based QTL-seq identified the loci governing earliness in lentil. The genetic analysis for maturity duration provided a good fit to 3:1 segregation (F 2 ), indicating earliness as a recessive trait. WGRS of Globe Mutant (late parent), late-flowering, and early-flowering bulks (from RILs) has generated 1124.57, 1052.24 million raw and clean reads, respectively. The QTL-Seq identified three QTLs (LcqDTF3.1, LcqDTF3.2, and LcqDTF3.3) on chromosome 3 having 246244 SNPs and 15577 insertions/deletions (InDels) and 13 flowering pathway genes. Of these, 11 exhibited sequence variations between bulks and validation (qPCR) revealed a significant difference in the expression of nine candidate genes (LcGA20oxG, LcFRI, LcLFY, LcSPL13a, Lcu.2RBY.3g060720, Lcu.2RBY.3g062540, Lcu.2RBY.3g062760, LcELF3a, and LcEMF1). Interestingly, the LcELF3a gene showed significantly higher expression in late-flowering genotype and exhibited substantial involvement in promoting lateness. Subsequently, an InDel marker (I-SP-383.9; LcELF3a gene) developed from LcqDTF3.2 QTL region showed 82.35% PVE (phenotypic variation explained) for earliness. The cloning, sequencing, and comparative analysis of the LcELF3a gene from both parents revealed 23 SNPs and InDels. Interestingly, a 52 bp deletion was recorded in the LcELF3a gene of L4775, predicted to cause premature termination of protein synthesis after 4 missense amino acids beyond the 351st amino acid due to the frameshift during translation. The identified InDel marker holds significant potential for breeding early maturing lentil varieties., (© 2024 The Author(s). Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.)

Background: Robotics Assembly Cells (RAC) have been designed to meet the flexibility requirements demanded by today's globalized market. The objective is to manufacture a vast variety of products at a low cost, which requires equipment with a high level of flexibility, such as robots. The need to schedule a great variety of jobs in an RAC is a very relevant issue, as efficiency and productivity depend on the sequence in which jobs are scheduled. Studies around this matter have developed models with analytical and heuristic approaches, as well as simulation methods and genetic algorithms, seeking to improve performance measures based mainly on time, utilization, and costs. Method: The purpose of this article is to formulate an exact mathematical model using mixed-integer linear programming (MILP) to optimize small scheduling problems. The objective is to minimize the measure of performance related to the tardiness and earliness of jobs. This optimization aims to mitigate the effects of delays in product deliveries, queue times, and work-in-process inventory in subsequent processes. Doing so facilitates adherence to agreed-upon delivery deadlines and prevents bottlenecks in the assembly cell. Results: The proposed mathematical model generates optimal solutions to the job scheduling problem in the assembly cell, which serves as a case study. This addresses the need to minimize tardiness to meet delivery deadlines or minimize earliness while avoiding an increase in work-in-process inventories. The model ensures that optimal scheduling decisions are made to optimize both delivery performance and inventory levels. Conclusions: Due to the NP-hard complexity of the scheduling problem under study, the proposed mathematical model demonstrates computational efficiency in solving scheduling problems with fewer than 20 jobs. The model is designed to handle such smaller-scale problems within a reasonable computational time frame, considering the inherent complexity of the scheduling problem.

Background: As blackgram cultivation is majorly spread in rain fed areas, breeding short duration and high yielding blackgram varieties is of profound importance to tackle terminal moisture stress and reap impressive yields by breaking the yield plateau. Hence, the present study was aimed to identify highly heterotic cross combinations for yield and earliness. Methods: Six parents along with 15 F1s were evaluated (rabi, 2019) for seed yield and its component traits along with earliness to estimate the magnitude of heterosis. Result: The cross LBG-752 x TBG-104 exhibited heterosis estimates in desirable direction for yield and earliness. The next best crosses were LBG-752 x PU-31, TU-40 x TBG-104, LBG-752 x TU-40 and IPU-2-43 x TBG-104. Because of its autogamous genetic architecture and biological constraints in large scale economic hybrid seed production, heterosis could be exploited only by isolating the early maturing and high yielding segregants followed by bi-parental or recurrent selection in early segregating generations and single plant selection in subsequent generations that would result in short duration and high yielding blackgram variety that fits well into different ecological niches. [ABSTRACT FROM AUTHOR]

Earliness in crop plants has a vital role in prevention of heat-induced drought stress and in combating global warming, which is predicted to exacerbate in the near future. Furthermore, earliness may expand production into northern areas or higher altitudes, having relatively shorter growing season and may also expand arable lands to meet global food demands. The primary objective of the present study was to investigate quantitative trait loci (QTLs) for super-earliness and important agro-morphological traits in a recombinant inbred line (RIL) population derived from an interspecific cross. A population of 114 RILs developed through single-seed descent from an interspecific cross involving Pisum sativum L. and P. fulvum Sibth. et Sm. was evaluated to identify QTLs for super-earliness and important agro-morphological traits. A genetic map was constructed with 44 SSRs markers representing seven chromosomes with a total length of 262.6 cM. Of the 14 QTLs identified, two were for super-earliness on LG2, one for plant height on LG3, six for number of pods per plant on LG2, LG4, LG5 and LG6, one for number of seeds per pod on LG6, one for pod length on LG4 and three for harvest index on LG3, LG5, and LG6. AA205 and AA372-1 flanking markers for super-earliness QTLs were suggested for marker-assisted selection (MAS) in pea breeding programs due to high heritability of the trait. This is the first study to map QTLs originating from P. sativum and P. fulvum recently identified species with super-earliness character and the markers (AA205 and AA372-1) linked to QTLs were valuable molecular tools for pea breeding.

In this paper, we study the scheduling of n jobs on a single machine. Each of the n jobs will be processed without interruption and becomes available for processing at time zero. The goal is to find a processing order for the jobs, minimizing the total completion time, total late work, total earliness time, and maximum earliness maximum tardiness. The posed problems in this paper are as follows: The first problem is to minimize the multi-criteria, which includes minimizing the total completion time, total late work, total earliness time, maximum earliness, and maximum tardiness that are denoted by ΣCj, ΣVj, ΣΕj, Emax, and Tmax, respectively. The second problem is to minimize the multi-objective functions (ΣCj + ΣVj, +ΣΕj; + Emax + Tmax). The theoretical section will present the mathematical formula for the discussed problem. Because these problems are NP- hard problems. It is difficult to determine the efficient (optimal) solution set for these problems. Some special cases are shown and proven to find efficient (optimal) solutions to the discussed problem. The significance of the dominance rule can be applied to problems to improve and to get good solutions that will be highlighted. [ABSTRACT FROM AUTHOR]

The presented study investigated the scheduling regarding jobs on a single machine. Each job will be processed with no interruptions and becomes available for the processing at time 0. The aim is finding a processing order with regard to jobs, minimizing total completion time , total late work , and maximal tardiness which is an NP-hard problem. In the theoretical part of the present work, the mathematical formula for the examined problem will be presented, and a sub-problem of the original problem of minimizing the multi-objective functions is introduced. Also, then the importance regarding the dominance rule (DR) that could be applied to the problem to improve good solutions will be shown. While in the practical part, two exact methods are important; a Branch and Bound algorithm (BAB) and a complete enumeration (CEM) method are applied to solve the three proposed MSP criteria by finding a set of efficient solutions. The experimental results showed that CEM can solve problems for up to jobs. Two approaches of the BAB method were applied: the first approach was BAB without dominance rule (DR), and the BAB method used dominance rules to reduce the number of sequences that need to be considered. Also, this method can solve problems for up to , and the second approach BAB with dominance rule (DR), can solve problems for up to jobs in a reasonable time to find efficient solutions to this problem. In addition, to find good approximate solutions, two heuristic methods for solving the problem are proposed, the first heuristic method can solve up to jobs, while the second heuristic method can solve up to jobs. Practical experiments prove the good performance regarding the two suggested approaches for the original problem. While for a sub-problem the experimental results showed that CEM can solve problems for up to jobs, the BAB without dominance rule (DR) can solve problems for up to , and the second approach BAB with dominance rule (DR), can solve problems for up to jobs in a reasonable time to find efficient solutions to this problem. Finally, the heuristic method can solve up to jobs. Arithmetic results are calculated by coding (programming) algorithms using (MATLAB 2019a)

The global and local climate changes determine the producing of highly-adaptive common (bread) wheat commercial cultivars of a new generation whose optimal earliness matches the climatic features of the territory where the cultivars are farmed. Principal component analysis involving our own and published data has been applied to investigate 98 commercial common wheat cultivars from Western and Eastern Siberia comparing their morphotypes; cultivar zoning time; length of the vegetation period; 1000-grain weight, and inheritance of spring growth habit. It demonstrated that the dominant Vrn gene polymorphism determining the spring growth habit of the Siberian cultivars was minimally polymorphic. In 75 % of the tested cultivars, the spring growth habit was controlled by digenic, namely dominant Vrn-A1 and Vrn-B1 genes. In 25 % of them (24 cultivars), spring growth habit is controlled by a single gene. In 19 and 5 of these cultivars spring growth habit is controlled by only one dominant gene, Vrn-B1 or Vrn-A1, respectively. In cv. Tulun 15, a trigenic control was identified. A conclusion about the optimality of the digenic control for the climatic conditions of both Western and Eastern Siberia has been confirmed. However, since none of the tested cultivars had the dominant Vrn-D1 gene typical of the regions of China and Central Asia bordering Siberia, it can be considered as an additional argument in favor of the European origin of Siberian common wheat cultivars. The revealed high frequency of the Vrn-B1c allele in the Western Siberian cultivars and the Vrn-B1a allele in the Eastern Siberian cultivars suggests their selectivity. The analysis also confirmed the dominance of red glume (ferrugineum, milturum) and awned spike (ferrugineum, erythrospermum) varieties in the Eastern Siberian cultivars, and white glume and awnedless spike (lutescens and albidum) ones in the Western Siberian cultivars. Small grain size cultivars are more typical of Eastern than Western Siberia. The retrospective analysis based on the cultivars’ zoning time included in the “State Register for Selection Achievements Admitted for Usage” brought us to the conclusion that the earliness/lateness of modern Siberian commercial cultivars was not regionally but rather zonally-associated (taiga, subtaiga, forest-steppe and steppe zones).

Introduction of exotic clones into the pedigree of commercial cashew clones could constitute a viable strategy to overcome the current low early nut yield and nut weight of the crop in West Africa. The aim of this study was to assess the combining abilities of Beninese, Brazilian and Ghanaian clones for early nut yield and nut weight. Twelve F1 hybrids were evaluated in the field for five traits such as stem diameter increment, canopy spread, nut yield, nut weight and cropping efficiency. Significant difference (p ≤ .01) was observed for most of the traits. Nut weight varied from 5.3 to 10.1 g/year, whilst nut yield ranged from 666.1 to 872.8 kg/ha/year among the top five crosses in the third to fifth year after planting. The Beninese (BE) progenies were comparable to the Ghanaian (SG) progenies for early nut yield but inferior to the Ghanaian and Brazilian (A) progenies for nut weight. Pearson correlation coefficient estimate (r = 0.74; p ≤ .01) suggest that, selecting for canopy spread in the north-south direction might improve early nut yield. GCA effects were more important than SCA effects. Narrow-sense heritability was moderate and exceeded 50% for all the traits. BE203 and SG224 showed positive GCA for early nut yield, whereas A2 and SG273 showed positive GCA for nut weight. Our study suggest that the Brazilian, Beninese and Ghanaian clones had different merits as potential parents for early nut yield and nut weight and could constitute a suitable genetic resource for improving cashew productivity.

Understanding the genetic architecture of complex traits is the major thrust in plant breeding programs. Hence, the present investigation was carried out at a dry land farm of S.V. Agricultural College, Tirupati during rabi, 2020 to elucidate the gene action governing seed yield, yield related traits and earliness in blackgram. The experimental material consisted of six generations viz., P1, P2, F1, F2, B1 and B2 of five blackgram crosses viz., LBG-752 x TBG- 104, LBG-752 x PU-31, LBG-752 x TU-40, TU-40 x TBG-104 and IPU-2-43 x TBG-104. The scaling tests suggested that the simple additive–dominance model is inadequate in elucidating gene action in all the crosses for all the traits. Generation mean analysis based on six parameter model made evident that gene interactions varied cross-wise as well as character-wise. A complementary type of epistasis was observed for majority of the yield attributing traits, while days to 50 % flowering and days to maturity had duplicate epistasis in majority of the cross combinations. High yielding and short duration blackgram varieties could be developed by exploiting both additive and non-additive gene effects in the present set of breeding material through inter-mating of desirable transgressive segregants in the early generations followed by simple pedigree selection.

The geographical dispersion of collaborative factories can provide cost-saving potential for manufacturers and lead them to easier fit the global markets. On the other hand, in such networks of factories, coordination is especially important for the just-in-time delivery of orders. This study investigates a new configuration of factories in a network of collaborative manufacturing. In the first stage, some independent suppliers produce and deliver the different components of the final products to the assembly factory. Each supplier can produce a particular component of a final product. In the assembly factory, the final products are assembled. The objective is to determine the optimal schedule of the jobs in each factory to minimize the sum of earliness and tardiness. A mixed-integer formulation for this problem is proposed, which can find the optimal solution for the small-size instances. The iterated local search methods are also developed to cope with larger instances. Computational experiments show that the iterated local search methods outperform the well-known iterated greedy method in literature. [ABSTRACT FROM AUTHOR]

The systematic identification of insertion/deletion (InDel) length polymorphisms from the entire lentil genome can be used to map the quantitative trait loci (QTL) and also for the marker-assisted selection (MAS) for various linked traits. The InDels were identified by comparing the whole-genome resequencing (WGRS) data of two extreme bulks (early- and late-flowering bulk) and a parental genotype (Globe Mutant) of lentil. The bulks were made by pooling 20 extreme recombinant inbred lines (RILs) each, derived by crossing Globe Mutant (late flowering parent) with L4775 (early flowering parent). Finally, 734,716 novel InDels were identified, which is nearly one InDel per 5,096 bp of lentil genome. Furthermore, 74.94% of InDels were within the intergenic region and 99.45% displayed modifier effects. Of these, 15,732 had insertions or deletions of 20 bp or more, making them amenable to the development of PCR-based markers. An InDel marker I-SP-356.6 (chr. 3; position 356,687,623; positioned 174.5 Kb from the LcFRI gene) was identified as having a phenotypic variance explained (PVE) value of 47.7% for earliness when validated in a RIL population. Thus, I-SP-356.6 marker can be deployed in MAS to facilitate the transfer of the earliness trait to other elite late-maturing cultivars. Two InDel markers viz., I-SP-356.6 and I-SP-383.9 (chr. 3; linked to LcELF3a gene) when tested in 9 lentil genotypes differing for maturity duration, clearly distinguished three early (L4775, ILL7663, Precoz) and four late genotypes (Globe Mutant, MFX, L4602, L830). However, these InDels could not be validated in two genotypes (L4717, L4727), suggesting either absence of polymorphism and/or presence of other loci causing earliness. The identified InDel markers can act as valuable tools for MAS for the development of early maturing lentil varieties.