Evaluation of Annual Clover Ecotypes by Using Drought Tolerance Indices

To evaluate clover ecotypes by using  drought tolerance indices, 17 annual clover ecotypes were tested in a split-plot experiment by using randomized complete  block design with three replications, under two irrigated and rain-fed conditions in the Saatlo Research Station in Urmia, Iran. In this study, based on the dry matter yield in stressed (Ys) and non-stressed (Yp) conditions, quantitative values of drought tolerance indices of mean productivity index (MP), tolerance index (TOL), geometric mean productivity index (GMP), harmonic mean index (HM), stress susceptibility index (SSI), and stress tolerance index (STI) were calculated. There was a significant difference among the ecotypes as to their yields under irrigated and rain-fed conditions, which indicated the existence of genetic diversity and the possibility of selection for drought tolerance and using them in breeding programs for further genetic. The correlations among drought indices and Yp and Ys showed that MP, GMP, HM, and STI were highly correlated with Yp and Ys. Cluster analysis categorized tolerant ecotypes No. 11, 2, 13, 8 and 10 in the same group and the others in the sensitive one. Based on the values of indices and higher dry matter yield, in both stress and non-stress conditions, ecotype No. 11 (T.resupinatum L.) was recognized to be as the most tolerant ecotype against drought

Adoption of snowball sampling technique with distance boundaries to assess the productivity issue faced by micro and small cocoa producers in Cusco

The food supply chain has gained impulse over the past few years induced by the rising global demand for food; therefore, much emphasis is placed upon examining this class of supply chains. It also faces constant production, storage, and distribution challenges, wherein the key link for proper operation is the farmer, who engages in the agricultural sector, heavily impacted by low crop productivity, which interfer with economic development at a national level. Consequently, it is important to assess those farmers who belong to micro and small enterprises in the agricultural sector. Due to the characteristics of the population, a nonprobability sampling technique was used to assess micro and small cocoa producers in La Convención Province, Cusco, Peru. To such end, a snowball sampling model with distance boundaries was adopted because the population is unknown and hard to reach